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Family of Sporadic Prefetching Algorithms Based on the Distance Function

Student: Voevodkin Vadim

Supervisor: Valery A. Kalyagin

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Data Mining (Master)

Final Grade: 10

Year of Graduation: 2024

Modern storage systems intensively utilize data prefetching algorithms while processing sequences of the read requests. Performance of the prefetchingalgorithm (for instance increase of the cache hit ratio of the cache system – CHR) directly affects overall performance characteristics of the storage system (read latency, IOPS, etc.). There are widely known prefetching algorithms that are focused on the discovery of the sequential patterns in the stream of requests. This study examines a family of prefetching algorithms that is focused on mining of the pseudo random (sporadic) patterns between read requests – sporadic prefetching algorithms. The key contribution of this paper is that it discovers a new, lightweight family of distance-based sporadic prefetching algorithms (DBSP) that outperforms the best previously known results on MSR traces collection.Another important contribution of this paper is a thorough description of the procedure for comparing the performance of sporadic prefetchers.

Full text (added May 29, 2024)

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