Patent Publication Number: US-2022229701-A1

Title: Dynamic allocation of computing resources

Description:
BACKGROUND 
     With the development of computer technologies, especially distributed computation technology, cloud computing has become a popular computing model in recent years. Cloud computing is a model that accesses to a configurable set of computing resources (including web servers, storage, graphics processing units, etc.) in a convenient and on-demand manner over a network. The administrator of the set of computing resources can quickly configure, provide, or release resources with a small management overhead. The focus of cloud computing is the management of the computing resources. The dynamic allocation of resources for cloud computing has become a focus of research. 
     SUMMARY 
     According to an implementation of the subject matter, a solution for dynamic management of computing resources is provided. In the solution, a first request for using a target number of computing resources in a set of computing resources is received, at least one free computing resource of the set of computing resources being organized into at least one free resource group. When it is determined that a free matching resource group is absent from in the first resource group and a free redundant resource group is present in at least one free resource group, the target number of computing resources are allocated for the first request by splitting the free redundant resource group, wherein the number of resources in the free redundant resource group is greater than the target number. Therefore, the dynamic allocation of computing resources is enabled. 
     This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the subject matter, nor is it intended to be used to limit the scope of the subject matter. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates a block diagram of a computing environment in which a plurality of implementations of the subject matter may be implemented; 
         FIG. 2  illustrates a flowchart a process of dynamic allocation of computing resources in accordance with some implementations of the subject matter; 
         FIG. 3  illustrates an example topology of a set of computing resources in accordance with some implementations of the subject matter; 
         FIG. 4  illustrates a flowchart of a process of allocation with available computing resources in accordance with some implementations of the subject matter; 
         FIG. 5  illustrates a flowchart of a process of dynamic allocation of computing resources in accordance with other implementations of the subject matter; 
         FIG. 6  illustrates a block diagram of an example computing device in accordance with some implementations of the subject matter. 
     
    
    
     In the drawings, the same or similar reference numerals refer to the same or similar elements. 
     DETAILED DESCRIPTION 
     The subject matter described herein will now be discussed with reference to several example implementations. It is to be understood these implementations are discussed only for the purpose of enabling those skilled in the art to better understand and thus implement the subject matter described herein, rather than suggesting any limitations on the scope of the subject matter. 
     As used herein, the term “comprises” and its variants are to be read as open terms that mean “comprises, but is not limited to.” The term “based on” is to be read as “based at least in part on.” The terms “one implementation” and “an implementation” are to be read as “at least one implementation.” The term “another implementation” is to be read as “at least one other implementation.” The terms “first,” “second,” and the like may refer to different or same objects. Other definitions, either explicit or implicit, may be included below. 
     As discussed above, a core issue for cloud computing is the management of the computing resources. Some traditional solutions allocate computing resources to multiple tenants who share a set of computing resources through credit management. For example, in a scenario wherein multiple tenants share a multi-graphics processing unit (GPU) cluster in cloud computing, a tenant can be assigned a certain number of tokens as its credit, and the tenant can obtain a GPU to process the submitted jobs by consuming a token. However, in the process of allocating computing resources, the conventional solution only considers whether there is remaining credit for the tenant who applies for the resource, without taking the locations of the allocated computing resources into account. Accordingly, allocations for a huge amount of resource requests with small size (e.g., a single GPU) results in a fragmented allocation of the computing resources. It is therefore difficult to serve tenants who may need a large amount of continuous computing resources. 
     According to an implementation of the subject matter, a solution for dynamic management of computing resources is provided. In the solution, a first request for using a target number of computing resource in a set of computing resources is received, wherein at least one free computing resource of the set of computing resources is organized into at least one free resource group. When it is determined that a free matching resource group is absent from the first resource group and a free redundant resource group is present in at least one free resource group, the target number of computing resources are allocated for the first request by splitting the free redundant resource group, wherein the number of resources in the free redundant resource group is greater than the target number. Therefore, the dynamic allocation of computing resources is enabled. 
     Basic principles and several implementations of the subject matter are described below with reference to the drawings. 
       FIG. 1  is a diagram illustrating computing environment  100  in which a plurality of implementations of the subject matter may be implemented. It should be understood that the computing environment  100  illustrated in  FIG. 1  is merely exemplary and should not be construed as limiting the functionality and scope of the implementations described herein. As shown in  FIG. 1 , the computing environment  100  includes a computing resource scheduling device  115  and a set of computing resources  120 , which may include a plurality of computing resources  125 - 1  to  125 -N (individually or collectively referred to as computing resource  125 ). In some implementations, computing resource  125  can include a graphics processing unit GPU. 
     In some implementations, a computing resource scheduling device  115  can be implemented as a variety of user terminals or server terminals. The server terminal can be a server, a large scale computing device provided by various service providers, and the like. The user terminal can be, for example, any type of mobile terminal, a fixed terminal or a portable terminal, including a mobile phone, a multimedia computer, a multimedia tablet, an internet node, a communicator, a desktop computer, a laptop computer, a netbook computer, a tablet computer, a personal Communication system (PCS) device, a personal navigation device, a personal digital assistant (PDA), audio/video player, a digital camera/camcorder, a pointing device, a television receiver, a radio broadcast receiver, an e-book device, a gaming terminal or any combination thereof, including accessories and peripherals for these devices, or any combination thereof. 
     The computing resource scheduling device  115  can be used to schedule computing resource  125  in a set of computing resources  120 . The computing resource scheduling device  115  receives from one or more applications or tenants  105  a request  110  for using a target number of computing resources. The computing resource scheduling device  115  can allocate a target number of computing resources for the request  110  from the set of computing resources  125  based on a computing resource dynamic scheduling process as described in detail below. For example, computing resource scheduling device  115  can allocate computing resource  125 - 1  and computing resource  125 - 2  for the request  110 . 
     An example implementation of dynamic allocation of computing resources by the computing resource scheduling device  115  is discussed in detail below. 
     Example Process 
       FIG. 2  illustrates a flowchart of a process  200  of dynamic allocation of computing resources in accordance with some implementations of the subject matter. Process  200  can be implemented by computing resource scheduling device  115 . 
     At  202 , the computing resource scheduling device  115  receives a first request  110  for using a target number of computing resources in the set of computing resources  120 , wherein at least one free computing resource of the set of computing resources  120  is organized into at least one free resource group. In some implementations, the computing resource scheduling device  115  can receive the request  110  from the application or tenant  105  who applies for computing resources in the set of computing resources  120 . For example, the tenant  105  can issue a request to the computing resource scheduling device  115  for using 2 GPU devices to deploy machine learning algorithms. 
     In some implementations, the computing resource scheduling device  115  can organize free computing resources in a set of computing resources  120  into one or more free resource groups based on predetermined rules. For example, based on analysis of the historical requests, it can be determined that most of the tenants request 2 computing resources, and the computing resource scheduling device  115  may preferentially organize the free computing resources into a form of a free resource group including two continuous computing resources. 
     Considering that applications to be deployed on computing resources pay more and more attention to proximity of the computing devices, for example, two GPUs on the same PCIe switch will achieve a better performance than those located in two different computing nodes. In some implementations, the computing scheduling resource device  115  can determine a multi-level topology corresponding to the set of computing resources  110  and organize the free resource groups based on the multi-level topology. The process of organizing free resource groups will now be described with reference to  FIG. 3 , and the GPU is taken as an example of computing resource.  FIG. 3  is a diagram illustrating an example topology  300  of a set of computing resources in accordance with some implementations of the subject matter. 
     For the example topology  300  as shown in  FIG. 3 , the multiple GPUs are organized as follows: they are organized into multiple compute nodes, and each compute node includes 2 central processing unit (CPU) slots, each CPU socket is further connected to 2 buses and the interface standard (PCIe) switch, and each PCIe switch is connected to two GPUs. As shown in  FIG. 3 , the topology  300  includes a plurality of nodes associated with a plurality of different levels. 
     Specifically, the topology  300  can include a first level  340  including a plurality of GPU nodes  345 - 1  to  345 - 8  (individually or collectively referred to as GPU node  345 ) corresponding to individual GPUs. For example, GPU nodes  345 - 1  to  345 - 8  correspond to computing resources  125 - 1  to  125 -N of  FIG. 1  respectively (where N=8). The topology  300  also includes a second level  330  including nodes  335 - 1  to  335 - 4  (individually or collectively referred to as PCIe node  335 ) corresponding to PCIe switches which connect multiple GPUs. 
     The topology  300  further includes a third level  320  including nodes  325 - 1  to  325 - 2  (individually or collectively referred to as CPU node  325 ) corresponding to the CPU socket which connect multiple PCIe switches. Further, the topology  300  also includes a fourth level  310  including nodes  315 - 1  to  315 -N (individually or collectively referred to as computing device node  315 ) corresponding to computing devices which connect multiple CPU sockets. 
     The specific node arrangement and specific number of levels in the topology  300  shown in  FIG. 3  are merely exemplary and are not intended to limit the solution of the subject matter. It should be understood that there may be additional levels or fewer levels, which will depend on the actual topology. For example, when one CPU socket is connected to one PCIe switch, the second level  330  can be omitted. In some implementations, the multi-level topology can include at least two of the first level  340 , the second level  330 , the third level  320 , and the fourth level  310 . 
     In some implementations, the computing resource scheduling device  115  can organize, based on the multi-level topology corresponding to the set of computing resources  110 , the at least one free computing resource into at least one free resource group, such that each free resource group includes computing resources associated with the same node in the multi-level topology, wherein a node in the multi-level topology correspond to a computing resource in the set of computing resources or a connection component for multiple computing resources in the set of computing resources. 
     In some implementations, the computing resource scheduling device  115  can organize the free computing resources, such that the free computing resources are associated with nodes of the highest level. For example, continuing with the example of  FIG. 3 , based on the multi-level topology  300 , in a case where the computing resources  125 - 1  to  125 -N are free, the computing scheduling resource device  115  can organize the free computing resources  125  into the same free resource group. In this group, all of the free computing resources  125  are associated with the computing device node  315 - 2  in the fourth level of multi-level topology  300 . 
     As another example, computing resources  125 - 1  and  125 - 2  corresponding to nodes  345 - 1  and  345 - 2  are used. Based on the multi-level topology  300 , the computing resource scheduling device  115  can determine that the computing resources  125 - 3  and  125 - 4  corresponding to the nodes  345 - 3  and  345 - 4  will be organized into a free resource group  370 . Each of the computing resources in the free resource group  370  correspond to the PCIe node  335 - 2 . Similarly, the computing resource scheduling device  115  can organize computing resources  125 - 5  to  125 -N(N=8) corresponding to nodes  345 - 5  to  345 - 8  into one free resource group  380 . Each of the computing resources in the free resource group  380  is associated with the CPU node  380 . As shown in  FIG. 3 , since the computing resources  125 - 1  and  125 - 2  corresponding to nodes  345 - 1  and  345 - 2  are used, the computing resources  125 - 1  and  125 - 2  will not be organized into a same free resource group along with computing resources  125 - 5  to  125 - 8 . Based on such a free resource organization manner, the computing resource scheduling device  115  can ensure the proximity for the allocated computing resources, thereby improving the efficiency of computing resources during runtime. 
     With continued reference to  FIG. 2 , at  204 , the computing resource scheduling device  115  determines whether a free matching resource group with a target number of computing resources is present in at least one of the free resource groups. In some implementations, computing resource scheduling device  115  can maintain a list of a free resource groups. Continuing with the example of  FIG. 3 , when all of the eight computing resources  125  are free, the computing resource scheduling device  115  can determine that there is only one free resource group with eight computing resources. In response to determining at  204  that the at least one free resource group includes a free matching resource group, the method  200  can also proceed to  210 , where the computing resource scheduling device  115  allocates the computing resources in the free matching resource group for the first request  110 . 
     In response to determining at  204  that the free matching resource group is absent from at least one free resource group, method  200  proceeds to  206 , where computing resource scheduling device  115  determines whether at least one free resource group includes a free redundant resource group, wherein the number of resources in the free redundant resource group is greater than the target number. Continuing with the example of  FIG. 3 , for example, when the first request  110  requests to use 2 computing resources, the computing resource scheduling device  115  may determine that there is no free matching resource group corresponding to the target number “2”. 
     The computing resource scheduling device  115  can further determine whether there is a free redundant resource group. In some implementations, the computing resource scheduling device  115  can search for a free redundant resource group in a higher level in an increasing order. For example, when the computing resource scheduling device  115  determines that there is no free resource group with a size of 2, it may further determine whether there is a free resource group (a resource group with a size of 4) corresponding to the third level  320 , and if not, then further determine whether there is a free resource group (a resource group with a size of 8) corresponding to the fourth level  310 . 
     In response to determining at  206  that the at least one free resource group includes a free redundant resource group, the method  200  proceeds to  208 , where the computing resource scheduling device  115  allocates a target number of computing resources for the first request by splitting the free redundant resource group. In some implementations, the computing resource scheduling device  115  can split the free redundant resource group into a first resource group and at least one second resource group, wherein the first resource group has a target number of computing resources. The computing resources scheduling device  114  can then allocate the computing resources in the first resource group for the first request. For example, continuing with the example of  FIG. 3 , when the eight computing resources  125  are all free, and the number of computing resources requested by the first request  110  is 2, the computing resource scheduling device  115  may split the free redundant resource group into the first resource group  360  (including the computing resources  125 - 1  and  125 - 2 ), a free resource group  370  (including the computing resources  125 - 3  and  125 - 4 ), and a free resource group  380  (including the computing resources  125 - 5  to  125 - 8 ). The computing resource scheduling device  115  may further allocate the computing resources  125 - 1  and  125 - 2  in the first resource  360  for the first request  110 . 
     In some implementations, the computing resource scheduling device  115  can split free redundant resource groups according to the topology. For example, the computing resource scheduling device  115  may split the free redundant resource group, which corresponds to the node  315 - 2  in the fourth level  310 , into two nodes  325 - 1  and  325 - 2  in the third level  320 . The free resource group corresponding to the node  325 - 1  is further split to two free resource groups corresponding to the nodes  335 - 1  and  335 - 2  in the fourth level  330 . Based on such a manner, the computing resource scheduling device  115  can further ensure that a larger continuous computing resource group is retained as much as possible, while ensuring the proximity of the allocated resources. Therefore, the computing resources can meet the requirements of usage requests with different sizes. 
     In some implementations, in response to completion of the first request  110 , the computing resource scheduling device  115  can mark the first resource group as free. The computing resource scheduling device  115  may further determine that all of the computing resources in the at least one second resource group are free, and then merge the first resource group and the at least one second resource group into a new free resource group. For example, continuing with the example of  FIG. 3 , when determining that the computing resources  125 - 1  and  125 - 2  corresponding to nodes  345 - 1  and  345 - 2  are marked as free, the computing resource scheduling device  115  may first determine whether the remaining computing resources  125 - 3  and  125 - 4  corresponding to the node  325 - 1  in the higher layer are free, and if so, the four computing resources  125 - 1  to  125 - 2  may be merged into a new free resource group. Further, the computing resource scheduling device  115  can also determine whether the remaining computing resources  125 - 5  to  125 -N(N=8) corresponding to the node  315 - 2  above node  325 - 1  are free, and if so, the resource scheduling device  115  may further merge the computing resources  125 - 1  to  125 -N(N=8) into a new free resource group for processing subsequent requests. In this manner, computing resource scheduling device  115  can always reserve a larger set of continuous computing resource groups, thereby enabling computing resources to meet the requirements of usage requests with different sizes. 
     In some implementations, in response to determining at  206  that a free redundant resource group is absent from the at least one free resource group, the method  200  can also proceed to  212 , where the computing resource scheduling device  115  determines whether the priority of first request  110  exceeds a priority threshold. In some implementations, the application and/or tenant  105  can append information indicating the priority when initiating the first request  110 . For example, the application and/or tenant  105  can specify a particular priority based on the type of tasks to be deployed. For example, a task with a higher importance can be assigned with a higher priority. 
     In some implementations, the computing resource scheduling device  115  can also implement priority control of the received requests.  FIG. 4  shows a flowchart of a process for priority control in accordance with further implementations of the subject matter. As shown in  FIG. 4 , at block  402 , the computing resource scheduling device  115  can determine a first number of computing resources in a resource group that the first tenant  105  associated with the first request has used. At block  404 , the computing resource scheduling device  115  may determine whether a sum of the target number and the first number exceeds the upper limit of the number of computing resources corresponding to the first tenant  105 . In some implementations, the upper limit of the number of computing resources corresponding to the first tenant is equal to a sum of a second number of computing resources pre-allocated for the first tenant and a third number of computing resources obtained by the tenant through exchanging with a second tenant. 
     For example, based on the service purchased by the tenant  105 , the computing resource scheduling device  115  may set a second number (also referred to as a tenant credit) of pre-allocated resources, for example 4, for the first tenant who submits the first request  110 . In some implementations, the computing resource scheduling device  115  can support dynamic adjustment of a second number of the pre-allocated resources of the tenant  105 . For example, the tenant  105  may apply to the computing resource scheduling device  115  to reduce the tenant credit in a first time period, and to increase the tenant credit in a second time period. In this manner, for example, the tenant  105  can hand over the computing resources that are usually free in exchange for more computing resources in a certain period when more jobs need to be processed. 
     In some implementations, each tenant can be pre-allocated with a virtual private set of computing resources, and resources in the virtual private set of computing resources can always be occupied by the tenant who has a higher priority. In some implementations, the virtual private set of computing resources can correspond to a node in a layer in the multi-level topology described above, such that the computing resources allocated to the tenant are always contiguous. 
     In some implementations, the computing resource scheduling device  115  can also support resource exchanges between the tenants. For example, the computing resource scheduling device  115  can configure predetermined rules for resource exchanges and collect resource exchange requests submitted by the tenants. The computing resource scheduling device can determine whether the submitted resource exchange request conforms to a predetermined rule for performing resource exchange. In some implementations, the predetermined rules may comprise exchanging computing resources based on points of different tenants. For example, different tenants can gain corresponding points by providing computing resources. For example, a tenant A can apply for exchanging one computing resource with 2 points, a tenant B can apply for exchanging one computing resource with 3 points, and a tenant C can apply for providing computing resources. In this case, according to the predetermined rule, the computing resource scheduling device  115  may determine that the tenant B can obtain the computing resources provided by the tenant C at the cost of 3 points, and the tenant C can gain the corresponding points. Based on such a manner, the computing resource scheduling device  115  can support the exchange of resources owned by different tenants, thereby further improving the usage efficiency of the computing resources. For example, the first tenant  105  can obtain two additional available computing resources through resource exchange. 
     In response to determining at block  404  that the sum exceeds an upper limit of the number of computing resources, the method proceeds to block  406 , where the computing resource scheduling device  115  may set the priority of the first request to be below a priority threshold. Based on such a manner, the computing resource scheduling device  115  can enable the tenant  105  to occupy at a lower priority some of the computing resources of other tenants which are temporarily free, thereby increasing the usage ratio of the computing resources. 
     Alternatively, in response to determining at block  404  that the sum exceeds the upper limit of the number of computing resources, the computing resource scheduling device  115  may suspend the first request until that the sum is less than or equal to the upper limit of the number of computing resources. 
     Alternatively, in response to determining at block  404  that the sum exceeds an upper limit of the number of computing resources, the computing resource scheduling device  115  may also alert the tenant  105  whether to allocate resources with low priority and remind the tenant  105  that the resources allocated with low priority may be reclaimed at any time. The computing resource scheduling device  115  may set the priority of the first request  110  to be lower than a threshold if the tenant  105  determines to allocate resources with a low priority. 
     With continued reference to  FIG. 2 , in response to determining at  212  that the priority is above the priority threshold, the method  200  can also proceed to  214 , where the computing resource scheduling device  115  allocates, for the first request, a target number of computing resources including at least one available computing resource in the set of computing resources. The available computing resources can comprise both a free computing resource and a candidate computing resource, and the candidate computing resource is a resource which has been allocated to a second request with a priority lower than or equal to a priority threshold. For example, when it is determined in the process through block  202  to block  206  that the tenant has no free computing resources and the priority of the first request  110  submitted by the tenant is above the priority threshold, some requests with a lower priority may have occupied the resources in the virtual private resource set that has been allocated to the tenant. 
     In some implementations, the computing resource scheduling device  115  allows a request with a priority exceeding a priority threshold to occupy computing resources that have been allocated to requests with a priority lower than or equal to the priority threshold, which are also referred to as candidate computing resources. The computing resource scheduling device  115  may also organize the available computing resources into at least one available computing resource group in the same manner as organizing the free resource groups. The process of block  214  will be described in detail below with reference to  FIG. 5 , which shows a flowchart of a process  500  for allocation with available computing resources in accordance with some implementations of the subject matter. 
     As shown in  FIG. 5 , at block  502 , the computing resource scheduling device  115  can determine whether an available matching resource group with a target number of computing resources is present in at least one of the available resource groups. Continuing with the example of  FIG. 3 , for example, the computing resources  125 - 1  and  125 - 2  corresponding to the nodes  345 - 1  and  345 - 2  are assigned to a second request which is below a priority threshold, the available resources in the case include the computing resources  125 - 1  to  125 -N (N=8), although the resources  125 - 1  and  125 - 2  are not free. Thus, in accordance with the manner described above, the computing resource scheduling device  115  can organize the available computing resources  125 - 1  to  125 - 8  into one available computing resource group. 
     In response to determining at block  502  that an available matching resource group is present in at least one of the available resource groups, the method proceeds to block  504 , wherein the computing resource scheduling device  115  can reclaim the computing resources that have been allocated in the available matching resource group. For example, when the first request  110  requires using eight computing resources, the computing resource scheduling device  115  can directly terminate the jobs performed on the computing resources  125 - 1  and  125 - 2  and reclaim the computing resources  125 - 1  and  125 - 2  that have been allocated to the second request. At block  506 , the computing resource scheduling device  115  allocates, for the first request  110 , the computing resources in the available matching resource groups. For example, the computing resource scheduling device  115  can allocate the available computing resources  125 - 1  to  125 -N(N=8) for the first request  110 . 
     Based on such a manner, the computing resource scheduling device  115  can also ensure that other tenants can always obtain computing resources within their corresponding credits while supporting some requests to temporarily occupy computing resources previously allocated to other tenants. 
     In response to determining at block  502  that an available matching resource group is absent from the at least one available resource group, the method proceeds to block  508 , where the computing resource scheduling device  115  can determine whether the at least one available resource group includes an available redundant resource group, wherein the number of resources in the available redundant resource group is greater than the target number. 
     In response to determining at block  508  that an available redundant resource group is present in the at least one available resource group, the method proceeds to block  510 , where the computing resource scheduling device  115  can allocate the target number of computing resources for the first request by splitting the available redundant resource group. It should be understood that the processes of blocks  508  and  510  are similar to the processes described above for blocks  206  and  208 , and the computing resource scheduling device  115  may obtain a target number of computing resources by splitting a larger consecutive available computing resource group. 
     Based on the above manner, the computing resource scheduling device  115  can perform different personalized allocation logic for different priority requests. Given the premise of preferentially allocating free computing resources, the high priority request can further use the computing resources occupied by requests with a low priority, thereby increasing the flexibility of computing resource allocation. 
     Example Environment 
       FIG. 6  is a block diagram illustrating a device  600  which is capable of implementing embodiments of the subject matter. The device  600  can be used to implement computing resource scheduling device  115  of  FIG. 1 . It should be understood that the device  600  illustrated in  FIG. 6  is merely exemplary and should not be construed as limitation to the functionality and scope of the implementations described herein. As shown in  FIG. 1 , components of the device  600  may include, but are not limited to, one or more processors or processing units  110 , a memory  120 , a storage device  130 , one or more communication units  140 , one or more input devices  150 , and one or multiple output devices  160 . 
     In some implementations, the device  600  can be implemented as a variety of user terminals or serving terminals. A serving terminal may be a server provided by a respective service provider, large-scale computing device, or the like. The user terminal may be any type of mobile terminal, fixed terminal or portable terminal, such as mobile telephone, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desk-top computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal navigation device, personal digital assistant (PDA), audio/video player, digital camera/video camera, positioning device, TV receiver, radio broadcast receiver, E-book device, gaming device or any combinations thereof, including accessories and peripherals of these devices or any combinations thereof. It would be appreciated that the computing device  100  can support any type of interface for a user (such as a “wearable” circuit.) 
     Processing unit  610  may be a physical or virtual processor and can implement various processes based on programs stored in the memory  620 . In a multi-processor system, a plurality of processing units execute computer executable instructions in parallel so as to improve parallel processing capability of the computing device  600 . The processing unit  610  may also be referred to as a central processing unit (CPU), a microprocessor, a controller, or a microcontroller. 
     The device  600  generally comprises various computer storage medium. The computer storage medium can be any medium accessible by the device  600 , including but not limited to volatile and non-volatile medium, and removable and non-removable medium. The memory  620  can be a volatile memory (for example, a register, cache, Random Access Memory (RAM)), non-volatile memory (for example, a Read-Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), flash memory), or any combination thereof. The memory  620  may include one or more program modules, for example computing resource scheduling module  622 , and these program modules are configured to perform functions of various implementations described herein. The computing resource scheduling module  622  may be accessed and run by the processing unit  610  to implement corresponding functions. The storage device  630  can be any removable and non-removable medium and may include machine-readable medium, which can be used for storing information and/or data and can be accessed in the device  600 . 
     Functions of the components of the device  600  may be implemented in a single computing cluster or multiple computers, and these computers can communicate through communicative connection. Therefore, the device  600  can operate in a networking environment using a logical connection with one or more other servers, personal computers (PCs) or further general network nodes. By means of the communication unit  640 , the device  600  can further communicate with one or more external devices (not shown) if required, the external device being for example a database  670 , other storage devices, a server and a display device, with one or more devices enabling the user to interact with the device  600 , or any devices (such as a network card, a modem and the like) enabling the device  600  to communicate with one or more other computing devices. Such communication can be performed via input/output (I/O) interfaces (not shown). 
     The input device  650  may include one or more of a variety of input devices, such as a mouse, a keyboard, a tracking ball, a voice-input device, and the like. The output device  660  may include one or more of a variety of output devices, such as a display, a loudspeaker, a printer, and the like. 
     The device  600  includes a computing resource scheduling module  622  configured to: receiving a first request for using a target number of computing resources in a set of computing resources, at least one free computing resource of the set of computing resources being organized into at least one free resource group; determine whether a free matching resource group with the target number of computing resources is present in the at least one free resource group; in response to the free matching resource group being absent from the at least one free resource group, determining whether a free redundant resource group is included in the at least one free resource group, a number of resources included in the free redundant resource group being greater than the target number; and in response to the free redundant resource group being present in the at least one free resource group, allocate the target number of computing resources for the first request by splitting the free redundant resource group. 
     Embodiments Implementations 
     Some example implementations of the subject matter are listed below. 
     In accordance with a first aspect, there is provided a method of managing computing resources. The method comprises: receiving a first request for using a target number of computing resources in a set of computing resources, at least one free computing resource of the set of computing resources being organized into at least one free resource group; determining whether a free matching resource group with the target number of computing resources is present in the at least one free resource group; in response to the free matching resource group being absent from the at least one free resource group, determining whether a free redundant resource group is present in the at least one free resource group, a number of resources in the free redundant resource group being greater than the target number; and in response to the free redundant resource group being present in the at least one free resource group, allocating the target number of computing resources for the first request by splitting the free redundant resource group. 
     In some implementations, the method further comprises: organizing the at least one free computing resource into the at least one free resource group based on a multi-level topology corresponding to the set of computing resources, such that each free resource group includes computing resources associated with a same node in the multi-level topology, a node in the multi-level topology corresponding to one of the set of computing resources or a connection component for multiple computing resources in the set of computing resources. 
     In some implementations, the computing resource comprises a graphics processing unit, and the multi-level topology comprises at least two of: a first level, comprising a node corresponding to an individual graphics processing unit; a second level, comprising a node corresponding to a PCIe switch for connecting a plurality of graphics processing units; a third level, comprising a node corresponding to a CPU socket for connecting a plurality of PCIe switches; and a fourth level, comprising a node corresponding to a computing device for connecting a plurality of CPU sockets. 
     In some implementations, allocating the target number of computing resources for the first request by splitting the free redundant resource group comprises: splitting the free redundant resource group into a first resource group and at least one second resource group, the first resource group including the target number of computing resources; and allocating computing resources from the first resource group for the first request. 
     In some implementations, the method further comprises: in response to completion of the first request, marking the first resource group as free; and in response to determining that all of computing resources in the at least one second resource group are free, merging the first resource group and the at least one second resource group into a new free resource group. 
     In some implementations, the method further comprises: in response to determining that the free redundant resource group is absent from the at least one free resource group, determining whether a priority of the first request exceeds a priority threshold; and in response to the priority exceeding the priority threshold, allocating, for the first request, the target number of computing resources including at least one available computing resource from the set of computing resources, the available computing resources including a free computing resource and a candidate computing resource allocated to a second request with a priority lower than or equal to the priority threshold. 
     In some implementations, the at least one available computing resource is organized into at least one available resource group, and wherein allocating for the first request the target number of computing resources including at least one available computing resource from the set of computing resources comprises: determining whether an available matching resource group with the target number of computing resources is present in the at least one available resource group; in response to the available matching resource group being present in the at least one available resource group, reclaiming a computing resource that has been allocated in the available matching resource group; and allocating computing resources from the available matching resource group for the first request. 
     In some implementations, allocating for the first request the target number of computing resources including at least one available computing resource from the set of computing resources comprises: in response to the available matching resource group being absent from the at least one available resource group, determining whether an available redundant resource group is present in the at least one available resource group, a number of resources in the available redundant resource group being greater than the target number; and in response to determining that the available redundant resource group is present in the at least one available resource group, allocating the target number of computing resources for the first request by splitting the available redundant resource group. 
     In some implementations, the method comprises: determining a first number of computing resources in a resource group that a first tenant associated with the first request has used; and in response to determining that a sum of the target number and the first number exceeds an upper limit of a number of computing resources corresponding to the first tenant, setting a priority of the first request to be lower than a priority threshold. 
     In some implementations, the upper limit of the number of computing resources corresponding to the first tenant is equal to a sum of a second number of computing resources pre-allocated for the first tenant and a third number of computing resources obtained by exchanging with a second tenant. 
     In accordance with a second aspect, there is provided a device. The device comprising: a processing unit; and a memory coupled to the processing unit and comprising instructions stored thereon which, when executed by the processing unit, cause the device to perform acts of: receiving a first request for using a target number of computing resources in a set of computing resources, at least one free computing resource of the set of computing resources being organized into at least one free resource group; determining whether a free matching resource group with the target number of computing resources is present in the at least one free resource group; free matching resource group being absent from the at least one free resource group, determining whether a free redundant resource group is present in the at least one free resource group, a number of resources in the free redundant resource group being greater than the target number; and in response to the free redundant resource group being present in the at least one free resource group, allocating the target number of computing resources for the first request by splitting the free redundant resource group. 
     In some implementations, the acts further comprises: organizing the at least one free computing resource into the at least one free resource group based on a multi-level topology corresponding to the set of computing resources, such that each free resource group includes computing resources associated with a same node in the multi-level topology, a node in the multi-level topology corresponding to one of the set of computing resources or a connection component for multiple computing resources in the set of computing resources. 
     In some implementations, the computing resource comprises a graphics processing unit, and the multi-level topology comprises at least two of: a first level, comprising a node corresponding to an individual graphics processing unit; a second level, comprising a node corresponding to a PCIe switch for connecting a plurality of graphics processing units; a third level, comprising a node corresponding to a CPU socket for connecting a plurality of PCIe switches; and a fourth level, comprising a node corresponding to a computing device for connecting a plurality of CPU sockets. 
     In some implementations, allocating the target number of computing resources for the first request by splitting the free redundant resource group comprises: splitting the free redundant resource group into a first resource group and at least one second resource group, the first resource group including the target number of computing resources; and allocating computing resources from the first resource group for the first request. 
     In some implementations, the acts further comprises: in response to completion of the first request, marking the first resource group as free; and in response to determining that all of computing resources in the at least one second resource group are free, merging the first resource group and the at least one second resource group into a new free resource group. 
     In some implementations, the acts further comprises: in response to determining that the free redundant resource group is absent from the at least one free resource group, determining whether a priority of the first request exceeds a priority threshold; and in response to the priority exceeding the priority threshold, allocating, for the first request, the target number of computing resources including at least one available computing resource from the set of computing resources, the available computing resources including a free computing resource and a candidate computing resource allocated to a second request with a priority lower than or equal to the priority threshold. 
     In some implementations, the at least one available computing resource is organized into at least one available resource group, and wherein allocating for the first request the target number of computing resources including at least one available computing resource from the set of computing resources comprises: determining whether an available matching resource group with the target number of computing resources is present in the at least one available resource group; in response to the available matching resource group being present in the at least one available resource group, reclaiming a computing resource that has been allocated in the available matching resource group; and allocating computing resources from the available matching resource group for the first request. 
     In some implementations, allocating for the first request the target number of computing resources including at least one available computing resource from the set of computing resources comprises: in response to the available matching resource group being absent from the at least one available resource group, determining whether an available redundant resource group is present in the at least one available resource group, a number of resources in the available redundant resource group being greater than the target number; and in response to determining that the available redundant resource group is present in the at least one available resource group, allocating the target number of computing resources for the first request by splitting the available redundant resource group. 
     In some implementations, the acts further comprises: determining a first number of computing resources in a resource group that a first tenant associated with the first request has used; and in response to determining that a sum of the target number and the first number exceeds an upper limit of a number of computing resources corresponding to the first tenant, setting a priority of the first request to be lower than a priority threshold. 
     In some implementations, the upper limit of the number of computing resources corresponding to the first tenant is equal to a sum of a second number of computing resources pre-allocated for the first tenant and a third number of computing resources obtained by exchanging with a second tenant. 
     In accordance with a third aspect, there is provided a computer program product being tangibly stored in a non-transitory computer storage medium and comprising machine executable instructions which, when executed by a device, cause the device to perform any method according to the first aspect. 
     In accordance with a fourth aspect, there is provided a computer-readable medium stored thereon with machine-executable instructions which, when executed by a device, cause the device to perform the method according to the first aspect. 
     The functionally described herein can be performed, at least in part, by one or more hardware logic components For example, and without limitation, illustrative types of hardware logic components that can be used include Field-Programmable Gate Arrays (FPGAs), Application-specific Integrated Circuits (ASICs), Application-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), and the like. 
     Program code for carrying out methods of the subject matter described herein may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowcharts and/or block diagrams to be implemented. The program code may execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server. 
     In the context of this disclosure, a machine-readable medium may be any tangible medium that may contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include but not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium would include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random-access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. 
     Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are contained in the above discussions, these should not be construed as limitations on the scope of the subject matter described herein, but rather as descriptions of features that may be specific to particular implementations. Certain features that are described in the context of separate implementations may also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation may also be implemented in multiple implementations separately or in any suitable sub-combination. 
     Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter specified in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.