Abstract: Embodiments of the present disclosure provide a method and device for data center management. For example, there is provided a method, comprising: obtaining information of hardware used in a data center, the information of the hardware including identification information describing an identifiable attribute of the hardware; identifying the hardware by matching the identification information with a resource profile, the resource profile recording identifiable attributes of a plurality of types of hardware; and updating a record associated with the hardware in a database of the data center using the obtained information. Corresponding device and computer program product are also provided.

Abstract: Systems and methods are provided to implement intelligent data coordination for accelerated computing in a distributed computing environment. For example, a method includes executing a task on a computing node, monitoring requests issued by the executing task, intercepting requests issued by the executing task which correspond to data flow operations to be performed as part of the task execution, and asynchronously executing the intercepted requests at scheduled times to coordinate data flow between resources on the computing node.

Abstract: A method for managing container images in a container hosting environment, comprising a set of machine nodes for hosting container images, comprises the following steps. At a machine node of the set of machine nodes, at least one image layer of a container image comprising multiple image layers is identified for compaction. The identified image layer is compacted by merging data of the identified layer with data of another image layer of the container image. The data of the compacted image layer is transmitted to a backup store remote from the machine node for storage. The set of machine nodes and the backup store are implemented via processing devices operatively coupled via a communication network to form the container hosting environment. The compacted image layer may then be recovered from the backup store.

Abstract: A graphics processing unit (GPU) service platform includes a control server, and a cluster of GPU servers each having one or more GPU devices. The control server receives a service request from a client system for GPU processing services, allocates multiple GPU servers within the cluster to handle GPU processing tasks specified by the service request by logically binding the allocated GPU servers, and designating one of the at least two GPU servers as a master server, and send connection information to the client system to enable the client system to connect to the master server. The master GPU server receives a block of GPU program code transmitted from the client system, which is associated with the GPU processing tasks specified by the service request, processes the block of GPU program code using the GPU devices of the logically bound GPU servers, and returns processing results to the client system.

Abstract: A graphics processing unit (GPU) service platform includes a control server, and a cluster of GPU servers each having one or more GPU devices. The control server receives a service request from a client system for GPU processing services, allocates multiple GPU servers within the cluster to handle GPU processing tasks specified by the service request by logically binding the allocated GPU servers, and designating one of the at least two GPU servers as a master server, and send connection information to the client system to enable the client system to connect to the master server. The master GPU server receives a block of GPU program code transmitted from the client system, which is associated with the GPU processing tasks specified by the service request, processes the block of GPU program code using the GPU devices of the logically bound GPU servers, and returns processing results to the client system.

Abstract: A container image registry is maintained at each host device in a set of host devices in a container hosting environment. A container image is composed of one or more container image layers such that each container image registry of each host device is configured to be able to store one or more different layers of one or more different container images. The method tracks which container image registry at which host device contains which container image layers. At each host device, one or more container images are obtained for launching one or more application programs. For a given host device, the one or more container images are obtained from one or more of: (i) one or more container image layers stored in its container image registry; and (ii) one or more container image layers stored in the container image registry of another host device.

Abstract: Techniques are provided to configure a graphics processing unit (GPU) service platform to provide GPU processing and checkpointing services to a client system. For example, when the GPU service platform receives a service request from a first client system for GPU processing services, a GPU server node is allocated to execute a first GPU processing task associated with the service request using one or more GPU devices. When a GPU checkpointing operation is performed during execution of the first GPU processing task to generate a checkpoint image of a current state of the first GPU processing task, the GPU server node is configured to execute at least a portion of a second GPU processing task associated with a second service request received from a second client system, using the one or more GPU devices concurrently with performing the GPU checkpointing operation for the first GPU processing task.

Abstract: A graphics processing unit (GPU) service platform includes a control server, and a cluster of GPU servers each having one or more GPU devices. The control server receives a service request from a client system for GPU processing services, allocates multiple GPU servers nodes within the cluster to handle GPU processing tasks specified by the service request by logically binding the allocated GPU server nodes, and designating one of the at least two GPU servers as a master server, and send connection information to the client system to enable the client system to connect to the master server. The master GPU server node receives a block of GPU program code transmitted from the client system, which is associated with the GPU processing tasks specified by the service request, processes the block of GPU program code using the GPU devices of the logically bound GPU servers, and returns processing results to the client system.

Abstract: A method implemented by a server enables sharing of GPU resources by multiple clients. The server receives a request from a first client for GPU services. The request includes a first block of GPU code of an application executing on the first client. A first task corresponding to the first block of GPU code is enqueued in a task queue. The task queue includes a second task that corresponds to a second block of GPU code of an application executing on a second client. The server schedules a time for executing the first task using a GPU device that is assigned to the first client, and dispatches the first task to a GPU worker process to execute the first task at the scheduled time using the GPU device. The GPU device is shared, either temporally or spatially, by the first and second clients for executing the first and second tasks.

Abstract: Embodiments of the present disclosure provide a method and device for data center management. For example, there is provided a method, comprising: obtaining information of hardware used in a data center, the information of the hardware including identification information describing an identifiable attribute of the hardware; identifying the hardware by matching the identification information with a resource profile, the resource profile recording identifiable attributes of a plurality of types of hardware; and updating a record associated with the hardware in a database of the data center using the obtained information. Corresponding device and computer program product are also provided.