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This project proposes a new way to take advantage of temporal locality to optimize TBN prefetching policy.

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yeojinia/gpu_tbntl_prefetcher

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1. Overview

We explore temporal locality using statistics to optimize original TBN prefetching(TBNp) policy implemented by NVIDIA CUDA drivers.

2. Performance Evaluation

We measure performance with Rodinia Benchmark http://www.cs.virginia.edu/rodinia/doku.php

3. Result

For SRAD we got a speedup of 15 percent in the unlimited memory case, and a speedup of 12 percent in the limited memory case compared to original TBNp. For other test case, there was no improvement.

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4. Contributors

Yeojin Kim, Josiah Blaisdell, SangYeon Lee

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This project proposes a new way to take advantage of temporal locality to optimize TBN prefetching policy.

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