ACM SIGMOD Record
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
The implementation and performance of compressed databases
ACM SIGMOD Record
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Super-Scalar RAM-CPU Cache Compression
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Integrating compression and execution in column-oriented database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
How to wring a table dry: entropy compression of relations and querying of compressed relations
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Data mining with the SAP NetWeaver BI accelerator
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Constant-Time Query Processing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Secondary indexing in one dimension: beyond b-trees and bitmap indexes
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
SIMD-scan: ultra fast in-memory table scan using on-chip vector processing units
Proceedings of the VLDB Endowment
SIMD-based decoding of posting lists
Proceedings of the 20th ACM international conference on Information and knowledge management
Lossless asymmetric single instruction multiple data codec
Software—Practice & Experience
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We study algorithms for efficient compression and decompression of a sequence of integers on modern hardware. Our focus is on universal codes in which the codeword length is a monotonically non-decreasing function of the uncompressed integer value; such codes are widely used for compressing "small integers". In contrast to traditional integer compression, our algorithms make use of the SIMD capabilities of modern processors by encoding multiple integer values at once. More specifically, we provide SIMD versions of both null suppression and Elias gamma encoding. Our experiments show that these versions provide a speedup from 1.5x up to 6.7x for decompression, while maintaining a similar compression performance.