WASP: Selective Data Prefetching with Monitoring Runtime Warp Progress on GPUs

This paper proposes a new data prefetching technique for Graphics Processing Units (GPUs) called Warp Aware Selective Prefetching (WASP). The main idea of WASP is to dynamically select warps whose progress is slower than that of the current warp as prefetching target warps. Under the in-order instru...

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Bibliographic Details
Published in:IEEE transactions on computers 2018-09, Vol.67 (9), p.1366-1373
Main Authors: Oh, Yunho, Yoon, Myung Kuk, Park, Jong Hyun, Park, Yongjun, Ro, Won Woo
Format: Article
Language:English
Subjects:
cache performance
data prefetching
Dynamic loads
GPGPU
Graphics processing units
Hardware
Message systems
Micromechanical devices
Monitoring
Prefetching
Warp
warp scheduling
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Summary:This paper proposes a new data prefetching technique for Graphics Processing Units (GPUs) called Warp Aware Selective Prefetching (WASP). The main idea of WASP is to dynamically select warps whose progress is slower than that of the current warp as prefetching target warps. Under the in-order instruction execution model of GPUs, these prefetching target warps will certainly execute the same load as the current warp. Exploiting that, WASP prefetches the data for prefetching target warps, which allows the prefetched data to be accurately accessed. To simply verify the progress of the warps, WASP monitors the counts of the dynamic load executions for all warps. When a warp executes a load, WASP searches the warps with lower load execution counts than the current warp and generates the prefetch requests for them. In our evaluation, WASP achieves a 16.8 percent speedup compared to the baseline GPU.
ISSN:0018-9340
1557-9956
DOI:10.1109/TC.2018.2813379