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- W4221095718 abstract "Prefetching which predicts future memory accesses and preloads them from main memory, is a widely-adopted technique to overcome the processor-memory performance gap. Unfortunately, hardware prefetchers implemented in today's processors cannot identify complex and irregular memory access patterns exhibited by modern data-driven applications and hence developers need to rely on software prefetching techniques. We investigate the challenges of enabling effective, automated software data prefetching. Our investigation reveals that the state-of-the-art compiler-based prefetching mechanism falls short in achieving high performance due to its static nature. Based on this insight, we design APT-GET, a novel profile-guided technique that ensures prefetch timeliness by leveraging dynamic execution time information. APT-GET leverages efficient hardware support such as Intel's Last Branch Record (LBR), for collecting application execution profiles with negligible overhead to characterize the execution time of loads. APT-GET then introduces a novel analytical model to find the optimal prefetch-distance and prefetch injection site based on the collected profile to enable timely prefetches. We study APT-GET in the context of 10 real-world applications and demonstrate that it achieves a speedup of up to 1.98× and of 1.30× on average. By ensuring prefetch timeliness, APT-GET improves the performance by 1.25× over the state-of-the-art software data prefetching mechanism." @default.
- W4221095718 created "2022-04-03" @default.
- W4221095718 creator A5002126571 @default.
- W4221095718 creator A5050964144 @default.
- W4221095718 creator A5057534738 @default.
- W4221095718 creator A5075674776 @default.
- W4221095718 creator A5090689004 @default.
- W4221095718 date "2022-03-28" @default.
- W4221095718 modified "2023-10-16" @default.
- W4221095718 title "APT-GET" @default.
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