sponsored byACMIEEE The International Conference for High Performance 
Computing, Networking, Storage and Analysis
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SCHEDULE: NOV 15-20, 2015

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Runtime-Driven Shared Last-Level Cache Management for Task-Parallel Programs

SESSION: Cache and Memory Subsystems


EVENT TAG(S): Architectures

TIME: 10:30AM - 11:00AM

SESSION CHAIR(S): Sunita Chandrasekaran

AUTHOR(S):Abhisek Pan, Vijay S. Pai



Task-parallel programming models with input annotation-based concurrency extraction at runtime present a promising paradigm for programming multicore processors. Through management of dependencies, task assignments, and orchestration, these models markedly simplify the programming effort for parallelization while exposing higher levels of concurrency.

In this paper we show that for multicores with a shared last-level cache (LLC), the concurrency extraction framework can be used to improve the shared LLC performance. Based on the input annotations for future tasks, the runtime instructs the hardware to prioritize data blocks with future reuse while evicting blocks with no future reuse. These instructions allow the hardware to preserve all the blocks for at least some of the future tasks and evict dead blocks. This leads to a considerable improvement in cache efficiency over what is achieved by hardware-only replacement policies, which can replace blocks for all future tasks resulting in poor hit-rates for all future tasks.

Chair/Author Details:

Sunita Chandrasekaran (Chair) - University of Delaware|

Abhisek Pan - Purdue University

Vijay S. Pai - Purdue University

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Paper provided by the ACM Digital Library

Paper also available from IEEE Computer Society