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Efficient Code Assignment Techniques for Local Memory on Software Managed Multicores

Efficient Code Assignment Techniques for Local Memory on Software Managed Multicores Efficient Code Assignment Techniques for Local Memory on Software Managed Multicores JING LU, KE BAI, and AVIRAL SHRIVASTAVA, Arizona State University Scaling the memory hierarchy is a major challenge when we scale the number of cores in a multicore processor. Software Managed Multicore (SMM) architectures come up as one of the promising solutions. In an SMM architecture, there are no caches, and each core has only a local scratchpad memory [Banakar et al. 2002]. As the local memory usually is small, large applications cannot be directly executed on it. Code and data of the task mapped to each core need to be managed between global memory and local memory. This article solves the problem of efficiently managing code on an SMM architecture. The primary requirement of generating efficient code assignments is a correct management cost model. In this article, we address this problem by proposing a cost calculation graph. In addition, we develop two heuristics CMSM (Code Mapping for Software Managed multicores) and CMSM_advanced that result in efficient code management execution on the local scratchpad memory. Experimental results collected after executing applications from the MiBench suite [Guthaus et al. 2001] demonstrate that merely by adopting the correct management http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Embedded Computing Systems (TECS) Association for Computing Machinery

Efficient Code Assignment Techniques for Local Memory on Software Managed Multicores

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References (43)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2015 by ACM Inc.
ISSN
1539-9087
DOI
10.1145/2738039
Publisher site
See Article on Publisher Site

Abstract

Efficient Code Assignment Techniques for Local Memory on Software Managed Multicores JING LU, KE BAI, and AVIRAL SHRIVASTAVA, Arizona State University Scaling the memory hierarchy is a major challenge when we scale the number of cores in a multicore processor. Software Managed Multicore (SMM) architectures come up as one of the promising solutions. In an SMM architecture, there are no caches, and each core has only a local scratchpad memory [Banakar et al. 2002]. As the local memory usually is small, large applications cannot be directly executed on it. Code and data of the task mapped to each core need to be managed between global memory and local memory. This article solves the problem of efficiently managing code on an SMM architecture. The primary requirement of generating efficient code assignments is a correct management cost model. In this article, we address this problem by proposing a cost calculation graph. In addition, we develop two heuristics CMSM (Code Mapping for Software Managed multicores) and CMSM_advanced that result in efficient code management execution on the local scratchpad memory. Experimental results collected after executing applications from the MiBench suite [Guthaus et al. 2001] demonstrate that merely by adopting the correct management

Journal

ACM Transactions on Embedded Computing Systems (TECS) – Association for Computing Machinery

Published: Dec 8, 2015

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