Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/71844
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Type: Conference paper
Title: Dynamic thread partition algorithm based on sharing data on CMP
Author: Zhou, D.
Tian, Y.
Shen, H.
Citation: Proceedings of the 12th International Conference on Parallell and Distributed Computing, Applications and Technologies, held in Gwangju, South Korea, 20-22 October, 2011: pp.122-127
Publisher: IEEE
Publisher Place: USA
Issue Date: 2011
ISBN: 9781457718076
Conference Name: International Conference on Parallel and Distributed Computing, Applications and Technologies (12th : 2011 : Gwangju, South Korea)
Statement of
Responsibility: 
Deng Zhou, Ye Tian, Hong Shen
Abstract: At the level of multi-core processors that share the same cache, data sharing among threads which belong to different cores may not enjoy the benifit of non-uniform cache access because it is difficult to determine which core should be set as the local position of data block while each cache block is setting as one of the core's local block. Studies have found that the cost of long latency access can be reduced by using a proper thread partition/allocation algorithm [5]. However, at present work, researchers pay little attention to thread partitioning algorithms which can reduce the cost of long latency access. In this paper, we present a dynamic thread partitioning algorithm according to data sharing among threads at the level of cache-shared-multicore processers. In our design, the algorithm makes the best effort to minimize shared block accessed by threads of different cores. Compared with the existing work, our new algorithm achieves a performance improvement. We perform experiments on 4 cores and more than 100 threads and the result show that our algorithm can reduce the interaction of threads belonging to different cores between 30% and 50% over the previously known solutions.
Keywords: Thread partition
On-chip latency
Multicore thread
Data sharing
Rights: © 2011 IEEE
DOI: 10.1109/PDCAT.2011.36
Published version: http://dx.doi.org/10.1109/pdcat.2011.36
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Computer Science publications

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