适合GPU的混合存取缓存索引框架

Hongjun Zhang, Yanjun Wu, Heng Zhang, Libo Zhang
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引用次数: 0

摘要

哈希表作为一种基于键值提供高效数据访问的数据索引结构,被广泛应用于各种计算机应用,特别是对性能要求极高的系统软件、数据库和高性能计算领域。在网络、云计算和物联网服务中,哈希表已经成为缓存系统的核心系统组件。然而,随着大规模数据量的大量增加,以多核CPU为哈希表结构核心的系统逐渐出现了性能瓶颈。目前迫切需要进一步提高哈希表的高性能和可扩展性。随着通用图形处理单元(GPU)的日益普及以及硬件计算能力和并发性能的大幅提升,以并行计算为核心的各类系统软件任务都在GPU上进行了优化,并取得了相当大的性能提升。由于散列表的稀疏性和随机性,直接在gpu上使用散列表现有的并行结构,必然会带来高频的内存访问和频繁的总线数据传输,从而影响gpu上散列表的性能。本研究主要分析缓存系统中哈希表索引的内存访问、命中率和索引开销。提出并提供了一种适用于GPU的混合存取缓存索引框架CCHT (cache Cuckoo Hash Table)。适合不同命中率和索引开销要求的缓存策略,允许同时执行写和查询操作,最大限度地利用GPU硬件的计算性能和并发特性,减少内存访问和总线传输开销。通过GPU硬件实现和实验验证,CCHT算法在保证缓存命中率的前提下,具有比其他缓存索引哈希表更好的性能。
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Hybrid Access Cache Indexing Framework Adapted to GPU
Hash tables, as a type of data indexing structure that provides efficient data access based on key values, are widely used in various computer applications, especially in system software, databases, and high-performance computing field that requires extremely high performance. In network, cloud computing and IoT services, hash tables have become the core system components of cache systems. However, with the large-scale increase in the amount of large-scale data, performance bottlenecks have gradually emerged in systems designed with a multi-core CPU as the core of the hash table structure. There is an urgent need to further improve the high performance and scalability of the hash tables. With the increasing popularity of general-purpose Graphic Processing Units (GPUs) and the substantial improvement of hardware computing capabilities and concurrency performance, various types of system software tasks with parallel computing as the core have been optimized on the GPU and have achieved considerable performance improvements. Due to the sparseness and randomness, using the existing parallel structure of the hash tables directly on the GPUs will inevitably bring high-frequency memory access and frequent bus data transmission, which affects the performance of the hash tables on the GPUs. This study focuses on the analysis of memory access, hit ratio, and index overhead of hash table indexes in the cache system. The hybrid access cache indexing framework CCHT (Cache Cuckoo Hash Table) adapted to GPU is proposed and provided. The cache strategy suitable to different requirements of hit ratios and index overheads allows concurrent execution of write and query operations, maximizing the use of the computing performance and concurrency characteristics of GPU hardware, reducing memory access and bus transferring overhead. Through GPU hardware implementation and experimental verification, CCHT is shown to have better performance than other cache indexing hash tables while ensuring cache hit ratios.
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