Configurable computing resource physical location determination

Examples may include techniques to determine locations of a physical resource in a data center. A data center can include a number of racks having sled spaced. The sled spaces accommodate sleds having one or more physical resources disposed on each sled. The racks and sleds can include a beacon and beacon sensor, respectively, operable to determine a location of the sleds within the data center. Beacons and beacon sensors can exchange signals, a pod controller can receive an information element including indications of the exchanged signals and determine a location of the physical resource within the data center.

TECHNICAL FIELD

Embodiments described herein generally relate to data centers and particularly to physical resource location determination within a data center.

BACKGROUND

Advancements in networking have enabled the rise in pools of configurable computing resources. A pool of configurable computing resources may be formed from a physical infrastructure including disaggregate physical resources for example, as found in large data centers. The physical infrastructure can include a number of resources having processors, memory, storage, networking, power, cooling, etc. Management entities of these data centers can aggregate a selection of the resources to form servers and/or computing hosts. These hosts can subsequently be allocated to execute system SW (e.g., OSs, VMMs, or the like), host containers, VMs, and/or applications. However, as the number of resources in the pool grows, it can be difficult to determine a physical location (e.g., in the data center, or the like) of resources in the pool.

DETAILED DESCRIPTION

Data centers may be generally composed of a large number of racks that may contain numerous types of hardware or configurable resources (e.g., storage, central processing units (CPUs), memory, networking, fans/cooling modules, power units, etc.). The types of hardware or configurable resources deployed in data centers may also be referred to as disaggregate physical elements. It is to be appreciated, that the size and number of resources within a data center can be large, for example, on the order of hundreds of thousands of disaggregate physical elements. These disaggregate physical elements are often disposed in large warehouses and can be spread across multiple floors of a warehouse or even spread across multiple warehouses. Maintenance of the disaggregate physical elements can require physical inspection, service, removal, replacement or the like. However, due to the number of the disaggregate physical elements, determining the actual physical location of a particular disaggregate physical element within a data center can be challenging. It is with respect to these and/or other challenges that the examples described herein are needed.

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 in this figure, 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), graphics processing units (GPUs), memory, interconnect components, 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 twister 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 usage information for the various resources, predicts resource usage for different types of workloads based on past resource usage, and dynamically reallocates the resources based on this information.

The racks102A to102D 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-manipulable resource sleds. Furthermore, in some embodiments, the racks102A to102D include integrated power sources that receive a higher current than is typical for power sources. The increased current enables the power sources to provide additional power to the components on each sled, enabling the components to operate at higher than typical frequencies.

Data center100can also include beacons disposed throughout the data center to facilitate locating various ones of the physical resources105A to105D. For example, as depicted in this figure, beacons108A to108D are depicted coupled to racks102A to102D, respectively. The data center100further includes beacon sensors (refer toFIG. 7,FIG. 10andFIG. 12) which can be associated with physical resources105A to105D and used to determine a location of the physical resources105A to105D within the data center100.

It is noted, that the beacons and corresponding beacon sensors can be any suitable beacon and corresponding sensor to emit and to receive signals including indications of locations and/or other information. In particular, the beacon and beacon sensors depicted herein can be any configured to emit and detect any signal usable to determine a location of physical resources105A to105D within data center100. For example, the beacons and sensors can be radio frequency identification (RFID) beacons and sensors, near field communication (NFC) beacons and sensors, magnetic beacons and sensors, or the like). Furthermore, it is important to note, that the beacons108A to108D are depicted coupled to racks102A to102D while beacon sensors are depicted coupled to sleds (e.g., refer toFIG. 2,FIG. 7,FIG. 10andFIG. 12) and associated with physical resources105A to105D. However, this is done for purposes of convenience and clarity only. Examples are not limited in this context and a data center, such as, data center100, can be implemented with beacons coupled to sleds and beacon sensors coupled to racks.

During operation, beacon sensors and beacons108A to108D can exchange signals and communicate control signals and/or information elements including indications of the received signals to sled management controllers (refer toFIG. 11andFIG. 12). Sled management controllers can determine a physical location of individual physical resources105A to105D based on the received signals. Additionally, beacons108A to108D and/or beacon sensors can send information elements to management entities (e.g., an orchestration layer, or the like) for the data center100, the information elements can include indications of operating conditions of physical resources105A to105D. For example, the information elements can include indications (e.g., data, metrics, statistics, logs, beacon location, etc.) related failures, errors, runtime conditions, and/or location within the data center100of the physical resources105A to105D. This is explained in greater detail below.

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 in this figure, 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 resources205-1to205-4comprised in the sleds204-1to204-4of rack202. As depicted in this illustrative embodiment, physical resources205-1to205-4include physical storage resources205-1, physical accelerator resources205-2, physical memory resources205-3, and physical compute resources205-5. 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 manipulable sleds comprising disaggregated resources, each type of resource can be upgraded independently of each other and at their own optimized refresh rate.

Furthermore, it is noted, the number of sleds204-1to204-4and the arrangement (e.g., column, row, etc.) is depicted at a quantity and in an arrangement to facilitate understanding. However, examples are not limited in these contexts.

Rack202can include beacons208-1to208-3disposed in various locations on, within, or adjacent to rack202. The number of beacons208-1to208-3and their placement respective to rack202can include a number and arrangement to provide determination of a physical location of individual physical resources205-1to205-4based on signals exchanged between beacons208-1to208-3and beacons sensors disposed in sleds204-1to204-4.

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 in this figure, 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 in this figure, 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.

Additionally, beacons can be placed throughout the data center300to provide for physical location determination of individual ones of the physical resources (e.g., refer toFIG. 1andFIG. 2) that may be disposed within racks302-1to302-32. For example, beacons308-41to308-44are depicted disposed on rack302-4. In some examples, beacons (e.g., beacons308-41to308-44, or the like) can be disposed on various locations of a rack. For example, a beacon could be disposed on a lower front portion of a rack (e.g., beacon308-44on rack302-4, or the like) while another beacon could be disposed on a lower rear portion of a rack (e.g., beacon308-43on rack302-4, or the like). Likewise beacon(s) could be disposed on a top portion of a rack (e.g., beacons308-41and308-42, or the like). It is worth noting that less than 4 beacons could be disposed on a rack. In general, however, a quantity of beacons should be implemented to facilitate determining a location of a sled within a rack.

In some examples, beacons308can be disposed on each of the racks302. In other examples, beacons308can be disposed on alternating ones of the racks302, or the like. Furthermore, with some examples, beacons308can be disposed at locations on/within/adjacent racks302(e.g., on opposing corners of top and bottom, or the like) to reduce interference between signals from beacons308and to provide for co-location or triangulation techniques to be implemented to determine locations of physical resources within the data center300based on beacon signals. In some examples, beacons308may not be associated with pods (e.g., groups of racks, or the like) and/or an entire data center (e.g., data center300, or the like). As such, techniques described herein could be implemented to determine a location of racks within the data center, and not just sleds within racks. Examples 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 in this figure, 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 here, 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.

Data center400can also feature beacons disposed on ones of racks402A to402D. For example, as depicted beacons408A to408D are disposed on racks402A to402D, respectively.

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, and 4. 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 embodiments, the dual-mode switch may be a single physical network wire that may be capable of carrying Ethernet or Onmi-Path communication, which may be auto-detected by the dual-mode optical switch515or configured by the Pod management controller. This allows for the same network to be used for Cloud traffic (Ethernet) or High Performance Computing (HPC), typically Onmi-Path or Infiniband. Moreover, and in some instances, an Onmi-Path protocol may carry Onmi-Path communication and Ethernet communication. In some embodiments, dual-mode optical switches515may constitute leaf switches530in a leaf-spine architecture additionally including one or more dual-mode optical spine switches520. Note that in some embodiments, the architecture may not be a leaf-spine architecture, but may be a two-ply switch architecture to connect directly to the sleds.

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., Omni-Path Architecture, Infiniband, or the like) 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 herein. As reflected in this figure, rack architecture600may generally feature a plurality of sled spaces (or sled bays) into which sleds may be inserted, each of which may be robotically-accessible via a rack access region601. In this particular non-limiting example, rack architecture600features five sled spaces603-1to603-5. Sled spaces603-1to603-5feature respective multi-purpose connector modules (MPCMs)616-1to616-5. In some instances, when a sled is inserted into any given one of sled spaces603-1to603-5, the corresponding MPCM may couple with a counterpart MPCM of the inserted sled. This coupling may provide the inserted sled with connectivity to both signaling infrastructure and power infrastructure of the rack in which it is housed. When a sled is inserted into any given one of sled spaces603-1to603-5, the corresponding MPCM may couple with a counterpart MPCM of the inserted sled. This coupling may provide the inserted sled with connectivity to both signaling infrastructure and power infrastructure of the rack in which it is housed.

Rack architecture600features beacons disposed on portions of an outside perimeter of rack architecture600. For example, beacons608-1to608-4are depicted. In some examples, as depicted in this figure, beacons608-1to608-4can be located within a physical boundary or exterior wall portion of racks architecture600. For example, beacons608-1to608-4can be located inside an exterior wall portion of rack architecture600to reduce interference between beacons608-1to608-4and beacon sensors of sleds inserted into sled spaces603-1to603-5and interference between beacons608-1to608-4of rack architecture600and other rack architectures in a data center. Examples are not limited in this context.

Included among the types of sleds to be accommodated by rack architecture600may be one or more types of sleds that feature expansion capabilities.FIG. 7illustrates an example of a sled704that may be representative of a sled of such a type. As shown in this figure, 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.

Sled704can also feature a beacon sensor709. Beacon sensor709can be coupled to a management controller (refer toFIG. 11andFIG. 12). An example management controller is described in greater detail below. However, in general, such a management controller can operate to receive control signals or information elements from beacon sensors (e.g., beacon sensor709) including an indication of signals received from beacons608. The management controller can determine a physical location of a resource associated with the beacon sensor709based on the information elements, and particularly, the signals from beacons608. Thus, location of the sled (e.g., in sled space, along access pathways in the data center, or the like) can be determined based on the received beacon signals.

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 expansion 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 expansion sled718ofFIG. 7, in the event that the inserted sled is configured with such a module.

Rack architecture800features beacons disposed on portions of an outside perimeter of rack architecture800. For example, beacons808-1to808-4are depicted. The embodiments are not limited to this example.

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 “1U” 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. 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.

Rack architecture900features beacons disposed on portions of an outside perimeter of rack architecture90000. For example, beacons908-1to908-4are depicted. The embodiments are not limited in this context.

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 that offers significantly greater throughput and significantly reduced latency relative to Ethernet. 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.

Sled1004can further feature beacon sensor1009. Beacon sensor1009can be coupled (e.g., via dual-mode optical network interface circuitry1026, via an out-of-band channel, or the like) to a management controller (refer toFIG. 11andFIG. 12). An example management controller is described in greater detail below. However, in general, such a management controller can operate to receive control signals or information elements from beacon sensors (e.g., beacon sensor1009) including an indication of signals received from beacons908. The management controller can determine a physical location of a resource associated with the beacon sensor1009based on the information elements, and particularly, the signals from beacons908. 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 in this figure, 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 (e.g., ones of the beacons and/or beacon sensors described herein, or the like) associated with each component to be installed.

Infrastructure management framework1150A can feature pod controller1134and sled controller(s)1132. Pod controller1134and sled controller(s)1132can provide telemetry and/or signal reporting including indications of signals received from beacons in data center to determine physical location of element of physical infrastructure1100A within data center1100. The embodiments are not limited in this context.

As depicted, 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 processors, 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 available 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 framework1150B. In various embodiments, virtual infrastructure management framework1150B may be designed to implement workload fingerprinting techniques and/or machine-learning techniques in conjunction with managing allocation of virtual computing resources1136and/or SDI services1138to cloud services1140. In some embodiments, virtual infrastructure management framework1150B 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.

FIG. 12illustrates a rack1202coupled to various management controllers according to an embodiment. In general, rack1202may be representative of an architecture of any particular one of the racks depicted herein. It is noted, that the rack1202includes the general rack architecture600depicted inFIG. 6. As reflected in this figure, rack1202comprises a number of sleds disposed in sled spaces within rack access region1201. In this particular non-limiting example, rack1202features five sled1204-1to1204-5disposed in sled spaces1203-1to1203-5, respectively. Rack1202features beacons disposed on portions rack1202. For example, beacons1208-1to1208-4are depicted. Additionally, each of the sleds1204-1to1204-5include a beacon sensor. Specifically, as depicted, sleds1204-1to1204-5include beacon sensors1209-1to1209-5, respectively.

In general, beacon sensors can be coupled to management layers and/or frameworks of the data center to which the sleds are a part (e.g., any of the data centers depicted herein, or the like). As depicted, each of beacon sensors1209-1to1209-5are coupled to a one of sled controllers1232-1to1232-2while sled controllers1232-1to1232-2are coupled to pod controller1234. Pod controller1234can be coupled to a data center orchestration layer (not shown). In some embodiments (e.g., as shown) a sled controller can be coupled to more than one sled1203and beacon sensor1209. For example, sled controller1232-1is depicted coupled to sleds1204-1and1204-2while sled controller1232-2is depicted coupled to sleds1204-3to1204-5.

In some embodiments, sled controller1232-1to1232-2can include circuitry arranged to implement pooled system manageability engine (PSME) operations. In some embodiments, pod controller1234can comprise circuitry arranged to implement functions on components within a rack, or pod. For example, pod controller1234can be arranged to receive telemetry data corresponding to sleds coupled to the pod controller1234. In particular, pod controller1234can receive (e.g., via sled controllers1232-1to1232-2, or the like) information elements including indications of signals exchanged between beacons1208-1to1208-4and beacon sensors1209-1to1209-5(e.g., emitted by beacons1208-1to1208-4and received by beacon sensors1209-1to1209-5, emitted by beacon sensors1209-1to1209-5and received by beacons1208-1to1208-4, or the like). Such indications of signals can be used to determine a physical location of elements (e.g., physical resources, or the like) associated with the individual beacon sensors.

In some examples, beacon sensors can be implemented in the sled controller (e.g., sled controllers1232-1,1232-2, or the like). In such examples, beacon sensors could determine sled locations based on sensor information as detailed herein, in addition to information regarding the sleds controlled by each sled controller, which can be set, for example, at installation of a sled, or the like).

In some examples, beacon sensors may be configured to send information elements including indications of signals received from beacons to POD controllers. In some examples, such information elements can include identifying information from a beacon, such as, for example, a location of a beacon (e.g., rack number in the data center, location of the rack based on access pathways, beacon identification number, or the like). The physical location of the sled could subsequently be determined based on information (e.g., a lookup table, a map, or the like) regarding a physical layout of the data center and referencing the information received from the beacons.

Additionally, sled controllers1232-1to1232-2can include features to program and/or associated beacon sensors with particular sleds1202-1to1202-5. For example, at provisioning or installation of a sled1204within rack1202, beacon sensors can be associated with (e.g., programmed, burned, flashed, or the like) a particular one of sleds1204-1to1204-5and physical resources of the sled.

In some examples, the beacon sensors can be configured to “listen” or receive signals on particular frequencies while beacons within the data center can be programmed (e.g., by a POD controller, or the like) to on unique frequencies. In some examples, beacons can be configured to operate on unique frequencies at the time of manufacturing. In alternative examples, beacons can “search” or verify whether a frequency is in use (e.g., at power on, or the like) to find an unused (or used less than a threshold value, or the like) frequency. The beacon can be configured to send a control signal to the POD controller to alert the POD controller to the frequency to which the beacon is configured. The POD controller can subsequently configure the beacon sensors to a matching frequency.

With some implementations, beacon sensors (e.g., beacon sensors1209-1to1209-5) can provide a delay (e.g., in microseconds, or the like) between each selected frequencies for receiving the data. For example, different beacons (e.g., beacons1208-1to1208-4) on a rack can be configured to operate at different frequencies, such as, for example, 1000 MHz, 1100 MHz and 1200 MHz. Each beacon can be configured to transmit signals at a specified time. Assuming each beacon transmits at the same starting time, then beacon sensors will receive the signals at different times (e.g., due to the different frequencies, or the like) and the beacon sensor could be configured to distinguish between these frequencies.

In some examples, beacons (e.g., beacons1208-1to1208-4) may be configured to repeatedly transmit. During periods where a beacon is not transmitting, the beacon may be configured to enter a lower power state, such as, for example, an off state, a sleep state, or the like. In some examples, the beacons can be configured to receive control signals from the POD controller to cause the beacons to enter a lower power state, or exit from a lower power state.

A logic flow may be implemented in software, firmware, and/or hardware. In software and firmware embodiments, a logic flow may be implemented by computer executable instructions stored on at least one non-transitory computer readable medium or machine readable medium, such as an optical, magnetic or semiconductor storage. The embodiments are not limited in this context.

FIG. 13illustrates an example of a logic flow. This figure depicts logic flow1300. Logic flow1300may be representative of some or all of the operations executed by one or more logic, features, or devices described herein, such as apparatus1132and/or1134. More particularly, logic flow1300may be implemented by at least sled controller(s)1132and/or pod controller1134to determine a physical location of physical resources within a data center.

Logic flow1300can begin at block1310. At block1310“receive an information element to include indications of signals received, at a beacon sensor, from a beacon in a datacenter” sled controller1132, pod manager1134and/or physical infrastructure management framework1150A can receive an information element including indications of signals received by a beacon sensor from beacons in a data center. For example, beacon sensors709,1009,1209, or the like can send an information element including indications of signals received from beacons in a data center.

Continuing to block1320“identify a physical resource associated with the beacon sensor” sled controller1132, pod manager1134and/or physical infrastructure management framework1150A can determine a physical resource associated with the beacon sensor. As detailed herein, sleds can feature beacon sensors. Beacon sensors can be individually associated with a particular sled (e.g., at provisioning of the sled, at installation of the sled, during a maintenance procedure of the sled or the like).

Continuing to block1330“determine a location within the datacenter of the physical resource based on the indications of the signals received at the beacon sensor” sled controller1132, pod manager1134and/or physical infrastructure management framework1150A can determine a physical location, within the data center of the physical resource associated with the beacon sensor. For example, the sled controller1132, pod manager1134and/or physical infrastructure management framework1150A can determine a sled space in which the sled is installed, a rack in which the sled is installed, an access pathway to which the rack is disposed, a crossing of access pathways adjacent to the rack in which the sled is installed, or the like.

It is noted, that the location of sleds can be used to, for example, initiate maintenance operations for the sled. In a specific example, control signals can be send (e.g., by framework1150A, or the like) to cause a robot to go to the determined position and perform a maintenance operation on a sled. Examples are not limited in this context.

FIG. 14illustrates an example of a storage medium2000. Storage medium2000may comprise an article of manufacture. In some examples, storage medium2000may include any non-transitory computer readable medium or machine readable medium, such as an optical, magnetic or semiconductor storage. Storage medium2000may store various types of computer executable instructions, such as instructions to implement logic flow1300. Examples of a computer readable or machine readable storage medium may include any tangible media capable of storing electronic data, including volatile memory or non-volatile memory, removable or non-removable memory, erasable or non-erasable memory, writeable or re-writeable memory, and so forth. Examples of computer executable instructions may include any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, object-oriented code, visual code, and the like. The examples are not limited in this context.

FIG. 15illustrates an example computing platform3000. In some examples, as shown in this figure, computing platform3000may include a processing component3040, other platform components or a communications interface3060. According to some examples, computing platform3000may be implemented in a computing device such as a server in a system such as a data center or server farm that supports a manager or controller for managing configurable computing resources as mentioned above.

In some examples, communications interface3060may include logic and/or features to support a communication interface. For these examples, communications interface3060may include one or more communication interfaces that operate according to various communication protocols or standards to communicate over direct or network communication links. Direct communications may occur via use of communication protocols or standards described in one or more industry standards (including progenies and variants) such as those associated with the PCI Express specification. Network communications may occur via use of communication protocols or standards such those described in one or more Ethernet standards promulgated by the Institute of Electrical and Electronics Engineers (IEEE). For example, one such Ethernet standard may include IEEE 802.3-2012, Carrier sense Multiple access with Collision Detection (CSMA/CD) Access Method and Physical Layer Specifications, Published in December 2012 (hereinafter “IEEE 802.3”). Network communication may also occur according to one or more OpenFlow specifications such as the OpenFlow Hardware Abstraction API Specification. Network communications may also occur according to Infiniband Architecture Specification, Volume 1, Release 1.3, published in March 2015 (“the Infiniband Architecture specification”).

Computing platform3000may be part of a computing device that may be, for example, a server, a server array or server farm, a web server, a network server, an Internet server, a work station, a mini-computer, a main frame computer, a supercomputer, a network appliance, a web appliance, a distributed computing system, multiprocessor systems, processor-based systems, or combination thereof. Accordingly, functions and/or specific configurations of computing platform3000described herein, may be included or omitted in various embodiments of computing platform3000, as suitably desired.

It should be appreciated that the exemplary computing platform3000shown in the block diagram of this figure may represent one functionally descriptive example of many potential implementations. Accordingly, division, omission or inclusion of block functions depicted in the accompanying figures does not infer that the hardware components, circuits, software and/or elements for implementing these functions would necessarily be divided, omitted, or included in embodiments.

The disclosure now turns to providing example implementations.

A system comprising: a rack comprising a plurality of sled spaces, each of the plurality of sled spaces arranged to receive a sled having a beacon sensor coupled to the sled; and a beacon coupled to the rack, the beacon to emit a signal to cooperate with the beacon sensor to determine a location of the sled.

The system of example 1, comprising a processor and a memory storing instructions executable by the processor, the instructions to cause the processor to receive an information element from the beacon sensor, the information element to include an indication of a location of the sled within the rack.

The system of example 1, comprising the sled, the sled comprising at least one physical resource.

The system of example 1, comprising a plurality of sleds, each of the plurality of sleds disposed within a respective one of the sled spaces and having a beacon sensor.

The system of example 4, each of the plurality of sleds comprising at least one physical resource.

The system of example 5, comprising a sled controller, the sled controller communicatively coupled to the beacon sensors, the sled controller to: receive information elements from the beacon sensors, the information elements to include indication of signals exchanged between the beacon and the beacon sensors; and determine a location of a one of the sleds within the sled spaces of the rack.

The system of example 6, the information elements to include indication of operating conditions of the physical resources.

The system of example 7, the operating conditions comprising at least one of a fault, an error, or a runtime condition.

The system of example 6, the sled controller to program the beacon sensors to associate the beacon sensors to a particular one of the sleds.

The system of any one of examples 1 to 9, the physical resources comprising at least one of a processor, a memory, a storage, a graphics processing unit, a field-programmable gate array, or an interface.

The system of any one of examples 1 to 9, comprising: a plurality of racks, each of the plurality of racks comprising a plurality of sled spaces, each of the plurality of sled spaces arranged to receive a sled having a beacon sensor coupled to the sled; and a plurality of beacons, at least one of the plurality of beacons coupled to a respective one of the plurality of racks, the plurality of beacons to emit a signal to cooperate the beacon sensors.

The system example 11, the racks disposed in a data center.

The system of any one of examples 1 to 9, the physical resources comprising at least one of a physical compute resource, a physical accelerator resource, a physical storage resource, or a physical memory resource.

An apparatus, comprising: a sled to couple to a rack of a data center; and a beacon sensor coupled to the sled, the beacon sensor to receive a signal from a beacon and send an information element to a sled controller, the information element to include an indication of a location of the sled relative to the beacon.

The apparatus of example 14, comprising at least one physical resource coupled to the sled.

The apparatus of example 15, the information element to include indication of operating conditions of the physical resources.

The apparatus of example 16, the operating conditions comprising at least one of a fault, an error, or a runtime condition.

The apparatus of example 15, the beacon sensor to receive signals from a plurality of beacons in the data center, the information element to include an indication of a location of the sled relative to the plurality of beacons.

The apparatus of any one of examples 15 to 18, the physical resources comprising at least one of a processor, a memory, a storage, a graphics processing unit, a field-programmable gate array, or an interface.

The apparatus of any one of examples 15 to 18, the physical resource comprising at least one of a physical compute resource, a physical accelerator resource, a physical storage resource, or a physical memory resource.

A method comprising: receiving an information element to include indications of signals received, at a beacon sensor, from a beacon in a datacenter; identifying a first physical resource of the data center associated with the beacon sensor; and determining a location within the datacenter of the first physical resource based on the indications of the signals received at the beacon sensor.

The method of example 19, the data center comprising a plurality of racks, each of the plurality of racks comprising a plurality of sled spaces arranged to receive a sled, each of the sleds comprising at least one of a plurality of physical resources, the first physical resource a one of the plurality of physical resources.

The method of example 20, the information element to include an indication of a one of the plurality of racks and sled spaces in which the first physical resource is disposed.

The method of example 21, comprising receiving the information element at a pod controller of the data center.

The method of example 22, each of the sleds comprising a beacon sensor.

The method of example 22, the information elements to include indication of operating conditions of the first physical resource.

The method of example 24, the operating conditions comprising at least one of a fault, an error, or a runtime condition.

The method of example 22, the pod controller to program the beacon sensors to associate the beacon sensors to first physical resource.

The method of any one of examples 21 to 26, the first physical resources comprising at least one of a processor, a memory, a storage, a graphics processing unit, a field-programmable gate array, or an interface.

The method of any one of examples 21 to 26, the physical resources comprising at least one of a physical compute resource, a physical accelerator resource, a physical storage resource, or a physical memory resource.

At least one machine readable medium comprising a plurality of instructions that in response to being executed by a pod controller in a data center cause the pod controller to: receive an information element to include indications of signals received, at a beacon sensor, from a beacon in a datacenter; identify a first physical resource of the data center associated with the beacon sensor; and determine a location within the datacenter of the first physical resource based on the indications of the signals received at the beacon sensor.

The at least one machine readable medium of example 29, the data center comprising a plurality of racks, each of the plurality of racks comprising a plurality of sled spaces arranged to receive a sled, each of the sleds comprising at least one of a plurality of physical resources, the first physical resource a one of the plurality of physical resources.

The at least one machine readable medium of example 30, the information element to include an indication of a one of the plurality of racks and sled spaces in which the first physical resource is disposed.

The at least one machine readable medium of example 31, each of the sleds comprising a beacon sensor.

The at least one machine readable medium of example 31, the information elements to include indication of operating conditions of the first physical resource.

The at least one machine readable medium of example 33, the operating conditions comprising at least one of a fault, an error, or a runtime condition.

The at least one machine readable medium of example 31, comprising instructions that cause the pod controller to program the beacon sensor to associate the beacon sensors to first physical resource.

The at least one machine readable medium of examples 29 to 35, the first physical resources comprising at least one of a processor, a memory, a storage, a graphics processing unit, a field-programmable gate array, or an interface.

The at least one machine readable medium of examples 29 to 35, the physical resources comprising at least one of a physical compute resource, a physical accelerator resource, a physical storage resource, or a physical memory resource.

The at least one machine readable medium of any one of examples 29 to 37, wherein the machine readable medium is non-transitory.

An apparatus comprising: means to receive an information element to include indications of signals received, at a beacon sensor, from a beacon in a datacenter; means to identify a first physical resource of the data center associated with the beacon sensor; and means to determine a location within the datacenter of the first physical resource based on the indications of the signals received at the beacon sensor.

The apparatus of example 39, the data center comprising a plurality of racks, each of the plurality of racks comprising a plurality of sled spaces arranged to receive a sled, each of the sleds comprising at least one of a plurality of physical resources, the first physical resource a one of the plurality of physical resources.

The at least one machine readable medium of example 30, the information element to include an indication of a one of the plurality of racks and sled spaces in which the first physical resource is disposed.

The at least one machine readable medium of example 31, each of the sleds comprising a beacon sensor.

The at least one machine readable medium of example 31, the information elements to include indication of operating conditions of the first physical resource.

The at least one machine readable medium of example 33, the operating conditions comprising at least one of a fault, an error, or a runtime condition.

The at least one machine readable medium of example 31, comprising instructions that cause the pod controller to program the beacon sensor to associate the beacon sensors to first physical resource.

The at least one machine readable medium of examples 29 to 35, the first physical resources comprising at least one of a processor, a memory, a storage, a graphics processing unit, a field-programmable gate array, or an interface.

The at least one machine readable medium of examples 29 to 35, the physical resources comprising at least one of a physical compute resource, a physical accelerator resource, a physical storage resource, or a physical memory resource.

The at least one machine readable medium of any one of examples 29 to 37, wherein the machine readable medium is non-transitory.