TY - GEN
T1 - Code restructuring for improving cache performance of MPSoCs
AU - Chen, G.
AU - Kandemir, Mahmut
PY - 2005
Y1 - 2005
N2 - One of the critical goals in code optimization for MPSoC architectures is to minimize the number of off-chip memory accesses. This is because such accesses can be extremely costly from both performance and power angles. While conventional data locality optimization techniques can be used for improving data access pattern of each processor independently, such techniques usually do not consider locality for shared data. This paper proposes a strategy that reduces the number of off-chip references due to shared data. It achieves this goal by restructuring a parallelized application code in such a fashion that a given data block is accessed by parallel processors within the same time frame, so that its reuse is maximized while it is in the on-chip memory space. This tends to minimize the number of off-chip references since the accesses to a given data block are clustered within a short period of time during execution. Our approach employs a polyhedral tool that helps us isolate computations that manipulate a given data block.
AB - One of the critical goals in code optimization for MPSoC architectures is to minimize the number of off-chip memory accesses. This is because such accesses can be extremely costly from both performance and power angles. While conventional data locality optimization techniques can be used for improving data access pattern of each processor independently, such techniques usually do not consider locality for shared data. This paper proposes a strategy that reduces the number of off-chip references due to shared data. It achieves this goal by restructuring a parallelized application code in such a fashion that a given data block is accessed by parallel processors within the same time frame, so that its reuse is maximized while it is in the on-chip memory space. This tends to minimize the number of off-chip references since the accesses to a given data block are clustered within a short period of time during execution. Our approach employs a polyhedral tool that helps us isolate computations that manipulate a given data block.
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U2 - 10.1109/ICCAD.2005.1560076
DO - 10.1109/ICCAD.2005.1560076
M3 - Conference contribution
AN - SCOPUS:33751425420
SN - 078039254X
SN - 9780780392540
T3 - IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
SP - 271
EP - 274
BT - Proceedings of theICCAD-2005
T2 - ICCAD-2005: IEEE/ACM International Conference on Computer-Aided Design, 2005
Y2 - 6 November 2005 through 10 November 2005
ER -