Invention Grant
- Patent Title: Managing workloads of a deep neural network processor
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Application No.: US16454026Application Date: 2019-06-26
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Publication No.: US11494237B2Publication Date: 2022-11-08
- Inventor: Chad Balling McBride , Amol A. Ambardekar , Boris Bobrov , Kent D. Cedola , George Petre , Larry Marvin Wall
- Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
- Applicant Address: US WA Redmond
- Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
- Current Assignee Address: US WA Redmond
- Agency: Newport IP, LLC
- Agent Leonard J. Hope
- Main IPC: G06F9/46
- IPC: G06F9/46 ; G06F9/50 ; G06N3/04

Abstract:
A computing system includes processor cores for executing applications that utilize functionality provided by a deep neural network (“DNN”) processor. One of the cores operates as a resource and power management (“RPM”) processor core. When the RPM processor receives a request to execute a DNN workload, it divides the DNN workload into workload fragments. The RPM processor then determines whether a workload fragment is to be statically allocated or dynamically allocated to a DNN processor. Once the RPM processor has selected a DNN processor, the RPM enqueues the workload fragment on a queue maintained by the selected DNN processor. The DNN processor dequeues workload fragments from its queue for execution. Once execution of a workload fragment has completed, the DNN processor generates an interrupt indicating that execution of the workload fragment has completed. The RPM processor can then notify the processor core that originally requested execution of the workload fragment.
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