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arXiv · 2607.25363

CW-Ghost: Search-Free Granularity Selection for Helper-Thread Prefetching via Capacity Windows

Ya Zhang·Tong Lei·Yao Chen·Yonggang Che·Chuanfu Xu·Haozhong Qiu·Yusong Tan
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Abstract

Helper-thread prefetching hides the latency of irregular memory accesses by executing address dependency chains ahead of the main thread. However, its effectiveness depends on the range of future iterations covered by the helper thread. A fixed coverage range cannot consistently accommodate different workloads and processors, whereas exhaustively evaluating candidate configurations incurs substantial configuration cost. This paper presents CW-Ghost, which uses a single offline profiling run to estimate the average demand cache line fill volume generated per target iteration in a target region. CW-Ghost combines this estimate with a cache capacity budget to derive a Capacity Window, which determines the iteration granularity of each prefetch chunk. In addition, bounded chunk-level synchronization limits the number of chunks by which the helper thread may run ahead of the main thread. Across 14 workload instances evaluated on Intel and AMD CPU platforms, CW-Ghost achieves geometric mean speedups of 1.54x and 1.33x, respectively, over the original programs. Compared with Ghost Threading, it improves geometric mean performance by 15.8% and 10.8%, respectively, while achieving more than 99% of the empirically optimal performance within the candidate set on both platforms. These results demonstrate that cache capacity constraints can effectively guide the selection of granularity for helper-thread prefetching.

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Ya Zhang, Tong Lei, Yao Chen, Yonggang Che, Chuanfu Xu, Haozhong Qiu, Yusong Tan. 2026-07-28. CW-Ghost: Search-Free Granularity Selection for Helper-Thread Prefetching via Capacity Windows. https://arxiv.org/abs/2607.25363

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