Heterogeneous (CPU+GPU) Working-set Hash Tables

Ziaul Choudhury, Suresh Purini
International Institute of Information Technology, Hyderabad, India
Ninth International Workshop on Programmability and Architectures for Heterogeneous Multicores (MULTIPROG-2016), 2016


   title={Heterogeneous (CPU+ GPU) Working-set Hash Tables},

   author={Choudhury, Ziaul and Purini, Suresh},



Download Download (PDF)   View View   Source Source   



In this paper, we propose heterogeneous (CPU+GPU) hash tables, that optimize operations for frequently accessed keys. The idea is to maintain a dynamic set of most frequently accessed keys in the GPU memory and the rest of the keys in the CPU main memory. Further, queries are processed in batches of fixed size. We measured the query throughput of our hash tables using Millions of Queries Processed per Second (MQPS) as a metric, on different key access distributions. On distributions, where some keys are queried more frequently than others, we achieved on average 10x higher MQPS when compared to a highly tuned serial hash table in the C++ Boost library; and 5x higher MQPS against a state of the art concurrent lock free hash table. The maximum load factor on the hash tables was set to 0.9. On uniform random query distributions, as expected our hash tables do not outperform concurrent lock free hash tables, nevertheless matches their performance.
Rating: 1.5/5. From 2 votes.
Please wait...

* * *

* * *

HGPU group © 2010-2021 hgpu.org

All rights belong to the respective authors

Contact us: