Abstract: Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to determine options for decisions in connection with design features of a computing device. In a particular implementation, design options for two or more design decisions of neural network processing device may be identified based, at least in part, on combination of a definition of available computing resources and one or more predefined performance constraints.

Abstract: Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to select options for decisions in connection with design features of a computing device. In a particular implementation, design options for two or more design decisions of neural network processing device may be selected based, at least in part, on combination of function values that are computed based, at least in part, on a tensor expressing sample neural network weights.

Abstract: Embodiments of the present invention set forth techniques for allocating execution resources to groups of threads within a graphics processing unit. A compute work distributor included in the graphics processing unit receives an indication from a process that a first group of threads is to be launched. The compute work distributor determines that a first subcontext associated with the process has at least one processor credit. In some embodiments, CTAs may be launched even when there are no processor credits, if one of the TPCs that was already acquired has sufficient space. The compute work distributor identifies a first processor included in a plurality of processors that has a processing load that is less than or equal to the processor loads associated with all other processors included in the plurality of processors. The compute work distributor launches the first group of threads to execute on the first processor.

Abstract: A computer-implemented method of identifying a neural network for processing data includes: clustering a training dataset into a plurality of data clusters based on similarities in activation patterns generated in neurons of a teacher neural network in response to inputting the training dataset into the teacher neural network, training a student neural network for processing each of the plurality of data clusters, and providing a data classifier neural network for identifying one or more of the trained student neural networks to process data based on a data cluster of the data.

Abstract: Embodiments of the present invention set forth techniques for allocating execution resources to groups of threads within a graphics processing unit. A compute work distributor included in the graphics processing unit receives an indication from a process that a first group of threads is to be launched. The compute work distributor determines that a first subcontext associated with the process has at least one processor credit. In some embodiments, CTAs may be launched even when there are no processor credits, if one of the TPCs that was already acquired has sufficient space. The compute work distributor identifies a first processor included in a plurality of processors that has a processing load that is less than or equal to the processor loads associated with all other processors included in the plurality of processors. The compute work distributor launches the first group of threads to execute on the first processor.

Abstract: Embodiments of the present invention set forth techniques for allocating execution resources to groups of threads within a graphics processing unit. A compute work distributor included in the graphics processing unit receives an indication from a process that a first group of threads is to be launched. The compute work distributor determines that a first subcontext associated with the process has at least one processor credit. In some embodiments, CTAs may be launched even when there are no processor credits, if one of the TPCs that was already acquired has sufficient space. The compute work distributor identifies a first processor included in a plurality of processors that has a processing load that is less than or equal to the processor loads associated with all other processors included in the plurality of processors. The compute work distributor launches the first group of threads to execute on the first processor.

Abstract: Embodiments of the present invention set forth techniques for allocating execution resources to groups of threads within a graphics processing unit. A compute work distributor included in the graphics processing unit receives an indication from a process that a first group of threads is to be launched. The compute work distributor determines that a first subcontext associated with the process has at least one processor credit. In some embodiments, CTAs may be launched even when there are no processor credits, if one of the TPCs that was already acquired has sufficient space. The compute work distributor identifies a first processor included in a plurality of processors that has a processing load that is less than or equal to the processor loads associated with all other processors included in the plurality of processors. The compute work distributor launches the first group of threads to execute on the first processor.

Abstract: A method and apparatus for partitioning a shared cache of a chip multi-processor are described. In one embodiment, the method includes a request of a cache block from system memory if a cache miss within a shared cache is detected according to a received request from a processor. Once the cache block is requested, a victim block within the shared cache is selected according to a processor identifier and a request type of the received request. In one embodiment, selection of the victim block according to a processor identifier and request type is based on a partition of a set-associative, shared cache to limit the selection of the victim block from a subset of available cache ways according to the cache partition. Other embodiments are described and claimed.

Abstract: A method and apparatus for partitioning a shared cache of a chip multi-processor are described. In one embodiment, the method includes a request of a cache block from system memory if a cache miss within a shared cache is detected according to a received request from a processor. Once the cache block is requested, a victim block within the shared cache is selected according to a processor identifier and a request type of the received request. In one embodiment, selection of the victim block according to a processor identifier and request type is based on a partition of a set-associative, shared cache to limit the selection of the victim block from a subset of available cache ways according to the cache partition. Other embodiments are described and claimed.