ParIS+: Data Series Indexing on Multi-Core Architectures

09/01/2020
by   Botao Peng, et al.
0

Data series similarity search is a core operation for several data series analysis applications across many different domains. Nevertheless, even state-of-the-art techniques cannot provide the time performance required for large data series collections. We propose ParIS and ParIS+, the first disk-based data series indices carefully designed to inherently take advantage of multi-core architectures, in order to accelerate similarity search processing times. Our experiments demonstrate that ParIS+ completely removes the CPU latency during index construction for disk-resident data, and for exact query answering is up to 1 order of magnitude faster than the current state of the art index scan method, and up to 3 orders of magnitude faster than the optimized serial scan method. ParIS+ (which is an evolution of the ADS+ index) owes its efficiency 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, and to the exploitation of the Single Instruction Multiple Data (SIMD) capabilities of modern CPUs, in order to further parallelize the execution of instructions inside each core.

READ FULL TEXT
research
09/02/2020

MESSI: In-Memory Data Series Indexing

Data series similarity search is a core operation for several data serie...
research
12/26/2022

Hercules Against Data Series Similarity Search

We propose Hercules, a parallel tree-based technique for exact similarit...
research
12/21/2020

Parallel Index-Based Structural Graph Clustering and Its Approximation

SCAN (Structural Clustering Algorithm for Networks) is a well-studied, w...
research
02/26/2018

Adaptive Geospatial Joins for Modern Hardware

Geospatial joins are a core building block of connected mobility applica...
research
06/20/2020

Coconut: sortable summarizations for scalable indexes over static and streaming data series

Many modern applications produce massive streams of data series that nee...
research
04/17/2023

Dumpy: A Compact and Adaptive Index for Large Data Series Collections

Data series indexes are necessary for managing and analyzing the increas...
research
06/20/2020

Coconut: a scalable bottom-up approach for building data series indexes

Many modern applications produce massive amounts of data series that nee...

Please sign up or login with your details

Forgot password? Click here to reset