Locality-Aware Task Management for Unstructured Parallelism: A Quantitative Limit Study

Provided by: Association for Computing Machinery
Topic: Hardware
Format: PDF
In this paper, the authors increase the number of cores on a processor die, the on-chip cache hierarchies that support these cores are getting larger, deeper, and more complex. As a result, non-uniform memory access effects are now prevalent even on a single chip. To reduce execution time and energy consumption, data access locality should be exploited. This is especially important for task-based programming systems, where a scheduler decides when and where on the chip the code segments, i.e., tasks, should execute.

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