Intel Corporation

Chunling Hu

Justin E Gottschlich

Tatiana Shpeisman

Rajkishore Barik

Jack Liu

A dynamic runtime scheduling system includes task manager circuitry capable of detecting a correspondence in at least a portion of the output arguments from one or more first tasks with at least a portion of the input arguments to one or more second tasks. Upon detecting the output arguments from the first task represents a superset of the second task input arguments, the task manager circuitry apportions the first task into a plurality of new subtasks. At least one of the new subtasks includes output arguments having a 1:1 correspondence to the second task input arguments. Upon detecting the output arguments from an first task represents a subset of the second task input arguments, the task manager circuitry may autonomously apportion the second task into a plurality of new subtasks. At least one of the new subtasks may include input arguments having a 1:1 correspondence to first task output arguments.

Dynamic runtime task management

A machine learning technique is used to improve dynamic prediction of processor utilization for multi-threaded user-level applications in a dynamic run-time environment based on processor utilization history. Processor supply voltage and processor clock frequency may be dynamically scaled based on the predicted processor utilization in order to reduce processor power consumption.

Growing community of inventors

San Jose, CA, United States of America

Chunling Hu