%0 Conference Proceedings
%T A Compilation and Run-Time Framework for Maximizing Performance of Self-scheduling Algorithms
%+ Beijing Institute of Technology (BIT)
%+ University of California [Irvine] (UC Irvine)
%+ Qualcomm Research
%A Wang, Yizhuo
%A Beni, Laleh, Aghababaie
%A Nicolau, Alexandru
%A Veidenbaum, Alexander, V.
%A Cammarota, Rosario
%Z Part 4: Applications of Parallel and Distributed Computing
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 11th IFIP International Conference on Network and Parallel Computing (NPC)
%C Ilan, Taiwan
%Y Ching-Hsien Hsu
%Y Xuanhua Shi
%Y Valentina Salapura
%I Springer
%3 Network and Parallel Computing
%V LNCS-8707
%P 459-470
%8 2014-09-18
%D 2014
%R 10.1007/978-3-662-44917-2_38
%K loop scheduling
%K self-scheduling
%K random forest
%Z Computer Science [cs]Conference papers
%X Ordinary programs contain many parallel loops which account for a significant portion of these programs’ completion time. The parallel executions of such loops can significantly speedup performance of modern multi-core systems. We propose a new framework - Locality Aware Self-scheduling (LASS) - for scheduling parallel loops to multi-core systems and boost up performance of known self-scheduling algorithms in diverse execution conditions. LASS enforces data locality, by forcing the execution of consecutive chunks of iterations to the same core, and favours load balancing with the introduction of a work-stealing mechanism. LASS is evaluated on a set of kernels on a multi-core system with 16 cores. Two execution scenarios are considered. In the first scenario our application runs alone on top of the operating system. In the second scenario our application runs in conjunction with an interfering parallel job. The average speedup achieved by LASS for first execution scenario is 11% and for the second one is 31%.
%G English
%Z TC 10
%Z WG 10.3
%2 https://inria.hal.science/hal-01403116/document
%2 https://inria.hal.science/hal-01403116/file/978-3-662-44917-2_38_Chapter.pdf
%L hal-01403116
%U https://inria.hal.science/hal-01403116
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-LNCS-8707
%~ IFIP-TC10
%~ IFIP-NPC
%~ IFIP-WG10-3