Patent · US Active

Scheduling processing of machine learning tasks on heterogeneous compute circuits

US11561826B1 · kind B1 · utility

2Cited by
0References
20Claims
0Family size

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Key dates

Filing dateNov 12, 2020
Grant dateJan 24, 2023
Priority date
Expiry dateJul 7, 2041

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06F2209/509
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

Scheduling work of a machine learning application includes instantiating kernel objects by a computer processor in response to input of kernel definitions. Each kernel object is of a kernel type indicating a compute circuit. The computer processor generates a graph in a memory. Each node represents a task and specifies an assignment of the task to one or more of the kernel objects, and each edge represents a data dependency. Task queues are created in the memory and assigned to queue tasks represented by the nodes. Kernel objects are assigned to the task queues, and the tasks are enqueued by threads executing the kernel objects, based on assignments of the kernel objects to the task queues and assignments of the tasks to the kernel objects. Tasks are dequeued by the threads, and the compute circuits are activated to initiate processing of the dequeued tasks.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.