IIIT Hyderabad Publications
A heterogeneous CPU+GPU Working-set hash table
Authors: Ziaul Choudhury,Suresh Purini
Report no: IIIT/TR/2016/19
In this paper, we propose heterogeneous (CPU+GPU) hash tables, that optimizes 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 out perform concurrent lock free hash tables, nevertheless matches their performance.
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Centre for Software Engineering Research Lab
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