ParIS: The Next Destination for Fast Data Series Indexing and Query Answering

Abstract

We propose ParIS, the first disk-based data series index that inherently takes advantage of modern hardware parallelization, in order to accelerate processing times. Our experimental results demonstrate that ParIS completely removes the CPU latency during index construction for disk-resident data. In terms of exact query answering, ParIS is more than 2 orders of magnitude faster than the current state of the art index scan method, and more than 3 orders of magnitude faster than the optimized serial scan method. ParIS owes its efficiency not only to the effective use of multi-core and multi-socket architectures, in order to distribute and execute in parallel both index construction and query answering, but also to the exploitation of the Single Instruction Multiple Data (SIMD) capabilities of modern CPUs, in order to further parallelize the execution of individual instructions inside each core.