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: Near-Storage Accelerator for High-Performance Log Analytics

Seongyoung Kang, Jiyoung An, Jinpyo Kim, Sang-Woo Jun

2021Year
9Citations
1Top-tier citations

Abstract

This paper presents, a log analytics platform with near-storage accelerators for high-performance, cost- and power-efficient unstructured log processing. offloads log analytics queries to an efficient near-storage FPGA implementation of a token querying engine, which can take advantage of the high internal bandwidth of storage devices within the available chip resource limitations. This engine is flexible enough to handle complex queries including template search based on user-defined tree-based template libraries, as well as concurrent execution of multiple queries. also uses a log-optimized version of a simple, high-throughput compression algorithm in order to further improve the effective bandwidth of backing storage.

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