NDLI: Adaptive Cache and Concurrency Allocation on GPGPUs

Content Provider	IEEE Xplore Digital Library
Author	Zhong Zheng Zhiying Wang Lipasti, M.
Copyright Year	2002
Abstract	Memory bandwidth is critical to GPGPU performance. Exploiting locality in caches can better utilize memory bandwidth. However, memory requests issued by excessive threads cause cache thrashing and saturate memory bandwidth, degrading performance. In this paper, we propose adaptive cache and concurrency allocation (CCA) to prevent cache thrashing and improve the utilization of bandwidth and computational resources, hence improving performance. According to locality and reuse distance of access patterns in GPGPU program, warps on a stream multiprocessor are dynamically divided into three groups: cached, bypassed, and waiting. The data cache accommodates the footprint of cached warps. Bypassed warps cannot allocate cache lines in the data cache to prevent cache thrashing, but are able to take advantage of available memory bandwidth and computational resource. Waiting warps are de-scheduled. Experimental results show that adaptive CCA can significant improve benchmark performance, with 80 percent harmonic mean IPC improvement over the baseline.
Sponsorship	IEEE Computer Society
Starting Page	90
Ending Page	93
Page Count	4
File Size	594802
File Format	PDF
ISSN	15566056
Volume Number	14
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bandwidth Resource management Instruction sets Concurrent computing Benchmark testing Cache memory concurrency GPGPU cache
Content Type	Text
Resource Type	Article
Subject	Hardware and Architecture

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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