Patent ID: 12191987

DETAILED DESCRIPTION OF THE DRAWINGS

While the concepts of the present disclosure are susceptible to various modifications and alternative forms, specific embodiments thereof have been shown by way of example in the drawings and will be described herein in detail. It should be understood, however, that there is no intent to limit the concepts of the present disclosure to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives consistent with the present disclosure and the appended claims.

References in the specification to “one embodiment,” “an embodiment,” “an illustrative embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may or may not necessarily include that particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described. Additionally, it should be appreciated that items included in a list in the form of “at least one A, B, and C” can mean (A); (B); (C); (A and B); (A and C); (B and C); or (A, B, and C). Similarly, items listed in the form of “at least one of A, B, or C” can mean (A); (B); (C); (A and B); (A and C); (Band C); or (A, B, and C).

The disclosed embodiments may be implemented, in some cases, in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried by or stored on a transitory or non-transitory machine-readable (e.g., computer-readable) storage medium, which may be read and executed by one or more processors. A machine-readable storage medium may be embodied as any storage device, mechanism, or other physical structure for storing or transmitting information in a form readable by a machine (e.g., a volatile or non-volatile memory, a media disc, or other media device).

In the drawings, some structural or method features may be shown in specific arrangements and/or orderings. However, it should be appreciated that such specific arrangements and/or orderings may not be required. Rather, in some embodiments, such features may be arranged in a different manner and/or order than shown in the illustrative figures. Additionally, the inclusion of a structural or method feature in a particular figure is not meant to imply that such feature is required in all embodiments and, in some embodiments, may not be included or may be combined with other features.

FIG.1illustrates a conceptual overview of a data center100that may generally be representative of a data center or other type of computing network in/for which one or more techniques described herein may be implemented according to various embodiments. As shown inFIG.1, data center100may generally contain a plurality of racks, each of which may house computing equipment comprising a respective set of physical resources. In the particular non-limiting example depicted inFIG.1, data center100contains four racks102A to102D, which house computing equipment comprising respective sets of physical resources (PCRs)105A to105D. According to this example, a collective set of physical resources106of data center100includes the various sets of physical resources105A to105D that are distributed among racks102A to102D. Physical resources106may include resources of multiple types, such as—for example—processors, co-processors, accelerators, field programmable gate arrays (FPGAs), memory, and storage. The embodiments are not limited to these examples.

The illustrative data center100differs from typical data centers in many ways. For example, in the illustrative embodiment, the circuit boards (“sleds”) on which components such as CPUs, memory, and other components are placed are designed for increased thermal performance. In particular, in the illustrative embodiment, the sleds are shallower than typical boards. In other words, the sleds are shorter from the front to the back, where cooling fans are located. This decreases the length of the path that air must to travel across the components on the board. Further, the components on the sled are spaced further apart than in typical circuit boards, and the components are arranged to reduce or eliminate shadowing (i.e., one component in the air flow path of another component). In the illustrative embodiment, processing components such as the processors are located on a top side of a sled while near memory, such as DIMMs, are located on a bottom side of the sled. As a result of the enhanced airflow provided by this design, the components may operate at higher frequencies and power levels than in typical systems, thereby increasing performance. Furthermore, the sleds are configured to blindly mate with power and data communication cables in each rack102A,102B,102C,102D, enhancing their ability to be quickly removed, upgraded, reinstalled, and/or replaced. Similarly, individual components located on the sleds, such as processors, accelerators, memory, and data storage drives, are configured to be easily upgraded due to their increased spacing from each other. In the illustrative embodiment, the components additionally include hardware attestation features to prove their authenticity.

Furthermore, in the illustrative embodiment, the data center100utilizes a single network architecture (“fabric”) that supports multiple other network architectures including Ethernet and Omni-Path. The sleds, in the illustrative embodiment, are coupled to switches via optical fibers, which provide higher bandwidth and lower latency than typical twisted pair cabling (e.g., Category 5, Category 5e, Category 6, etc.). Due to the high bandwidth, low latency interconnections and network architecture, the data center100may, in use, pool resources, such as memory, accelerators (e.g., graphics accelerators, FPGAs, ASICs, etc.), and data storage drives that are physically disaggregated, and provide them to compute resources (e.g., processors) on an as needed basis, enabling the compute resources to access the pooled resources as if they were local. The illustrative data center100additionally receives utilization information for the various resources, predicts resource utilization for different types of workloads based on past resource utilization, and dynamically reallocates the resources based on this information.

The racks102A,102B,102C,102D of the data center100may include physical design features that facilitate the automation of a variety of types of maintenance tasks. For example, data center100may be implemented using racks that are designed to be robotically-accessed, and to accept and house robotically-manipulatable resource sleds. Furthermore, in the illustrative embodiment, the racks102A,102B,102C,102D include integrated power sources that receive a greater voltage than is typical for power sources. The increased voltage enables the power sources to provide additional power to the components on each sled, enabling the components to operate at higher than typical frequencies.

FIG.2illustrates an exemplary logical configuration of a rack202of the data center100. As shown inFIG.2, rack202may generally house a plurality of sleds, each of which may comprise a respective set of physical resources. In the particular non-limiting example depicted inFIG.2, rack202houses sleds204-1to204-4comprising respective sets of physical resources205-1to205-4, each of which constitutes a portion of the collective set of physical resources206comprised in rack202. With respect toFIG.1, if rack202is representative of—for example—rack102A, then physical resources206may correspond to the physical resources105A comprised in rack102A. In the context of this example, physical resources105A may thus be made up of the respective sets of physical resources, including physical storage resources205-1, physical accelerator resources205-2, physical memory resources205-3, and physical compute resources205-5comprised in the sleds204-1to204-4of rack202. The embodiments are not limited to this example. Each sled may contain a pool of each of the various types of physical resources (e.g., compute, memory, accelerator, storage). By having robotically accessible and robotically manipulatable sleds comprising disaggregated resources, each type of resource can be upgraded independently of each other and at their own optimized refresh rate.

FIG.3illustrates an example of a data center300that may generally be representative of one in/for which one or more techniques described herein may be implemented according to various embodiments. In the particular non-limiting example depicted inFIG.3, data center300comprises racks302-1to302-32. In various embodiments, the racks of data center300may be arranged in such fashion as to define and/or accommodate various access pathways. For example, as shown inFIG.3, the racks of data center300may be arranged in such fashion as to define and/or accommodate access pathways311A,311B,311C, and311D. In some embodiments, the presence of such access pathways may generally enable automated maintenance equipment, such as robotic maintenance equipment, to physically access the computing equipment housed in the various racks of data center300and perform automated maintenance tasks (e.g., replace a failed sled, upgrade a sled). In various embodiments, the dimensions of access pathways311A,311B,311C, and311D, the dimensions of racks302-1to302-32, and/or one or more other aspects of the physical layout of data center300may be selected to facilitate such automated operations. The embodiments are not limited in this context.

FIG.4illustrates an example of a data center400that may generally be representative of one in/for which one or more techniques described herein may be implemented according to various embodiments. As shown inFIG.4, data center400may feature an optical fabric412. Optical fabric412may generally comprise a combination of optical signaling media (such as optical cabling) and optical switching infrastructure via which any particular sled in data center400can send signals to (and receive signals from) each of the other sleds in data center400. The signaling connectivity that optical fabric412provides to any given sled may include connectivity both to other sleds in a same rack and sleds in other racks. In the particular non-limiting example depicted inFIG.4, data center400includes four racks402A to402D. Racks402A to402D house respective pairs of sleds404A-1and404A-2,404B-1and404B-2,404C-1and404C-2, and404D-1and404D-2. Thus, in this example, data center400comprises a total of eight sleds. Via optical fabric412, each such sled may possess signaling connectivity with each of the seven other sleds in data center400. For example, via optical fabric412, sled404A-1in rack402A may possess signaling connectivity with sled404A-2in rack402A, as well as the six other sleds404B-1,404B-2,404C-1,404C-2,404D-1, and404D-2that are distributed among the other racks402B,402C, and402D of data center400. The embodiments are not limited to this example.

FIG.5illustrates an overview of a connectivity scheme500that may generally be representative of link-layer connectivity that may be established in some embodiments among the various sleds of a data center, such as any of example data centers100,300, and400ofFIGS.1,3, and4. Connectivity scheme500may be implemented using an optical fabric that features a dual-mode optical switching infrastructure514. Dual-mode optical switching infrastructure514may generally comprise a switching infrastructure that is capable of receiving communications according to multiple link-layer protocols via a same unified set of optical signaling media, and properly switching such communications. In various embodiments, dual-mode optical switching infrastructure514may be implemented using one or more dual-mode optical switches515. In various embodiments, dual-mode optical switches515may generally comprise high-radix switches. In some embodiments, dual-mode optical switches515may comprise multi-ply switches, such as four-ply switches. In various embodiments, dual-mode optical switches515may feature integrated silicon photonics that enable them to switch communications with significantly reduced latency in comparison to conventional switching devices. In some embodiments, dual-mode optical switches515may constitute leaf switches530in a leaf-spine architecture additionally including one or more dual-mode optical spine switches520.

In various embodiments, dual-mode optical switches may be capable of receiving both Ethernet protocol communications carrying Internet Protocol (IP packets) and communications according to a second, high-performance computing (HPC) link-layer protocol (e.g., Intel's Omni-Path Architecture's, Infiniband) via optical signaling media of an optical fabric. As reflected inFIG.5, with respect to any particular pair of sleds504A and504B possessing optical signaling connectivity to the optical fabric, connectivity scheme500may thus provide support for link-layer connectivity via both Ethernet links and HPC links. Thus, both Ethernet and HPC communications can be supported by a single high-bandwidth, low-latency switch fabric. The embodiments are not limited to this example.

FIG.6illustrates a general overview of a rack architecture600that may be representative of an architecture of any particular one of the racks depicted inFIGS.1to4according to some embodiments. As reflected inFIG.6, rack architecture600may generally feature a plurality of sled spaces into which sleds may be inserted, each of which may be robotically-accessible via a rack access region601. In the particular non-limiting example depicted inFIG.6, rack architecture600features five sled spaces603-1to603-5. Sled spaces603-1to603-5feature respective multi-purpose connector modules (MPCMs)616-1to616-5.

FIG.7illustrates an example of a sled704that may be representative of a sled of such a type. As shown inFIG.7, sled704may comprise a set of physical resources705, as well as an MPCM716designed to couple with a counterpart MPCM when sled704is inserted into a sled space such as any of sled spaces603-1to603-5ofFIG.6. Sled704may also feature an expansion connector717. Expansion connector717may generally comprise a socket, slot, or other type of connection element that is capable of accepting one or more types of expansion modules, such as an expansion sled718. By coupling with a counterpart connector on expansion sled718, expansion connector717may provide physical resources705with access to supplemental computing resources705B residing on expansion sled718. The embodiments are not limited in this context.

FIG.8illustrates an example of a rack architecture800that may be representative of a rack architecture that may be implemented in order to provide support for sleds featuring expans10n capabilities, such as sled704ofFIG.7. In the particular non-limiting example depicted inFIG.8, rack architecture800includes seven sled spaces803-1to803-7, which feature respective MPCMs816-1to816-7. Sled spaces803-1to803-7include respective primary regions803-1A to803-7A and respective expansion regions803-1B to803-7B. With respect to each such sled space, when the corresponding MPCM is coupled with a counterpart MPCM of an inserted sled, the primary region may generally constitute a region of the sled space that physically accommodates the inserted sled. The expansion region may generally constitute a region of the sled space that can physically accommodate an expansion module, such as expans10n sled718ofFIG.7, in the event that the inserted sled is configured with such a module.

FIG.9illustrates an example of a rack902that may be representative of a rack implemented according to rack architecture800ofFIG.8according to some embodiments. In the particular non-limiting example depicted inFIG.9, rack902features seven sled spaces903-1to903-7, which include respective primary regions903-1A to903-7A and respective expansion regions903-1B to903-7B. In various embodiments, temperature control in rack902may be implemented using an air cooling system. For example, as reflected inFIG.9, rack902may feature a plurality of fans919that are generally arranged to provide air cooling within the various sled spaces903-1to903-7. In some embodiments, the height of the sled space is greater than the conventional “1 U” server height. In such embodiments, fans919may generally comprise relatively slow, large diameter cooling fans as compared to fans used in conventional rack configurations. Running larger diameter cooling fans at lower speeds may increase fan lifetime relative to smaller diameter cooling fans running at higher speeds while still providing the same amount of cooling. The sleds are physically shallower than conventional rack dimensions. Further, components are arranged on each sled to reduce thermal shadowing (i.e., not arranged serially in the direction of air flow). As a result, the wider, shallower sleds allow for an increase in device performance because the devices can be operated at a higher thermal envelope (e.g., 250 W) due to improved cooling (i.e., no thermal shadowing, more space between devices, more room for larger heat sinks, etc.).

MPCMs916-1to916-7may be configured to provide inserted sleds with access to power sourced by respective power modules920-1to920-7, each of which may draw power from an external power source921. In various embodiments, external power source921may deliver alternating current (AC) power to rack902, and power modules920-1to920-7may be configured to convert such AC power to direct current (DC) power to be sourced to inserted sleds. In some embodiments, for example, power modules920-1to920-7may be configured to convert 277-volt AC power into 12-volt DC power for provision to inserted sleds via respective MPCMs916-1to916-7. The embodiments are not limited to this example.

MPCMs916-1to916-7may also be arranged to provide inserted sleds with optical signaling connectivity to a dual-mode optical switching infrastructure914, which may be the same as—or similar to—dual-mode optical switching infrastructure514ofFIG.5. In various embodiments, optical connectors contained in MPCMs916-1to916-7may be designed to couple with counterpart optical connectors contained in MPCMs of inserted sleds to provide such sleds with optical signaling connectivity to dual-mode optical switching infrastructure914via respective lengths of optical cabling922-1to922-7. In some embodiments, each such length of optical cabling may extend from its corresponding MPCM to an optical interconnect loom923that is external to the sled spaces of rack902. In various embodiments, optical interconnect loom923may be arranged to pass through a support post or other type of load-bearing element of rack902. The embodiments are not limited in this context. Because inserted sleds connect to an optical switching infrastructure via MPCMs, the resources typically spent in manually configuring the rack cabling to accommodate a newly inserted sled can be saved.

FIG.10illustrates an example of a sled1004that may be representative of a sled designed for use in conjunction with rack902ofFIG.9according to some embodiments. Sled1004may feature an MPCM1016that comprises an optical connector1016A and a power connector1016B, and that is designed to couple with a counterpart MPCM of a sled space in conjunction with insertion of MPCM1016into that sled space. Coupling MPCM1016with such a counterpart MPCM may cause power connector1016to couple with a power connector comprised in the counterpart MPCM. This may generally enable physical resources1005of sled1004to source power from an external source, via power connector1016and power transmission media1024that conductively couples power connector1016to physical resources1005.

Sled1004may also include dual-mode optical network interface circuitry1026. Dual-mode optical network interface circuitry1026may generally comprise circuitry that is capable of communicating over optical signaling media according to each of multiple link-layer protocols supported by dual-mode optical switching infrastructure914ofFIG.9. In some embodiments, dual-mode optical network interface circuitry1026may be capable both of Ethernet protocol communications and of communications according to a second, high-performance protocol. In various embodiments, dual-mode optical network interface circuitry1026may include one or more optical transceiver modules1027, each of which may be capable of transmitting and receiving optical signals over each of one or more optical channels. The embodiments are not limited in this context.

Coupling MPCM1016with a counterpart MPCM of a sled space in a given rack may cause optical connector1016A to couple with an optical connector comprised in the counterpart MPCM. This may generally establish optical connectivity between optical cabling of the sled and dual-mode optical network interface circuitry1026, via each of a set of optical channels1025. Dual-mode optical network interface circuitry1026may communicate with the physical resources1005of sled1004via electrical signaling media1028. In addition to the dimensions of the sleds and arrangement of components on the sleds to provide improved cooling and enable operation at a relatively higher thermal envelope (e.g., 250 W), as described above with reference toFIG.9, in some embodiments, a sled may include one or more additional features to facilitate air cooling, such as a heatpipe and/or heat sinks arranged to dissipate heat generated by physical resources1005. It is worthy of note that although the example sled1004depicted inFIG.10does not feature an expansion connector, any given sled that features the design elements of sled1004may also feature an expansion connector according to some embodiments. The embodiments are not limited in this context.

FIG.11illustrates an example of a data center1100that may generally be representative of one in/for which one or more techniques described herein may be implemented according to various embodiments. As reflected inFIG.11, a physical infrastructure management framework1150A may be implemented to facilitate management of a physical infrastructure1100A of data center1100. In various embodiments, one function of physical infrastructure management framework1150A may be to manage automated maintenance functions within data center1100, such as the use of robotic maintenance equipment to service computing equipment within physical infrastructure1100A. In some embodiments, physical infrastructure1100A may feature an advanced telemetry system that performs telemetry reporting that is sufficiently robust to support remote automated management of physical infrastructure1100A. In various embodiments, telemetry information provided by such an advanced telemetry system may support features such as failure prediction/prevention capabilities and capacity planning capabilities. In some embodiments, physical infrastructure management framework1150A may also be configured to manage authentication of physical infrastructure components using hardware attestation techniques. For example, robots may verify the authenticity of components before installation by analyzing information collected from a radio frequency identification (RFID) tag associated with each component to be installed. The embodiments are not limited in this context.

As shown inFIG.11, the physical infrastructure1100A of data center1100may comprise an optical fabric1112, which may include a dual-mode optical switching infrastructure1114. Optical fabric1112and dual-mode optical switching infrastructure1114may be the same as—or similar to—optical fabric412ofFIG.4and dual-mode optical switching infrastructure514ofFIG.5, respectively, and may provide high-bandwidth, low-latency, multi-protocol connectivity among sleds of data center1100. As discussed above, with reference toFIG.1, in various embodiments, the availability of such connectivity may make it feasible to disaggregate and dynamically pool resources such as accelerators, memory, and storage. In some embodiments, for example, one or more pooled accelerator sleds1130may be included among the physical infrastructure1100A of data center1100, each of which may comprise a pool of accelerator resources—such as co-processors and/or FPGAs, for example—that is globally accessible to other sleds via optical fabric1112and dual-mode optical switching infrastructure1114.

In another example, in various embodiments, one or more pooled storage sleds1132may be included among the physical infrastructure1100A of data center1100, each of which may comprise a pool of storage resources that is available globally accessible to other sleds via optical fabric1112and dual-mode optical switching infrastructure1114. In some embodiments, such pooled storage sleds1132may comprise pools of solid-state storage devices such as solid-state drives (SSDs). In various embodiments, one or more high-performance processing sleds1134may be included among the physical infrastructure1100A of data center1100. In some embodiments, high-performance processing sleds1134may comprise pools of high-performance processors, as well as cooling features that enhance air cooling to yield a higher thermal envelope of up to 250 W or more. In various embodiments, any given high-performance processing sled1134may feature an expansion connector1117that can accept a far memory expansion sled, such that the far memory that is locally available to that high-performance processing sled1134is disaggregated from the processors and near memory comprised on that sled. In some embodiments, such a high-performance processing sled1134may be configured with far memory using an expansion sled that comprises low-latency SSD storage. The optical infrastructure allows for compute resources on one sled to utilize remote accelerator/FPGA, memory, and/or SSD resources that are disaggregated on a sled located on the same rack or any other rack in the data center. The remote resources can be located one switch jump away or two-switch jumps away in the spine-leaf network architecture described above with reference toFIG.5. The embodiments are not limited in this context.

In various embodiments, one or more layers of abstraction may be applied to the physical resources of physical infrastructure1100A in order to define a virtual infrastructure, such as a software-defined infrastructure1100B. In some embodiments, virtual computing resources1136of software-defined infrastructure1100B may be allocated to support the provision of cloud services1140. In various embodiments, particular sets of virtual computing resources1136may be grouped for provision to cloud services1140in the form of SDI services1138. Examples of cloud services1140may include—without limitation—software as a service (SaaS) services1142, platform as a service (PaaS) services1144, and infrastructure as a service (IaaS) services1146.

In some embodiments, management of software-defined infrastructure1100B may be conducted using a virtual infrastructure management framework 1150B. In various embodiments, virtual infrastructure management framework 1150B may be designed to implement workload fingerprinting techniques and/or machine-learning techniques m conjunction with managing allocation of virtual computing resources1136and/or SDI services1138to cloud services1140. In some embodiments, virtual infrastructure management framework 1150B may use/consult telemetry data in conjunction with performing such resource allocation. In various embodiments, an application/service management framework1150C may be implemented in order to provide QoS management capabilities for cloud services1140. The embodiments are not limited in this context.

Referring now toFIG.12, a system1210for dynamically allocating shared resources among logic portions of accelerators used to execute workloads may be implemented in accordance with the data centers100,300,400,1100described above with reference toFIGS.1,3,4, and11. In the illustrative embodiment, the system1210includes an orchestrator server1220in communication with a set of managed nodes1230. Each managed node1230may be embodied as an assembly of resources (e.g., physical resources206), such as compute resources (e.g., physical compute resources205-4), storage resources (e.g., physical storage resources205-1), accelerator resources (e.g., physical accelerator resources205-2), or other resources (e.g., physical memory resources205-3) from the same or different sleds (e.g., the sleds204-1,204-2,204-3,204-4, etc.) or racks (e.g., one or more of racks302-1through302-32). In the illustrative embodiment, a managed node1232includes accelerators1250,1260of an accelerator sled1240and CPUs1272,1282of compute sleds1270,1280. As described in more detail herein, the accelerator1250includes multiple logic portions1252,1254which may each be embodied as any subset of the logic (e.g., circuitry) of the accelerator1250capable of separately executing a workload (e.g., a portion of an application assigned to a corresponding compute sled, such as the compute sled1270) and utilizing shared resources1256,1258, such as memory and data storage, of the accelerator1250during the execution of the workload. As such, using the separate logic portions1252,1254, the accelerator1250may accelerate the execution of separate workloads. Similarly, the accelerator1260includes logic portions1262,1264and shared resources1266,1268similar to the corresponding components of the accelerator1250described above.

Each managed node1230may be established, defined, or “spun up” by the orchestrator server1220at the time a workload is to be assigned to the managed node1230or at any other time, and may exist regardless of whether any workloads are presently assigned to the managed node1230. In the illustrative embodiment, the set of managed nodes1230includes managed nodes1232,1234, and1236. While three managed nodes1230are shown in the set, it should be understood that in other embodiments, the set may include a different number of managed nodes1230(e.g., tens of thousands). The system1210may be located in a data center and provide storage and compute services (e.g., cloud services) to a client device1214that is in communication with the system1210through a network1212. The orchestrator server1220may support a cloud operating environment, such as OpenStack, and the managed nodes1230may execute one or more applications or processes (i.e., workloads), such as in virtual machines or containers, on behalf of a user of the client device1214.

As discussed in more detail herein, in operation, in the illustrative embodiment an accelerator (e.g., the accelerator1250) is configured to execute assigned workloads with the logic portions1252,1254and allocate specified amounts of the shared resources1256,1258to the logic portions1252,1254during the execution of the workloads. Furthermore, during execution of the workloads, the accelerator1250is to monitor the actual utilization of the resources allocated to the logic portions1252,1254and report back resource utilization data to another compute device, such as to the orchestrator server1220, which may, in turn, send the resource utilization data to another compute device, such as the CPU1272. The CPU1272may be executing a workload (e.g., an application) associated with a workload (e.g., a set of operations in the application) executed by one of the logic portions1252,1254. In some embodiments, the accelerator1250only reports the resource utilization if the resource utilization does not satisfy a threshold (e.g., the utilization falls below the allocated amount of the shared resource by a predefined amount such as 5%). In response, the accelerator1250may receive a request (e.g., directly from the orchestrator server1220or from the CPU1272via the orchestrator server1220) to adjust the threshold amount of the underutilized resource to be allocated to the corresponding logic portion (e.g., the logic portion1252), to free up the unused amount of the resource for use by other logic portions (e.g., the logic portion1254) of the accelerator1250. In response, the accelerator1250, in the illustrative embodiment, adjusts the threshold amount in accordance with the request, while the workloads are still being executed by the logic portions1252,1254of the accelerator1250. As such, the accelerator1250more efficiently uses the available shared resources1256,1258, thereby saving costs that would otherwise be spent to add additional resources to the data center1100to provide a particular agreed-upon quality of service (e.g., throughput, latency, etc.) for a customer (e.g., in a service level agreement (SLA)).

Referring now toFIG.13, the accelerator1250may be embodied as any type of compute device capable of accelerating the execution of a workload and performing the other functions described herein, including continually allocating and reallocating shared resources to logic portions of the accelerator1250pursuant to requests from another compute device (e.g., the orchestrator server1220, the CPU1272, etc.) as the workloads are executed, monitoring the actual utilization of the shared resources by each logic portion, and reporting the resource utilization data to one or more other compute devices (e.g., the orchestrator server1220, the CPU1272, etc.). For example, the accelerator1250may be embodied as a physical accelerator resource205-2on a sled204-2, as described above with reference toFIG.2. As shown inFIG.13, the accelerator1250includes acceleration circuitry1302, a main memory1304, an input/output (I/O) subsystem1306, a dynamic resource allocation logic unit1308, a resource monitor logic unit1310, one or more data storage devices1312, and communication circuitry1314. In some embodiments, one or more of the illustrative components may be incorporated in, or otherwise form a portion of, another component. For example, the dynamic resource allocation logic unit1308and/or the resource monitor logic unit1310may be incorporated in the acceleration circuitry1302.

The acceleration circuitry1302may be embodied as any circuitry capable of executing one or more workloads faster than a general purpose processor. The acceleration circuitry1302may be embodied as a field programmable gate array (FPGA), a cryptography accelerator, a graphics accelerator, a compression accelerator, or other specialized single or multi-core processor(s), an application specific integrated circuit (ASIC), reconfigurable hardware or hardware circuitry, or other specialized hardware to facilitate the accelerated execution of a workload. In the illustrative embodiment, the acceleration circuitry1302includes multiple logic portions1252,1254which may be embodied as any devices or circuitry capable of concurrently executing separate workloads while accessing other resources of the accelerator1250, such as the main memory1304, the data storage devices1312, and/or bandwidth of the communication circuitry1314.

The main memory1304may be embodied as any type of volatile (e.g., dynamic random access memory (DRAM), etc.) or non-volatile memory or data storage capable of performing the functions described herein. In operation, the main memory1304may store various software and data used during operation such as workload data, resource utilization data, resource utilization threshold data, libraries, and drivers.

The I/O subsystem1306may be embodied as circuitry and/or components to facilitate input/output operations with the acceleration circuitry1302, the main memory1304, and other components of the accelerator1250. For example, the I/O subsystem1306may be embodied as, or otherwise include, memory controller hubs, input/output control hubs, integrated sensor hubs, firmware devices, communication links (e.g., point-to-point links, bus links, wires, cables, light guides, printed circuit board traces, etc.), and/or other components and subsystems to facilitate the input/output operations. In some embodiments, the I/O subsystem1306may form a portion of a system-on-a-chip (SoC) and be incorporated, along with one or more of the acceleration circuitry1302, the main memory1304, and other components of the accelerator1250, on a single integrated circuit chip.

The dynamic resource allocation logic unit1308may be embodied as any device or circuitry capable of allocating specified amounts of resources (e.g., main memory1304, capacity of the data storage devices1312, bandwidth of the communication circuitry1314, etc.) to corresponding particular logic portions1252,1254. For example, the dynamic resource allocation logic unit1308may be embodied as a co-processor, embedded circuit, ASIC, FPGA, and/or other circuitry. The dynamic resource allocation logic unit1308may compare a request from one of the logic portions1252for an amount of a resource, compare the requested amount, and any amount already used by the requesting logic portion1252,1254, to a threshold amount to be allocated, and grant or deny the request as a function of whether the total amount (e.g., the amount already used and the requested amount) exceeds the threshold amount. Additionally, the dynamic resource allocation logic unit1308is to dynamically adjust the thresholds in response to requests (e.g., from another compute device) as the workloads are being executed by the logic portions1252,1254.

The resource monitor logic unit1310may be embodied as any device or circuitry capable of monitoring the resource utilization by each logic portion1252,1254as the workloads are executed. For example, the dynamic resource allocation logic unit1308may be embodied as a co-processor, embedded circuit, ASIC, FPGA, and/or other circuitry. In the illustrative embodiment, the resource monitor logic unit1310may compare the resource utilization by a particular logic portion1252,1254to the resource utilization threshold set by the dynamic resource allocation logic unit1308and determine whether the present resource utilization satisfies (e.g., is within a predefined range, such as 5%, of) the resource utilization threshold. If not, the resource monitor logic unit1310, in the illustrative embodiment, may generate a violation message to report the present resource utilization to another compute device (e.g., the orchestrator server1220, the CPU1272, etc.). In other embodiments, the resource monitor logic unit1310may continually (e.g., on a periodic basis) report all resource utilizations by the logic portions1252,1254regardless of whether the utilizations satisfy corresponding resource utilization thresholds.

The one or more illustrative data storage devices1312, may be embodied as any type of devices configured for short-term or long-term storage of data such as, for example, memory devices and circuits, memory cards, hard disk drives, solid-state drives, or other data storage devices. Each data storage device1312may include a system partition that stores data and firmware code for the data storage device1312. Each data storage device1312may also include an operating system partition that stores data files and executables for an operating system.

The communication circuitry1314may be embodied as any communication circuit, device, or collection thereof, capable of enabling communications over the network1212between the accelerator1250and another compute device (e.g., the orchestrator server1220and/or other compute devices). The communication circuitry1314may be configured to use any one or more communication technology (e.g., wired or wireless communications) and associated protocols (e.g., Ethernet, Bluetooth®, Wi-Fi®, WiMAX, etc.) to effect such communication.

The illustrative communication circuitry1314includes a network interface controller (NIC)1316, which may also be referred to as a host fabric interface (HFI). The NIC1316may be embodied as one or more add-in-boards, daughtercards, network interface cards, controller chips, chipsets, or other devices that may be used by the accelerator1250to connect with another compute device (e.g., the orchestrator server1220). In some embodiments, the NIC1316may be embodied as part of a system-on-a-chip (SoC) that includes one or more processors, or included on a multichip package that also contains one or more processors. In some embodiments, the NIC1316may include a local processor (not shown) and/or a local memory (not shown) that are both local to the NIC1316. In such embodiments, the local processor of the NIC1316may be capable of performing one or more of the functions of the acceleration circuitry1302, the dynamic resource allocation logic unit1308, and/or the resource monitor logic unit1310described herein. Additionally or alternatively, in such embodiments, the local memory of the NIC1316may be integrated into one or more components of the accelerator1250at the board level, socket level, chip level, and/or other levels. The accelerator1260may have components similar to those described inFIG.13. The description of those components of the accelerator1250is equally applicable to the description of components of the accelerator1260and is not repeated herein for clarity of the description. While shown as being within one accelerator130, in some embodiments, an accelerator sled (e.g., the accelerator sled1240) may have one NIC1316that is shared by all of the accelerators1250,1260on the accelerator sled1240and virtualized to appear as multiple NICs1316(e.g., one for each accelerator1250,1260).

Referring now toFIG.14, the orchestrator server1220may be embodied as any type of compute device capable of performing the functions described herein, including issuing a request to have cloud services performed, receiving results of the cloud services, assigning workloads to managed nodes1230, managing communications between components (e.g., accelerators1250,1260, and CPUs1272,1282) of a managed node1230, such as resource utilization violation messages and requests to change resource utilization thresholds for shared resources (e.g., the main memory1304, the data storage devices1312, the communication circuitry1314, etc.) within an accelerator (e.g., the accelerator1250). For example, the orchestrator server1220may be embodied as a computer, a distributed computing system, one or more sleds (e.g., the sleds204-1,204-2,204-3,204-4, etc.), a server (e.g., stand-alone, rack-mounted, blade, etc.), a multiprocessor system, a network appliance (e.g., physical or virtual), a desktop computer, a workstation, a laptop computer, a notebook computer, a processor-based system, or a network appliance. As shown inFIG.14, the illustrative orchestrator server1220includes a central processing unit (CPU)1402, a main memory1404, an input/output (I/O) subsystem1406, communication circuitry1408, and one or more data storage devices1412. Of course, in other embodiments, the orchestrator server1220may include other or additional components, such as those commonly found in a computer (e.g., display, peripheral devices, etc.). Additionally, in some embodiments, one or more of the illustrative components may be incorporated in, or otherwise form a portion of, another component. For example, in some embodiments, the main memory1404, or portions thereof, may be incorporated in the CPU1402.

The CPU1402may be embodied as any type of processor capable of performing the functions described herein. The CPU1402may be embodied as a single or multi-core processor(s), a microcontroller, or other processor or processing/controlling circuit. In some embodiments, the CPU1402may be embodied as, include, or be coupled to a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), reconfigurable hardware or hardware circuitry, or other specialized hardware to facilitate performance of the functions described herein. Similarly, the main memory1404may be embodied as any type of volatile (e.g., dynamic random access memory (DRAM), etc.) or non-volatile memory or data storage capable of performing the functions described herein. In some embodiments, all or a portion of the main memory1404may be integrated into the CPU1402. In operation, the main memory1404may store various software and data used during operation such as workload data, resource utilization data, resource utilization threshold data, quality of service data, operating systems, applications, programs, libraries, and drivers.

The I/O subsystem1406may be embodied as circuitry and/or components to facilitate input/output operations with the CPU1402, the main memory1404, and other components of the orchestrator server1220. For example, the I/O subsystem1406may be embodied as, or otherwise include, memory controller hubs, input/output control hubs, integrated sensor hubs, firmware devices, communication links (e.g., point-to-point links, bus links, wires, cables, light guides, printed circuit board traces, etc.), and/or other components and subsystems to facilitate the input/output operations. In some embodiments, the I/O subsystem1406may form a portion of a system-on-a-chip (SoC) and be incorporated, along with one or more of the CPU1402, the main memory1404, and other components of the orchestrator server1220, on a single integrated circuit chip.

The communication circuitry1408may be embodied as any communication circuit, device, or collection thereof, capable of enabling communications over the network1212between the orchestrator server1220and another compute device (e.g., the client device1214, and/or the managed nodes1230). The communication circuitry1408may be configured to use any one or more communication technology (e.g., wired or wireless communications) and associated protocols (e.g., Ethernet, Bluetooth®, Wi-Fi®, WiMAX, etc.) to effect such communication.

The illustrative communication circuitry1408includes a network interface controller (NIC)1410, which may also be referred to as a host fabric interface (HFI). The NIC1410may be embodied as one or more add-in-boards, daughtercards, network interface cards, controller chips, chipsets, or other devices that may be used by the orchestrator server1220to connect with another compute device (e.g., the client device1214and/or the managed nodes1230). In some embodiments, the NIC1410may be embodied as part of a system-on-a-chip (SoC) that includes one or more processors, or included on a multichip package that also contains one or more processors. In some embodiments, the NIC1410may include a local processor (not shown) and/or a local memory (not shown) that are both local to the NIC1410. In such embodiments, the local processor of the NIC1410may be capable of performing one or more of the functions of the CPU1402described herein. Additionally or alternatively, in such embodiments, the local memory of the NIC1410may be integrated into one or more components of the orchestrator server1220at the board level, socket level, chip level, and/or other levels.

The one or more illustrative data storage devices1412, may be embodied as any type of devices configured for short-term or long-term storage of data such as, for example, memory devices and circuits, memory cards, hard disk drives, solid-state drives, or other data storage devices. Each data storage device1412may include a system partition that stores data and firmware code for the data storage device1412. Each data storage device1412may also include an operating system partition that stores data files and executables for an operating system.

Additionally or alternatively, the orchestrator server1220may include one or more peripheral devices1414. Such peripheral devices1414may include any type of peripheral device commonly found in a compute device such as a display, speakers, a mouse, a keyboard, and/or other input/output devices, interface devices, and/or other peripheral devices.

The client device1214and the managed nodes1230may have components similar to those described inFIG.14. The description of those components of the orchestrator server1220is equally applicable to the description of components of the client device1214and the managed nodes1230and is not repeated herein for clarity of the description. Further, it should be appreciated that any of the client device1214and the managed nodes1230may include other components, sub-components, and devices commonly found in a computing device, which are not discussed above in reference to the orchestrator server1220and not discussed herein for clarity of the description. As discussed above, each managed node1230may include resources distributed across multiple sleds and in such embodiments, the CPU1402, memory1404, and/or communication circuitry1408may include portions thereof located on the same sled or different sled.

As described above, the client device1214, the orchestrator server1220, and the managed nodes1230are illustratively in communication via the network1212, which may be embodied as any type of wired or wireless communication network, including global networks (e.g., the Internet), local area networks (LANs) or wide area networks (WANs), cellular networks (e.g., Global System for Mobile Communications (GSM), 3G, Long Term Evolution (LTE), Worldwide Interoperability for Microwave Access (WiMAX), etc.), digital subscriber line (DSL) networks, cable networks (e.g., coaxial networks, fiber networks, etc.), or any combination thereof.

Referring now toFIG.15, in the illustrative embodiment, each accelerator (e.g., the accelerator1250) may establish an environment1500during operation. The illustrative environment1500includes a network communicator1520, a workload executor1530, a resource allocator1540, and a resource utilization monitor1550. Each of the components of the environment1500may be embodied as hardware, firmware, software, or a combination thereof. As such, in some embodiments, one or more of the components of the environment1500may be embodied as circuitry or a collection of electrical devices (e.g., network communicator circuitry1520, workload executor circuitry1530, resource allocator circuitry1540, resource utilization monitor circuitry1550, etc.). It should be appreciated that, in such embodiments, one or more of the network communicator circuitry1520, workload executor circuitry1530, resource allocator circuitry1540, or resource utilization monitor circuitry1550may form a portion of one or more of the acceleration circuitry1302, the dynamic resource allocation logic unit1308, the resource monitor logic unit1310, the main memory1304, the I/O subsystem1306, and/or other components of the accelerator1250.

In the illustrative embodiment, the environment1500includes workload data1502which may be embodied as any data indicative of workloads to be executed by the logic portions1252,1254of the accelerator1250, such as bit streams usable to configure hardware of the logic portions1252,1254to execute operations in a workload, computer-executable instructions, identifiers of the workloads, and/or a map of the assignments of workloads to the logic portions1252,1254. The illustrative environment1500additionally includes resource utilization data1504which may be embodied as any data indicative of the present utilization of each of the resources shared among the logic portions1252,1254of the accelerator1250, such as a number of gigabytes of the main memory1304used by each logic portion1252,1254, a number of gigabytes of the data storage devices1312used by each logic portion1252,1254, a number of gigabytes per second of network bandwidth used by each logic portion1252,1254, etc. or relative values, such as percentages of the resources used by each logic portion1252,1254. Additionally, the illustrative environment1500includes resource utilization threshold data1506which may be embodied as any data indicative of limits on the amount of one or more types of resources (e.g., main memory1304, data storage1312, communication circuitry1314, etc.) that are to be used by each logic portion1252,1254. As described herein, the accelerator1250may continually adjust the resource utilization threshold data1506as the workloads are executed (e.g., in response to requests received from another compute device such as the orchestrator server1220). In some embodiments, the resource utilization threshold data1506may include identifiers of classes of service and corresponding resource types and amounts of each resource type to be allocated in association with the identified class of service.

In the illustrative environment1500, the network communicator1520, which may be embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof as discussed above, is configured to facilitate inbound and outbound network communications (e.g., network traffic, network packets, network flows, etc.) to and from the accelerator1250, respectively. To do so, the network communicator1520is configured to receive and process data packets from one system or computing device (e.g., the orchestrator server1220) and to prepare and send data packets to a system or computing device (e.g., the orchestrator server1220). Accordingly, in some embodiments, at least a portion of the functionality of the network communicator1520may be performed by the communication circuitry1408, and, in the illustrative embodiment, by the NIC1410. The workload executor1530, which may be embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof as discussed above, is configured to execute workloads assigned to the accelerator1250using the logic portions1252,1254.

The resource allocator1540, which may be embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof as discussed above, is configured to allocate specified amounts of resources (e.g., main memory1304, capacity of the data storage devices1312, bandwidth of the communication circuitry1314, etc.) to the corresponding particular logic portions1252,1254. The resource allocator1540may do so by comparing a request from one of the logic portions1252for an amount of a resource, comparing the requested amount, and any amount already used by the requesting logic portion1252to a threshold amount to be allocated (e.g., an amount identified in the resource utilization threshold data1506), and granting or denying the request as a function of whether the total amount (e.g., the amount already used and the requested amount) exceeds the threshold amount. Additionally, the resource allocator1540is to dynamically adjust the thresholds in the resource utilization threshold data1506in response to requests (e.g., from another compute device such as the orchestrator server1220) as the workloads are being executed by the logic portions1252,1254. In the illustrative embodiment, the resource allocator1540includes a class of service translator1542, which may be configured to translate a given class of service to an amount of a particular resource to be allocated, such as by referencing a map of classes of service and corresponding types and amounts of resources defined in the resource utilization threshold data1506as described above. It should be appreciated that the class of service translator1542may be embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof.

The resource utilization monitor1550, which may be embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof as discussed above, is configured to monitor the utilization of each logic portion1252,1254as the workloads are executed. In the illustrative embodiment, the resource utilization monitor1550may compare the utilization of a particular logic portion1252,1254to a corresponding resource utilization threshold in the resource utilization threshold data1506and determine whether the present resource utilization satisfies the threshold. For example, the resource utilization monitor1550may determine whether the present utilization of a resource by the logic portion1252is within a predefined range, such as 5%, of the corresponding resource utilization threshold. In the illustrative embodiment, the resource utilization monitor1550includes a resource utilization reporter1552, which may be configured to report the resource utilization data1504to another compute device (e.g., to the orchestrator server1220). In some embodiments, the resource utilization reporter1552may be configured to report only resource utilizations that do not satisfy their corresponding resource utilization thresholds. In other embodiments, the resource utilization reporter1552may be configured to report all resource utilization data1504, such as on a periodic, repeating basis or in response to a query from another compute device (e.g., from the orchestrator server1220). It should be appreciated that the resource utilization reporter1552may be embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof.

Referring now toFIG.16, the orchestrator server1220may establish an environment1600during operation. The illustrative environment1600includes a network communicator1620and a resource manager1630. Each of the components of the environment1600may be embodied as hardware, firmware, software, or a combination thereof. As such, in some embodiments, one or more of the components of the environment1600may be embodied as circuitry or a collection of electrical devices (e.g., network communicator circuitry1620, resource manager circuitry1630, etc.). It should be appreciated that, in such embodiments, one or more of the network communicator circuitry1620or resource manager circuitry1630may form a portion of one or more of the CPU1402, the main memory1404, the I/O subsystem1406, and/or other components of the orchestrator server1220. In the illustrative embodiment, the environment1600includes workload data1602which may be embodied as any data indicative of workloads to be executed by the managed nodes1230and the assignments of the workloads to the components of the managed nodes1230, such as identifications of accelerators1250,1260, to which workloads are assigned, the logic portions1252,1254,1262,1264within the accelerators1250,1260that are executing the workloads, identifications of CPUs1272,1282executing workloads, and/or other data indicative of the present assignment of the workloads among the managed nodes1230. Additionally, the illustrative environment1600includes resource utilization data1604, which is similar to the resource utilization data1504except the resource utilization data1604includes data indicative of resource utilizations across all components of all of the managed nodes1230, rather than only the utilizations of resources within the accelerator1250. Further, in the illustrative embodiment, the environment1600includes resource utilization threshold data1606which is similar to the resource utilization threshold data1506, except the resource utilization threshold data1606includes data indicative of resource utilization thresholds across the managed nodes1230, rather than only the resource utilization thresholds specific to the accelerator1250. In addition, in the illustrative embodiment, the environment1600includes quality of service data1608which may be indicative of quality of service targets (e.g., a maximum latency, a minimum throughput, etc.) to be provided in association with different workloads (e.g., based on service level agreements with customers) and quality of service measurements (e.g., latency, throughput, etc.) presently provided by the system1210as the workloads are executed.

In the illustrative environment1600, the network communicator1620, which may be embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof as discussed above, is configured to facilitate inbound and outbound network communications (e.g., network traffic, network packets, network flows, etc.) to and from the orchestrator server1220, respectively. To do so, the network communicator1620is configured to receive and process data packets from one system or computing device (e.g., the client device1214) and to prepare and send data packets to another computing device or system (e.g., the managed nodes1230). Accordingly, in some embodiments, at least a portion of the functionality of the network communicator1620may be performed by the communication circuitry1408, and, in the illustrative embodiment, by the NIC1410.

The resource manager1630, which may be embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof, is configured to assign workloads to the managed nodes1230including the accelerators (e.g., accelerators1250,1260) and general purpose CPUs (e.g., CPUs1272,1282), receive the resource utilization data1604and send requests to components of the managed nodes1230(e.g., the accelerators1250,1260) to adjust the resource utilization thresholds on a continual basis in response to changes in resource utilizations indicated in the resource utilization data1604. To do so, in the illustrative embodiment, the resource manager1630includes a workload assignor1632, a resource utilization analyzer1636, and a resource utilization adjuster1638. The workload assignor1632, in the illustrative embodiment, is configured to assign workloads to the managed nodes1230for execution. Further, in the illustrative embodiment, the workload assignor1632includes an acceleration assignor1634which is configured to assign certain workloads or portions thereof to corresponding accelerators (e.g., the accelerators1250,1260). In doing so, the acceleration assignor1634may identify a type of the workload based on a profile of resource utilizations of the workload over time or based on a tag, an analysis of the computer-executable instructions within the workload, a header of the workload, metadata indicative of the types operations to be executed in the workload, or from a request from a CPU (e.g., the CPU1272) to offload a portion of a workload onto a particular accelerator1250,1260or type of accelerator (e.g., FPGA, graphics accelerator, cryptography accelerator, compression accelerator, etc.), and assign the workload to a corresponding accelerator1250,1260for execution.

The resource utilization analyzer, in the illustrative embodiment, is configured to receive the resource utilization data1604and determine whether the present utilization of resources among the managed nodes1230, such as the utilization by logic portions (e.g., the logic portions1252,1254) of shared resources within an accelerator (e.g., the accelerator1250) is in violation of resource utilization threshold indicated in the resource utilization threshold data1606. As described above, in some embodiments, the accelerators1250,1260may only report violations of the resource utilization thresholds rather than all resource utilizations. The resource utilization adjuster1638, in the illustrative embodiment, is configured to determine an adjustment to be made to the utilization of a resource, such as an adjustment to a resource utilization threshold for a particular resource (e.g., the memory1304) for a particular logic portion (e.g., the logic portion1252) of an accelerator (e.g., the accelerator1250). The resource utilization adjuster1638may determine a change in the class of service to be assigned, such as reducing from a second class of service associated with using 50% of the resource (e.g., the memory1304) to a first class of service associated with using 40% of the resource, thereby freeing up a portion of that resource for use by another logic portion (e.g., the logic portion1254) of the accelerator (e.g., the accelerator1250). In some embodiments, a CPU (e.g., the CPU1272) on a compute sled (e.g., the compute sled1270) of a managed node1230executing a workload, such as an application, may perform all or a subset of the functions described above, to manage the acceleration of a portion of the workload executed by the CPU1272and, as such, may establish an environment similar to the environment1600.

It should be appreciated that each of the workload assignor1632, the acceleration assignor1634, the resource utilization analyzer1636, and the resource utilization adjuster1638may be separately embodied as hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof. For example, the workload assignor1632may be embodied as a hardware component, while the acceleration assignor1634, the resource utilization analyzer1636, and the resource utilization adjuster1638are embodied as virtualized hardware components or as some other combination of hardware, firmware, software, virtualized hardware, emulated architecture, and/or a combination thereof.

Referring now toFIG.17, in use, an accelerator (e.g., the accelerator1250) may execute a method1700for performing dynamic resource allocation among its logic portions (e.g., the logic portions1252,1254). The method1700begins with block1702in which the accelerator1250determines whether to enable dynamic resource allocation. In the illustrative embodiment, the accelerator1250determines to enable dynamic resource allocation if the accelerator1250determines that it is capable of executing multiple workloads concurrently in different logic portions1252,1254, such as by detecting the presence of the logic portions1252,1254or by comparing an identifier of the accelerator1250to a set of accelerator identifiers known to be capable of executing workloads in separate logic portions. In other embodiments, the accelerator1250may make the determination of whether to enable dynamic resource allocation based on other factors. Regardless, in response to a determination to enable dynamic resource allocation, the method1700advances to block1704in which the accelerator1250receives one or more workloads to be executed by corresponding logic portions1252,1254of the accelerator1250. In doing so, the accelerator1250may receive a bit stream indicative of the workload to be accelerated, as indicated in block1706. The bit stream may include configuration data for configuring the logic gates of the accelerator1250if the accelerator1250is a FPGA. In receiving the one or more workloads, the accelerator1250may receive a designation of a logic portion1252,1254of the accelerator1250that is to execute the workload, as indicated in block1708. The designation may be an identifier, such as a number, that uniquely identifies the logic portion1252,1254within the accelerator1250.

Subsequently, in block1710, the accelerator1250identifies one or more resource utilization thresholds (e.g., the resource utilization threshold data1506) associated with the resources of the accelerator1250for the corresponding one or more logic portions1252,1254that are to execute the assigned one or more workloads from block1704. In doing so, the accelerator1250may receive the resource utilization threshold data1506from the orchestrator server1220, as indicated in block1712. As indicated in block1714, the accelerator1250may receive the resource utilization threshold data1506from a CPU (e.g., the CPU1272) executing a portion of the workload, such as a portion that is not to be accelerated, as indicated in block1714. In some embodiments, the orchestrator server1220may initially receive the resource utilization threshold data1506from the CPU1272and then forward the resource utilization threshold data1506to the accelerator1250. As indicated in block1716, the accelerator1250may receive a utilization threshold for high bandwidth memory (e.g., the main memory1304), such as number of gigabytes of the main memory1304that are to be used by the logic portion1252, or a percentage of the total amount of main memory1304that is to be used by the logic portion1252. Similarly, as indicated in block1718, the accelerator1250may receive a utilization threshold for data storage (e.g., the data storage devices1312), such as a number of gigabytes of the capacity of the data storage devices1312or a percentage of a total amount of the available capacity. Additionally or alternatively, as indicated in block1720, the accelerator1250may receive a utilization threshold for network bandwidth, such as a number of gigabytes per second or a percentage of the total amount of capacity of the communication circuitry1314of the accelerator1250. As indicated in block1722, the accelerator1250may receive a class of service identifier for one or more of the resources, which the accelerator1250may then translate to a corresponding numeric value (e.g., gigabytes, gigabytes per second, etc.) or percentage of total capacity, such as with the map of classes of service and corresponding values in the resource utilization threshold data1506, as described with reference toFIG.15. Additionally, as indicated in block1724, the accelerator1250may receive a request to register a utilization monitor for one or more of the resources to be shared among the logic portions1252,1254. The request may identify the logic portion1252,1254to which the monitor pertains, the type of resource whose utilization is to be monitored by the accelerator1250, and the corresponding utilization threshold for the resource. As such, if the utilization threshold is not satisfied (e.g., the actual resource utilization is not within a predefined range, such as 5% of the threshold), the accelerator1250may report the violation of the resource utilization threshold to the orchestrator server1220or the CPU1272. Subsequently, the method1700advances to block1726ofFIG.18, in which the accelerator1250executes the assigned one or more workloads with the corresponding one or more logic portions1252,1254of the accelerator1250.

Referring now toFIG.18, in block1728, the accelerator1250limits the resource utilization by the corresponding logic portions1252,1254to the resource utilization thresholds from block1710. In doing so, the accelerator1250, and in particular, the dynamic resource allocation logic unit1308, may receive a request from the logic portions1252,1254for allocation of resources, such as a request for a particular amount of memory capacity or network bandwidth. As indicated in block1732, the accelerator1250, and in particular, the dynamic resource allocation logic unit1308, may grant requests up to the corresponding resource utilization thresholds for the requesting logic portions1252,1254and deny requests that would result in resource utilizations that exceed the corresponding resource utilization thresholds. Additionally, in block1734, the accelerator1250monitors the utilization of the resources that are associated with the resource utilization thresholds identified in block1710ofFIG.17. In doing so, the resource monitor logic unit1310may add together the requested amounts of resources from the requests received by the dynamic resource allocation logic unit1308to determine the total amount of each resource used by each logic portion1252,1254, and/or may receive telemetry data from the resources (e.g., through the I/O subsystem1306) which may be embodied as any data indicative of the present utilization (e.g., portion of the capacity presently being used) of the resource and the logic portions1252,1254or workloads associated with those utilizations. In the illustrative embodiment, in block1736, the accelerator1250determines whether the resource utilization thresholds are satisfied. In doing so, as indicated in block1738, the accelerator1250determines whether less than the resource utilization threshold for each resource is being used by the corresponding logic portion. In the illustrative embodiment, the accelerator1250may determine that the threshold is satisfied as long as the present utilization is within a predefined range, such as 5%, of the corresponding threshold (e.g., a threshold of 50% of the memory capacity may be satisfied if the present utilization is between 45% and 50% of the memory capacity). In block1740, the accelerator1250determines the subsequent operations to perform in response to whether the resource utilization thresholds are presently satisfied. If the thresholds are satisfied, the method1700loops back to block1726in which the accelerator1250continues to execute the workloads with the corresponding logic portions1252,1254. Otherwise, if one or more of the resource utilization thresholds are not satisfied, the method1700advances to block1742.

In block1742, the accelerator1250reports one or more of the present resource utilizations to another compute device in the system1210. In doing so, as indicated in block1744, the accelerator1250reports the resource utilizations that do not satisfy the corresponding resource utilization thresholds. As indicated in block1746, the accelerator1250may report the resource utilizations to the orchestrator server1220. In other embodiments, the accelerator1250may report the resource utilizations to a CPU executing a portion of the workload (e.g., the CPU1272executing a portion of the workload that is not be accelerated). In some embodiments, the orchestrator server1220may receive the resource utilizations, as described in block1746, and forward the resource utilizations on to the CPU (e.g., the CPU1272) for analysis. Subsequently, the method1700loops back to block1710ofFIG.17, in which the accelerator1250again identifies resource utilization thresholds, such as by receiving adjusted resource utilization thresholds for the reported resource utilizations that did not satisfy the earlier resource utilization thresholds. As such, with lower resource utilization thresholds, an unused portion of those resources that were previously reserved for use by one of the logic portions (e.g., the logic portion1252) may become available for use by another logic portion (e.g., the logic portion1254) in the accelerator1250.

Referring now toFIG.19, in use, the orchestrator server1220may execute a method1900for managing resource utilizations within an accelerator (e.g., the accelerator1250). It should be understood that while the method1900is described with respect to one accelerator (e.g., the accelerator1250), the orchestrator server1220may perform the method1900for other accelerators (e.g., the accelerator1260) in the system1210as well. The method1900begins with block1902in which the orchestrator server1220determines whether to manage resource utilizations of an accelerator (e.g., the accelerator1250) in the system1210. In the illustrative embodiment, the orchestrator server1220may determine to manage accelerator resource utilizations if at least one accelerator having the ability to execute workloads on separate logic portions1252,1254is present in the system1210. In other embodiments, the orchestrator server1220may make the determination of whether to manager accelerator resource utilizations based on other factors. Regardless, in response to a determination to manage acceleration resource utilizations, the method1900advances to block1904, in which the orchestrator server1220assigns a workload to be accelerated by a logic portions (e.g., the logic portion1252) of an accelerator (e.g., the accelerator1250). As described above, with reference toFIG.16, the orchestrator server1220may make the determination to assign a workload in response to identifying the workload or a portion of the workload as being amenable to a particular type of acceleration for which an accelerator (e.g., the accelerator1250) is available. As indicated in block1906, in assigning the workload, the orchestrator server1220may send, to an accelerator (e.g., the accelerator1250) a bit stream indicative of the workload to be executed. The bit stream may include configuration data usable to configure logic gates of an FPGA to execute the workload. In block1908, in assigning the workload, the orchestrator server1220may send a designation of the logic portion (e.g., the logic portion1252) that is to execute the assigned workload. The designation may be an identifier, such as a number, that uniquely identifies the logic portion1252in the accelerator1250.

Subsequently, in block1910, the orchestrator server1220sends one or more resource utilization thresholds associated with one or more resources of the accelerator1250for the logic portion1252that is to execute the workload. In doing so, the orchestrator server1220may send the one or more resource utilization thresholds as a function of a service level agreement associated with the workload. As described above, with reference toFIG.16, the quality of service data1608may include quality of service targets (e.g., a maximum latency, a minimum throughput, etc.) that are to be met in the execution of workloads on behalf of various customers. As such, orchestrator server1220may send corresponding resource utilization thresholds to control the allocation of resources in the accelerator1250to enable the logic portion1252of the accelerator1250to satisfy the quality of service targets while executing the workload. In block1914, the orchestrator server1220may send a resource utilization threshold for high bandwidth memory (e.g., the main memory1304). Block1914corresponds with block1716ofFIG.17described above. As indicated in block1916, the orchestrator server1220may send a resource utilization threshold for data storage (e.g., the data storage devices1312). Block1916corresponds with block1718, described above with reference toFIG.17. Additionally or alternatively, in block1918, the orchestrator server1220may send a resource utilization threshold for network bandwidth (e.g., the communication circuitry1314). Block1918corresponds with block1720ofFIG.17, described above. In block1920, the orchestrator server1220may send a class of service identifier for one or more of the resources. As described above with reference to block1722, each class of service may be mapped to a corresponding actual amount of a resource to be allocated to the logic portion1252. In the illustrative embodiment, the orchestrator server1220may send a request to the accelerator1250to register a utilization monitor for one or more of the resources (e.g., a resource having a utilization threshold associated with it). Block1922corresponds with block1724ofFIG.17, described above.

Subsequently, the method1900advances to block1924ofFIG.20, in which the orchestrator server1220receives present resource utilization data (e.g., the resource utilization data1604) of the logic portion1252executing the workload. Subsequently, the orchestrator server1220determines whether the one or more resource utilizations indicated in the received resource utilization data satisfy the corresponding thresholds. To make the determination, the orchestrator server1220may perform an analysis similar to that described with reference to block1736ofFIG.18. For example, the orchestrator server1220may determine whether a given resource utilization reported by the accelerator1250is within a predefined range, such as 5%, of the corresponding resource utilization threshold. In other embodiments, the mere fact that the orchestrator server1220received resource utilization data1604for a particular resource and logic portion (e.g., the logic portion1252) is indicative of a violation of the corresponding threshold, such as when the accelerator1250sends the resource utilization data in association with a resource utilization monitor that was registered in block1922ofFIG.19. In some embodiments, the orchestrator server1220may receive notifications (e.g., resource utilization data1604) through an out-of-band management network on a particular channel and port that was configured at boot time. In block1928, the orchestrator server1220determines the subsequent operations as a function of whether the resource utilization threshold(s) are satisfied. In response to a determination that the resource utilization thresholds are satisfied, the method1900loops back to block1924in which the orchestrator server1220continues to await resource utilization data1604. Otherwise, if one or more of the thresholds are not satisfied, the method1900advances to block1930in which the orchestrator server1220determines one or more adjustments to the allocation of resources to the logic portion1252of the accelerator1250. In doing so, as indicated in block1932, the orchestrator server1220determines one or more adjustments to one or more of the resource utilization thresholds. In the illustrative embodiment, the orchestrator server1220reduces the violated resource utilization threshold(s) for one logic portion (e.g., the logic portion1252, which did not use all of a resource capacity allocated to it) to free up the resource(s) for use by another logic portion (e.g., the logic portion1254) of the accelerator1250. Subsequently, the method1900loops back to block1910ofFIG.19, in which the orchestrator server1220sends the updated resource utilization threshold(s) to the accelerator1250. While described as being performed by the orchestrator server1220, in some embodiments, a CPU (e.g., the CPU1272) executing a workload associated with the workload assigned to the accelerator1250may perform all or a portion of method1900(e.g., with the accelerator1250sending resource utilization data1504either directly to the CPU1272or through the orchestrator server1220to the CPU1272).

Referring now toFIG.21, in a series2100of messages, a compute device2210, which may be an administrator's compute device, sends a message2120to the orchestrator server1220to register a class of service pursuant to a service level agreement. The message2120, in the illustrative embodiment, includes an identifier of an accelerator (e.g., the accelerator1250), an identifier of a resource, such as a number or other identifier capable of uniquely identifying a shared resource within the accelerator1250(e.g., the main memory1304, the data storage devices1312, the communication circuitry1314, etc.), an identifier of the class of service (e.g., “1”, “2”, etc.), and an amount of the resource to be allocated in association with that class of service. The amount may be specified as a combination of an indication of the type of the measurement (e.g., a relative measurement or an absolute measurement) and the corresponding amount (e.g., 50%, or 2 gigabytes). In response, the orchestrator server1220determines whether the compute device2110has permission to register the class of service, such as by comparing an identifier of the compute device or login credentials entered by a user of the compute device2110to a reference set of permissions data. In response to a determination that the compute device2110does not have permission to register the class of service, the orchestrator server1220sends a not acknowledge (“NACK”) message back to the compute device2110. Otherwise, the orchestrator server1220sends the registration message2120including the parameters, to the identified accelerator (e.g., the accelerator1250). In response, the accelerator1250determines whether the parameters are acceptable (e.g., whether the specified amount of the resource is actually available to be allocated if the corresponding class of service is requested, whether the class of service is a duplicate of another class of service that has already been registered, etc.). In response to a determination that the parameters are not acceptable, the accelerator sends a NACK message back to the orchestrator server1220, which in turn, sends the NACK message to the compute device2110. Otherwise, the accelerator1250registers the class of service (e.g., in the resource utilization threshold data1506) and sends an acknowledgement message (“ACK”) back to the orchestrator server1220. In the illustrative embodiment, the acknowledgement message includes an identifier of a service level agreement associated with the registered class of service. The orchestrator server1220, in the illustrative embodiment, then sends the acknowledgement message to the compute device2210.

Referring now toFIG.22, in a series2200of messages, a compute device2210, which may be a CPU (e.g., CPU1272) on a compute sled (e.g., the compute sled1270) executing a workload associated with a workload to be executed on an accelerator (e.g., the accelerator1250) sends a message2220to the orchestrator server1220to set a resource utilization threshold for a particular logic portion (e.g., the logic portion1252) and a particular resource (e.g., the main memory1304, the data storage devices1308, the communication circuitry1314). The message2220includes a set of parameters, including an identifier of the accelerator (e.g., the accelerator1250), an identifier of the logic portion (e.g., the logic portion1252) in the accelerator1250, an identifier of the resource for which the threshold pertains, and an actual value of the threshold or a reference to the class of service (e.g., a class of service registered in the series2100of messages described with reference toFIG.21). The orchestrator server1220subsequently determines whether the compute device2210has permission to set the resource utilization threshold (e.g., whether the compute device2210is included in the same managed node1230as the accelerator1250and is executing a workload associated with the workload to be accelerated by the accelerator1250). In response to a determination that the compute device2210does not have the requisite permissions, the orchestrator server1220sends a NACK message back to the compute device2210. Otherwise, the orchestrator server1220forwards the message on to the identified accelerator (e.g., the accelerator1250). In response, the accelerator1250checks the parameters, including determining whether the requested resource utilization threshold does not exceed the total capacity of the identified resource, and if the parameters are satisfactory, reconfigures the resource utilization threshold (e.g., by storing the new resource utilization threshold in the resource utilization threshold data1506for use by the dynamic resource allocation logic unit1308and the resource monitor logic unit1310ofFIG.13). The accelerator1250then sends an ACK message that includes an identifier of the service level agreement associated with the resource utilization threshold. Otherwise, the accelerator1250sends a NACK message that identifies an error in the parameters. In either case, the orchestrator server1220sends the response from the accelerator1250back to the compute device2210.

Referring now toFIG.23, in a series2300of messages, the compute device2210may send a message2320to the orchestrator server1220to remove a resource utilization threshold that was previously set, such as in the series2200of messages described with reference toFIG.22. In the illustrative embodiment, the message2320to remove the resource utilization threshold includes the identifier of the service level agreement that was previously sent from the accelerator1250to the compute device2210when the resource utilization threshold was set. In response, the orchestrator server1220sends the message2320to the accelerator1250. Subsequently, the accelerator1250, in the illustrative embodiment, determines whether the service level agreement identified in the message2320corresponds to a previously set resource utilization threshold. If not, the accelerator1250sends back a NACK message. Otherwise, the accelerator removes the resource utilization threshold (e.g., removes the resource utilization threshold from the resource utilization threshold data1506) and sends an ACK message back to the orchestrator server1220, which sends the ACK message to the compute device2210.

Referring now toFIG.24, in a series2400of messages, the compute device2210may send a message2420to the orchestrator server1220to adjust a resource utilization threshold that was previously set. The message2420includes the identifier of the service level agreement that was returned by the accelerator1250when the resource utilization threshold was originally set, and the adjusted threshold, which may be embodied as an absolute amount (e.g., gigabytes), a relative amount (e.g., 50%), or a class of service that has previously been registered (e.g., in the series2100of messages ofFIG.21). The orchestrator server1220receives the message2420and sends it to the accelerator1250which determines whether the adjusted resource utilization threshold is within the total amount of the resource available to the accelerator1250, and if so, sets the adjusted resource utilization threshold, such as by storing it in the resource utilization threshold data1506. Subsequently, the accelerator1250sends an ACK message to the orchestrator server1220which then sends the ACK message to the compute device2210. However, if the adjusted resource utilization threshold exceeds the total amount of the resource available in the accelerator1250, the accelerator1250instead sends back a NACK message to the orchestrator server1220, which then sends the NACK message to the compute device2210.

Referring now toFIG.25, in a series2500of messages, the compute device2210may send a message2520to the orchestrator server1220to register a resource utilization monitor to generate a violation message if a resource utilization threshold is not satisfied during the execution of a workload by a logic portion (e.g., the logic portion1252) of an accelerator (e.g., the accelerator1250). The message includes an identifier of the accelerator1250, an identifier of the logic portion1252, an identifier of the resource whose utilization is to be monitored, and the resource utilization threshold that, if not satisfied, should result in the accelerator1250sending a violation message indicating that the resource utilization threshold has not been satisfied. In response, the orchestrator server1220determines whether the compute device2210has permission to register the resource utilization monitor, using a process similar to that described with reference toFIG.21. If the orchestrator server1220determines that the compute device2210does not have permission to register the resource utilization monitor, the orchestrator server1220sends back a NACK message indicating that the compute device2210does not have permission to register a resource utilization monitor. Otherwise, the orchestrator server1220sends the message2520to the accelerator1250. In response, the accelerator1250determines whether the threshold amount of the resource specified in the message2520is within the total amount of the resource available to the accelerator1250and, if so, creates a resource utilization monitor, such as by storing the threshold in the resource utilization threshold data1506and determining to report a violation if the resource monitor logic unit1310determines that the utilization of the specified resource by the specified logic portion1252does not satisfy the threshold defined in the message2520. If the threshold amount in the message2520exceeds the total amount of the resource available, the accelerator1250instead sends back a NACK message. Otherwise, the accelerator1250sends back an ACK message indicating that the resource utilization monitor has been successfully registered. In the illustrative embodiment, the ACK message includes an identifier of the registered resource utilization monitor. The accelerator1250may store the identifier of the registered monitor in the resource utilization threshold data1506in association with the resource utilization threshold.

Referring now toFIG.26, in a series2600of messages, during the execution of a workload, if the accelerator1250determines that a resource utilization monitor that was registered previously (e.g., the resource utilization monitor registered in the series2500of messages), the accelerator1250sends a violation message2620to the orchestrator server1220. The violation message2620, in the illustrative embodiment, includes the identifier of the registered resource utilization monitor corresponding to the violated resource utilization threshold. In some embodiments, the violation message2620may additionally include the present resource utilization of the corresponding resource by the corresponding logic portion1252. The orchestrator server1220, in response, sends the violation message2620to the compute device2210.

Referring now toFIG.27, in a series2700of messages, the compute device2210may send a message2720to deregister a resource utilization monitor (e.g., the resource utilization monitor registered in the series of 2500 of messages). The message2720includes the identifier of the resource utilization monitor to be deregistered. The orchestrator server1220, in the illustrative embodiment, receives the message2720and sends the message2720on to the accelerator1250. In response, the accelerator1250determines whether the identifier corresponds with a registered resource utilization monitor, which may be stored in association with the corresponding resource utilization threshold in the resource utilization threshold data1506. If so, the accelerator1250deregisters the resource utilization monitor, such as by removing the corresponding resource utilization threshold and monitor identifier from the resource utilization threshold data1506, and sends back an ACK message. Otherwise, the accelerator1250sends back a NACK message indicating that the deregistration failed.

EXAMPLES

Illustrative examples of the technologies disclosed herein are provided below. An embodiment of the technologies may include any one or more, and any combination of, the examples described below.

Example 1 includes an accelerator to dynamically manage the utilization of shared resources within the accelerator, the accelerator comprising acceleration circuitry comprising multiple logic portions, wherein each logic portion is capable of executing a different workload; one or more shared resources to be used by the logic portions in the execution of the workloads; communication circuitry to receive a workload to be executed by a logic portion of the accelerator; and a dynamic resource allocation logic unit to (i) identify a resource utilization threshold associated with one or more of the shared resources of the accelerator to be used by a logic portion of the multiple logic portions in the execution of the workload, (ii) limit, as a function of the resource utilization threshold, the utilization of the one or more shared resources by the logic portion as the logic portion executes the workload, and (iii) adjust the resource utilization threshold as the workload is executed.

Example 2 includes the subject matter of Example 1, and further including a resource monitor logic unit to monitor the resource utilization by the logic portion as the workload is executed and report the resource utilization to another device.

Example 3 includes the subject matter of any of Examples 1 and 2, and wherein the resource monitor logic unit is further to determine whether the present resource utilization satisfies the resource utilization threshold associated with the corresponding resources and wherein to report the present resource utilization to another device comprises to report the present resource utilization in response to a determination that the present resource utilization does not satisfy the resource utilization threshold.

Example 4 includes the subject matter of any of Examples 1-3, and wherein to adjust the resource utilization threshold comprises to receive an adjustment to the resource utilization threshold from the other device; and apply the adjustment to the resource utilization threshold.

Example 5 includes the subject matter of any of Examples 1-4, and wherein to receive the workload comprises to receive a bit stream indicative of the workload to be accelerated.

Example 6 includes the subject matter of any of Examples 1-5, and wherein to receive the workload comprises to receive a designation of a logic portion to execute the workload.

Example 7 includes the subject matter of any of Examples 1-6, and wherein to identify the resource utilization threshold comprises to receive resource utilization threshold data indicative of the resource utilization threshold from an orchestrator server.

Example 8 includes the subject matter of any of Examples 1-7, and wherein to identify the resource utilization threshold comprises to receive resource utilization threshold data indicative of the resource utilization threshold from a processor assigned to execute a portion of the workload.

Example 9 includes the subject matter of any of Examples 1-8, and wherein to identify the resource utilization threshold comprises to receive a resource utilization threshold indicative of an amount of memory to be used by the logic portion.

Example 10 includes the subject matter of any of Examples 1-9, and wherein to identify the resource utilization threshold comprises to receive a resource utilization threshold indicative of an amount of data storage to be used by the logic portion.

Example 11 includes the subject matter of any of Examples 1-10, and wherein to identify the resource utilization threshold comprises to receive a resource utilization threshold indicative of an amount of network bandwidth to be used by the logic portion.

Example 12 includes the subject matter of any of Examples 1-11, and wherein to identify the resource utilization threshold comprises to receive an identifier of a class of service associated with an amount of a resource to be used by the logic portion.

Example 13 includes the subject matter of any of Examples 1-12, and wherein to identify the resource utilization threshold comprises to receive a request to register a resource utilization monitor to monitor a utilization of one or more of the resources by the logic portion.

Example 14 includes the subject matter of any of Examples 1-13, and wherein to limit the utilization of the one or more resources comprises to receive a request from the logic portion for allocation of an amount of a resource; determine whether the requested amount is less than or equal to the resource utilization threshold; and allocate, in response to a determination that the requested amount is less than or equal to the resource utilization threshold, the requested amount to the logic portion.

Example 15 includes the subject matter of any of Examples 1-14, and wherein the resource monitor logic unit is further to determine whether less than the resource utilization threshold is presently utilized by the logic portion; and determine, in response to a determination that that less than the resource utilization threshold is presently utilized by the logic portion, that the resource utilization threshold is not satisfied.

Example 16 includes a method for dynamically managing the utilization of shared resources within an accelerator, the method comprising receiving, by the accelerator, a workload to be executed by a logic portion of a plurality of logic portions of the accelerator; identifying, by the accelerator, a resource utilization threshold associated with one or more shared resources of the accelerator to be used by the logic portion in the execution of the workload; limiting, as a function of the resource utilization threshold, the utilization of the one or more shared resources by the logic portion as the logic portion executes the workload; and adjusting, subsequent to the limiting of the utilization, the resource utilization threshold as the workload is executed.

Example 17 includes the subject matter of Example 16, and further including monitoring, by the accelerator, the resource utilization by the logic portion as the workload is executed; and reporting, by the accelerator, the resource utilization to another device.

Example 18 includes the subject matter of any of Examples 16 and 17, and further including determining, by the accelerator, whether the present resource utilization satisfies the resource utilization threshold associated with the corresponding resources; wherein reporting the present resource utilization to another device comprises reporting the present resource utilization in response to a determination that the present resource utilization does not satisfy the resource utilization threshold.

Example 19 includes the subject matter of any of Examples 16-18, and wherein adjusting the resource utilization threshold comprises receiving, by the accelerator, an adjustment to the resource utilization threshold from the other device; and applying, by the accelerator, the adjustment to the resource utilization threshold.

Example 20 includes the subject matter of any of Examples 16-19, and wherein receiving the workload comprises receiving a bit stream indicative of the workload to be accelerated.

Example 21 includes the subject matter of any of Examples 16-20, and wherein receiving the workload comprises receiving a designation of a logic portion to execute the workload.

Example 22 includes the subject matter of any of Examples 16-21, and wherein identifying the resource utilization threshold comprises receiving resource utilization threshold data indicative of the resource utilization threshold from an orchestrator server.

Example 23 includes the subject matter of any of Examples 16-22, and wherein identifying the resource utilization threshold comprises receiving resource utilization threshold data indicative of the resource utilization threshold from a processor assigned to execute a portion of the workload.

Example 24 includes the subject matter of any of Examples 16-23, and wherein identifying the resource utilization threshold comprises receiving a resource utilization threshold indicative of an amount of memory to be used by the logic portion.

Example 25 includes the subject matter of any of Examples 16-24, and wherein identifying the resource utilization threshold comprises receiving a resource utilization threshold indicative of an amount of data storage to be used by the logic portion.

Example 26 includes the subject matter of any of Examples 16-25, and wherein identifying the resource utilization threshold comprises receiving a resource utilization threshold indicative of an amount of network bandwidth to be used by the logic portion.

Example 27 includes the subject matter of any of Examples 16-26, and wherein identifying the resource utilization threshold comprises receiving an identifier of a class of service associated with an amount of a resource to be used by the logic portion.

Example 28 includes the subject matter of any of Examples 16-27, and wherein identifying the resource utilization threshold comprises receiving a request to register a resource utilization monitor to monitor a utilization of one or more of the resources by the logic portion.

Example 29 includes the subject matter of any of Examples 16-28, and wherein limiting the utilization of the one or more resources comprises receiving a request from the logic portion for allocation of an amount of a resource; determining whether the requested amount is less than or equal to the resource utilization threshold; and allocating, in response to a determination that the requested amount is less than or equal to the resource utilization threshold, the requested amount to the logic portion.

Example 30 includes the subject matter of any of Examples 16-29, and further including determining, by the accelerator, whether less than the resource utilization threshold is presently utilized by the logic portion; and determining, by the accelerator and in response to a determination that less than the resource utilization threshold is presently utilized by the logic portion, that the resource utilization threshold is not satisfied.

Example 31 includes one or more machine-readable storage media comprising a plurality of instructions stored thereon that, in response to being executed, cause an accelerator to perform the method of any of Examples 16-30.

Example 32 includes an accelerator comprising means for performing the method of any of Examples 16-30.

Example 33 includes an accelerator to dynamically manage the utilization of shared resources within the accelerator, the accelerator comprising network communicator circuitry to receive a workload to be executed by the accelerator; workload executor circuitry to execute the workload with a logic portion of a plurality of logic portions of the accelerator; and resource allocator circuitry to (i) identify a resource utilization threshold associated with one or more shared resources of the accelerator to be used by the logic portion in the execution of the workload, (ii) limit, as a function of the resource utilization threshold, the utilization of the one or more shared resources by the logic portion as the logic portion executes the workload, and (iii) adjust, subsequent to the limiting of the utilization, the resource utilization threshold as the workload is executed.

Example 34 includes the subject matter of Example 33, and further including resource utilization monitor circuitry to monitor the resource utilization by the logic portion as the workload is executed; and wherein the network communicator circuitry is further to report the resource utilization to another device.

Example 35 includes the subject matter of any of Examples 33 and 34, and wherein the resource utilization monitor circuitry is further to determine whether the present resource utilization satisfies the resource utilization threshold associated with the corresponding resources; and to report the present resource utilization to another device comprises to report the present resource utilization in response to a determination that the present resource utilization does not satisfy the resource utilization threshold.

Example 36 includes the subject matter of any of Examples 33-35, and wherein to adjust the resource utilization threshold comprises to receive an adjustment to the resource utilization threshold from the other device; and apply the adjustment to the resource utilization threshold.

Example 37 includes the subject matter of any of Examples 33-36, and wherein to receive the workload comprises to receive a bit stream indicative of the workload to be accelerated.

Example 38 includes the subject matter of any of Examples 33-37, and wherein to receive the workload comprises to receive a designation of a logic portion to execute the workload.

Example 39 includes the subject matter of any of Examples 33-38, and wherein to identify the resource utilization threshold comprises to receive resource utilization threshold data indicative of the resource utilization threshold from an orchestrator server.

Example 40 includes the subject matter of any of Examples 33-39, and wherein to identify the resource utilization threshold comprises to receive resource utilization threshold data indicative of the resource utilization threshold from a processor assigned to execute a portion of the workload.

Example 41 includes the subject matter of any of Examples 33-40, and wherein to identify the resource utilization threshold comprises to receive a resource utilization threshold indicative of an amount of memory to be used by the logic portion.

Example 42 includes the subject matter of any of Examples 33-41, and wherein to identify the resource utilization threshold comprises to receiving a resource utilization threshold indicative of an amount of data storage to be used by the logic portion.

Example 43 includes the subject matter of any of Examples 33-42, and wherein to identify the resource utilization threshold comprises to receive a resource utilization threshold indicative of an amount of network bandwidth to be used by the logic portion.

Example 44 includes the subject matter of any of Examples 33-43, and wherein to identify the resource utilization threshold comprises to receive an identifier of a class of service associated with an amount of a resource to be used by the logic portion.

Example 45 includes the subject matter of any of Examples 33-44, and wherein to identify the resource utilization threshold comprises to receive a request to register a resource utilization monitor to monitor a utilization of one or more of the resources by the logic portion.

Example 46 includes the subject matter of any of Examples 33-45, and wherein to limit the utilization of the one or more resources comprises to receive a request from the logic portion for allocation of an amount of a resource; determine whether the requested amount is less than or equal to the resource utilization threshold; and allocate, in response to a determination that the requested amount is less than or equal to the resource utilization threshold, the requested amount to the logic portion.

Example 47 includes the subject matter of any of Examples 33-46, and wherein to determine whether the resource utilization threshold is satisfied comprises to determine whether less than the resource utilization threshold is presently utilized by the logic portion; and determine, in response to a determination that less than the resource utilization threshold is presently utilized by the logic portion, that the resource utilization threshold is not satisfied.

Example 48 includes an accelerator to dynamically manage the utilization of shared resources within the accelerator, the accelerator comprising circuitry for receiving a workload to be executed by a logic portion of a plurality of logic portions of the accelerator; means for identifying a resource utilization threshold associated with one or more shared resources of the accelerator to be used by the logic portion in the execution of the workload; means for limiting, as a function of the resource utilization threshold, the utilization of the one or more shared resources by the logic portion as the logic portion executes the workload; and means for adjusting, subsequent to the limiting of the utilization, the resource utilization threshold as the workload is executed.

Example 49 includes the subject matter of Example 48, and further including circuitry for monitoring the resource utilization by the logic portion as the workload is executed; and circuitry for reporting the resource utilization to another device.

Example 50 includes the subject matter of any of Examples 48 and 49, and further including circuitry for determining whether the present resource utilization satisfies the resource utilization threshold associated with the corresponding resources; wherein the circuitry for reporting the present resource utilization to another device comprises circuitry for reporting the present resource utilization in response to a determination that the present resource utilization does not satisfy the resource utilization threshold.

Example 51 includes the subject matter of any of Examples 48-50, and wherein the means for adjusting the resource utilization threshold comprises circuitry for receiving an adjustment to the resource utilization threshold from the other device; and circuitry for applying the adjustment to the resource utilization threshold.

Example 52 includes the subject matter of any of Examples 48-51, and wherein the circuitry for receiving the workload comprises circuitry for receiving a bit stream indicative of the workload to be accelerated.

Example 53 includes the subject matter of any of Examples 48-52, and wherein the circuitry for receiving the workload comprises circuitry for receiving a designation of a logic portion to execute the workload.

Example 54 includes the subject matter of any of Examples 48-53, and wherein means for identifying the resource utilization threshold comprises circuitry for receiving resource utilization threshold data indicative of the resource utilization threshold from an orchestrator server.

Example 55 includes the subject matter of any of Examples 48-54, and wherein the means for identifying the resource utilization threshold comprises circuitry for receiving resource utilization threshold data indicative of the resource utilization threshold from a processor assigned to execute a portion of the workload.

Example 56 includes the subject matter of any of Examples 48-55, and wherein the means for identifying the resource utilization threshold comprises circuitry for receiving a resource utilization threshold indicative of an amount of memory to be used by the logic portion.

Example 57 includes the subject matter of any of Examples 48-56, and wherein the means for identifying the resource utilization threshold comprises circuitry for receiving a resource utilization threshold indicative of an amount of data storage to be used by the logic portion.

Example 58 includes the subject matter of any of Examples 48-57, and wherein the means for identifying the resource utilization threshold comprises circuitry for receiving a resource utilization threshold indicative of an amount of network bandwidth to be used by the logic portion.

Example 59 includes the subject matter of any of Examples 48-58, and wherein the means for identifying the resource utilization threshold comprises circuitry for receiving an identifier of a class of service associated with an amount of a resource to be used by the logic portion.

Example 60 includes the subject matter of any of Examples 48-59, and wherein the means for identifying the resource utilization threshold comprises circuitry for receiving a request to register a resource utilization monitor to monitor a utilization of one or more of the resources by the logic portion.

Example 61 includes the subject matter of any of Examples 48-60, and wherein the means for limiting the utilization of the one or more resources comprises circuitry for receiving a request from the logic portion for allocation of an amount of a resource; circuitry for determining whether the requested amount is less than or equal to the resource utilization threshold; and circuitry for allocating, in response to a determination that the requested amount is less than or equal to the resource utilization threshold, the requested amount to the logic portion.

Example 62 includes the subject matter of any of Examples 48-61, and further including circuitry for determining whether less than the resource utilization threshold is presently utilized by the logic portion; and circuitry for determining, in response to a determination that less than the resource utilization threshold is presently utilized by the logic portion, that the resource utilization threshold is not satisfied.

Example 63 includes a compute device to manage the dynamic allocation of resources by an accelerator, the compute device comprising one or more processors; one or more memory devices having stored therein a plurality of instructions that, when executed by the one or more processors, cause the compute device to assign a workload to be accelerated by a logic portion of a plurality of logic portions of an accelerator; send resource utilization threshold data indicative of a resource utilization threshold of one or more resources of the accelerator to be used by the logic portion in the execution of the workload; receive resource utilization data indicative of a present resource utilization of the one or more resources by the logic portion as the workload is executed; determine an adjustment to the resource utilization threshold; and send the adjustment to the accelerator to adjust the allocation of the one or more resources among the logic portions of the accelerator as the workload is executed.

Example 64 includes the subject matter of Example 63, and wherein to assign a workload comprises to send a bit stream to the accelerator, wherein the bit stream is indicative of the workload to be executed.

Example 65 includes the subject matter of any of Examples 63 and 64, and wherein to assign a workload comprises to send a designation of one of a plurality of the logic portions of the accelerator to execute the workload.

Example 66 includes the subject matter of any of Examples 63-65, and wherein to send the resource utilization threshold data comprises to send a resource utilization threshold associated with a service level agreement assigned to the workload.

Example 67 includes the subject matter of any of Examples 63-66, and wherein to send the resource utilization threshold data comprises to send a resource utilization threshold indicative of an amount of memory to be used by the logic portion.

Example 68 includes the subject matter of any of Examples 63-67, and wherein to send the resource utilization threshold data comprises to send a resource utilization threshold indicative of an amount of data storage to be used by the logic portion.

Example 69 includes the subject matter of any of Examples 63-68, and wherein to send the resource utilization threshold data comprises to send a resource utilization threshold indicative of an amount of network bandwidth to be used by the logic portion.

Example 70 includes the subject matter of any of Examples 63-69, and wherein to send the resource utilization threshold data comprises to send an identifier of a class of service associated with an amount of a resource to be used by the logic portion.

Example 71 includes the subject matter of any of Examples 63-70, and wherein to send the resource utilization threshold data comprises to send a request to register a resource utilization monitor to monitor a utilization of one or more of the resources by the logic portion.

Example 72 includes the subject matter of any of Examples 63-71, and wherein the plurality of instructions, when executed, further cause the compute device to determine whether the present resource utilization satisfies the resource utilization threshold associated with the resource; and wherein to determine an adjustment to the resource utilization threshold comprises to determine the adjustment in response to a determination that the present resource utilization does not satisfy the resource utilization threshold.

Example 73 includes a method for managing the dynamic allocation of resources by an accelerator, the method comprising assigning, by the compute device, a workload to be accelerated by a logic portion of a plurality of logic portions of an accelerator; sending, by the compute device, resource utilization threshold data indicative of a resource utilization threshold of one or more resources of the accelerator to be used by the logic portion in the execution of the workload; receiving, by the compute device, resource utilization data indicative of a present resource utilization of the one or more resources by the logic portion as the workload is executed; determining, by the compute device, an adjustment to the resource utilization threshold; and sending, by the compute device, the adjustment to the accelerator to adjust the allocation of the one or more resources among the logic portions of the accelerator as the workload is executed.

Example 74 includes the subject matter of Example 73, and wherein assigning a workload comprises sending a bit stream to the accelerator, wherein the bit stream is indicative of the workload to be executed.

Example 75 includes the subject matter of any of Examples 73 and 74, and wherein assigning a workload comprises sending a designation of one of a plurality of the logic portions of the accelerator to execute the workload.

Example 76 includes the subject matter of any of Examples 73-75, and wherein sending the resource utilization threshold data comprises sending a resource utilization threshold associated with a service level agreement assigned to the workload.

Example 77 includes the subject matter of any of Examples 73-76, and wherein sending the resource utilization threshold data comprises sending a resource utilization threshold indicative of an amount of memory to be used by the logic portion.

Example 78 includes the subject matter of any of Examples 73-77, and wherein sending the resource utilization threshold data comprises sending a resource utilization threshold indicative of an amount of data storage to be used by the logic portion.

Example 79 includes the subject matter of any of Examples 73-78, and wherein sending the resource utilization threshold data comprises sending a resource utilization threshold indicative of an amount of network bandwidth to be used by the logic portion.

Example 80 includes the subject matter of any of Examples 73-79, and wherein sending the resource utilization threshold data comprises sending an identifier of a class of service associated with an amount of a resource to be used by the logic portion.

Example 81 includes the subject matter of any of Examples 73-80, and wherein sending the resource utilization threshold data comprises sending a request to register a resource utilization monitor to monitor a utilization of one or more of the resources by the logic portion.

Example 82 includes the subject matter of any of Examples 73-81, and further including determining, by the compute device, whether the present resource utilization satisfies the resource utilization threshold associated with the resource; and wherein determining an adjustment to the resource utilization threshold comprises determining the adjustment m response to a determination that the present resource utilization does not satisfy the resource utilization threshold.

Example 83 includes one or more machine-readable storage media comprising a plurality of instructions stored thereon that, in response to being executed, cause a compute device to perform the method of any of Examples 73-82.

Example 84 includes a compute device comprising means for performing the method of any of Examples 73-82.

Example 85 includes a compute device comprising one or more processors; one or more memory devices having stored therein a plurality of instructions that, when executed by the one or more processors, cause the compute device to perform the method of any of Examples 73-82.

Example 86 includes a compute device to manage the dynamic allocation of resources by an accelerator, the compute device comprising resource manager circuitry to assign a workload to be accelerated by a logic portion of a plurality of logic portions of an accelerator; and network communicator circuitry to (i) send resource utilization threshold data indicative of a resource utilization threshold of one or more resources of the accelerator to be used by the logic portion in the execution of the workload, (ii) receive resource utilization data indicative of a present resource utilization of the one or more resources by the logic portion as the workload is executed; wherein the resource manager circuitry is further to determine an adjustment to the resource utilization threshold, and the network communicator circuitry is further to send the adjustment to the accelerator to adjust the allocation of the one or more resources among the logic portions of the accelerator as the workload is executed.

Example 87 includes the subject matter of Example 86, and wherein to assign a workload comprises to send a bit stream to the accelerator, wherein the bit stream is indicative of the workload to be executed.

Example 88 includes the subject matter of any of Examples 86 and 87, and wherein to assign a workload comprises to send a designation of one of a plurality of the logic portions of the accelerator to execute the workload.

Example 89 includes the subject matter of any of Examples 86-88, and wherein to send the resource utilization threshold data comprises to send a resource utilization threshold associated with a service level agreement assigned to the workload.

Example 90 includes the subject matter of any of Examples 86-89, and wherein to send the resource utilization threshold data comprises to send a resource utilization threshold indicative of an amount of memory to be used by the logic portion.

Example 91 includes the subject matter of any of Examples 86-90, and wherein to send the resource utilization threshold data comprises to send a resource utilization threshold indicative of an amount of data storage to be used by the logic portion.

Example 92 includes the subject matter of any of Examples 86-91, and wherein to send the resource utilization threshold data comprises to send a resource utilization threshold indicative of an amount of network bandwidth to be used by the logic portion.

Example 93 includes the subject matter of any of Examples 86-92, and wherein to send the resource utilization threshold data comprises to send an identifier of a class of service associated with an amount of a resource to be used by the logic portion.

Example 94 includes the subject matter of any of Examples 86-93, and wherein to send the resource utilization threshold data comprises to send a request to register a resource utilization monitor to monitor a utilization of one or more of the resources by the logic portion.

Example 95 includes the subject matter of any of Examples 86-94, and wherein the resource manager circuitry is further to determine whether the present resource utilization satisfies the resource utilization threshold associated with the resource; and wherein to determine an adjustment to the resource utilization threshold comprises to determine the adjustment in response to a determination that the present resource utilization does not satisfy the resource utilization threshold.

Example 96 includes a compute device for managing the dynamic allocation of resources by an accelerator, the compute device comprising circuitry for assigning a workload to be accelerated by a logic portion of a plurality of logic portions of an accelerator; circuitry for sending resource utilization threshold data indicative of a resource utilization threshold of one or more resources of the accelerator to be used by the logic portion in the execution of the workload; circuitry for receiving resource utilization data indicative of a present resource utilization of the one or more resources by the logic portion as the workload is executed; means for determining an adjustment to the resource utilization threshold; and circuitry for sending the adjustment to the accelerator to adjust the allocation of the one or more resources among the logic portions of the accelerator as the workload is executed.

Example 97 includes the subject matter of Example 96, and wherein the circuitry for assigning a workload comprises circuitry for sending a bit stream to the accelerator, wherein the bit stream is indicative of the workload to be executed.

Example 98 includes the subject matter of any of Examples 96 and 97, and wherein the circuitry for assigning a workload comprises circuitry for sending a designation of one of a plurality of the logic portions of the accelerator to execute the workload.

Example 99 includes the subject matter of any of Examples 96-98, and wherein the circuitry for sending the resource utilization threshold data comprises circuitry for sending a resource utilization threshold associated with a service level agreement assigned to the workload.

Example 100 includes the subject matter of any of Examples 96-99, and wherein the circuitry for sending the resource utilization threshold data comprises circuitry for sending a resource utilization threshold indicative of an amount of memory to be used by the logic portion.

Example 101 includes the subject matter of any of Examples 96-100, and wherein the circuitry for sending the resource utilization threshold data comprises circuitry for sending a resource utilization threshold indicative of an amount of data storage to be used by the logic portion.

Example 102 includes the subject matter of any of Examples 96-101, and wherein the circuitry for sending the resource utilization threshold data comprises circuitry for sending a resource utilization threshold indicative of an amount of network bandwidth to be used by the logic portion.

Example 103 includes the subject matter of any of Examples 96-102, and wherein the circuitry for sending the resource utilization threshold data comprises circuitry for sending an identifier of a class of service associated with an amount of a resource to be used by the logic portion.

Example 104 includes the subject matter of any of Examples 96-103, and wherein the circuitry for sending the resource utilization threshold data comprises circuitry for sending a request to register a resource utilization monitor to monitor a utilization of one or more of the resources by the logic portion.

Example 105 includes the subject matter of any of Examples 96-104, and further including circuitry for determining whether the present resource utilization satisfies the resource utilization threshold associated with the resource; and wherein the means for determining an adjustment to the resource utilization threshold comprises means for determining the adjustment in response to a determination that the present resource utilization does not satisfy the resource utilization threshold.