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Previous research addressed the potential problems of the hard-disk orienteddesign of DBMSs of flashSSDs. In this paper, we focus on exploiting potentialbenefits of flashSSDs. First, we examine the internal parallelism issues offlashSSDs by conducting benchmarks to various flashSSDs. Then, we suggestalgorithm-design principles in order to best benefit from the internalparallelism. We present a new I/O request concept, called psync I/O that canexploit the internal parallelism of flashSSDs in a single process. Based onthese ideas, we introduce B+-tree optimization methods in order to utilizeinternal parallelism. By integrating the results of these methods, we present aB+-tree variant, PIO B-tree. We confirmed that each optimization methodsubstantially enhances the index performance. Consequently, PIO B-tree enhancedB+-tree's insert performance by a factor of up to 16.3, while improvingpoint-search performance by a factor of 1.2. The range search of PIO B-tree wasup to 5 times faster than that of the B+-tree. Moreover, PIO B-treeoutperformed other flash-aware indexes in various synthetic workloads. We alsoconfirmed that PIO B-tree outperforms B+-tree in index traces collected insidethe Postgresql DBMS with TPC-C benchmark.

B+-tree Index Optimization by Exploiting Internal Parallelism of Flash-based Solid State Drives