Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

  • Zhang, P
  • Fang, J
  • Yang, C
  • Huang, C
  • Tang, T
  • Wang, Z
View in ORKG
Publication date
March 2020
Publisher
Institute of Electrical and Electronics Engineers (IEEE)

Abstract

As many-core accelerators keep integrating more processing units, it becomes increasingly more difficult for a parallel application to make effective use of all available resources. An effective way for improving hardware utilization is to exploit spatial and temporal sharing of the heterogeneous processing units by multiplexing computation and communication tasks - a strategy known as heterogeneous streaming. Achieving effective heterogeneous streaming requires carefully partitioning hardware among tasks, and matching the granularity of task parallelism to the resource partition. However, finding the right resource partitioning and task granularity is extremely challenging, because there is a large number of possible solutions and the opti...

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