Litcius/Paper detail

Tile-based Lightweight Integer Compression in GPU

Anil Shanbhag, Bobbi Yogatama, Xiangyao Yu, Samuel Madden

2022Proceedings of the 2022 International Conference on Management of Data34 citationsDOIOpen Access PDF

Abstract

GPUs are increasingly used for high-performance and interactive data analytics workloads due to their capability to accelerate computation using massive parallelism. A key constraint of GPU-based data analytics today is the limited memory capacity in GPU devices.

Topics & Concepts

Computer scienceParallel computingAnalyticsCUDAComputationTileGeneral-purpose computing on graphics processing unitsParallelism (grammar)Key (lock)Constraint (computer-aided design)Data compressionInteger (computer science)Computer architectureComputational scienceOperating systemDatabaseGraphicsAlgorithmArtEngineeringMechanical engineeringVisual artsAlgorithms and Data CompressionParallel Computing and Optimization TechniquesAdvanced Data Storage Technologies