Sparse data applications have irregular access patterns that stymie modern memory architectures. Although hyper-sparse workloads have received considerable attention in the past, moderately-sparse workloads prevalent in machine learning applications, graph processing and HPC have not. Where the former can bypass the cache hierarchy, the latter fit in the cache. This article makes the observation that intelligent, near-processor cache management can improve bandwidth utilization for data-irregular accesses, thereby accelerating moderately-sparse workloads. We propose SortCache, a processor-centric approach to accelerating sparse workloads by introducing accelerators that leverage the on-chip cache subsystem, with minimal programmer intervention.
CITATION STYLE
Srikanth, S., Jain, A., Conte, T. M., Debenedictis, E. P., & Cook, J. (2021). SortCache: Intelligent Cache Management for Accelerating Sparse DataWorkloads. ACM Transactions on Architecture and Code Optimization, 18(4). https://doi.org/10.1145/3473332
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