Faster Compressed Indexes On Next-Generation Hardware

下一代硬件上更快的压缩索引

• 批准号: RGPIN-2017-03910
• 负责人: Lemire, Daniel
• 金额: $ 3.06万
• 依托单位: TÉLUQ
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634510
• 关键词: Faster; Compressed; Indexes; Next; Generation

Software indexes accelerate applications in business analytics, machine learning, and data science. They often determine the performance of big-data applications. Efficient indexes not only improve latency and throughput, but they also reduce energy usage. Many indexes make parsimonious use of internal memory so that critical data remains close to the processor. It is also desirable to work directly on the compressed data, to avoid potentially harmful decoding passes. Thus, we use lightweight compression strategies, optimized for speed.

软件索引加速了业务分析、机器学习和数据科学领域的应用。它们通常决定着大数据应用程序的性能。高效的索引不仅可以改善延迟和吞吐量，还可以减少能源使用。许多索引对内部内存的使用非常节省，以便关键数据保持在处理器附近。直接处理压缩数据也是可取的，以避免潜在的有害解码过程。因此，我们使用针对速度进行了优化的轻量级压缩策略。