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Near memory key/value lookup acceleration
Author(s) -
Scott Lloyd,
Maya Gokhale
Publication year - 2017
Publication title -
proceedings of the international symposium on memory systems
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/3132402.3132434
Subject(s) - computer science , lookup table , speedup , key (lock) , hash function , workload , associative array , hash table , table (database) , parallel computing , memory bandwidth , operating system , database , computer security , artificial intelligence
In the "Big Data" era, fast lookup of keys in a key/value store is a ubiquitous operation. We have designed a near memory accelerator combining simple hardware building blocks to accelerate lookup in a hash table based key/value store. We report on the co-design of hardware and software to accomplish fast lookup using open addressing. The accelerator implements a batch get command to look up a set of keys in a single request. Using an FPGA emulator, we evaluate the performance of a query workload under a comprehensive range of conditions such as hash table load factor (fill) and query key repeat distribution (likelihood of a key to reappear in a query workload). We emulate two memory configurations: Hybrid Memory Cube (or High Bandwidth Memory), and Storage Class Memory. Our design shows 12.8X - 2.9X speedup compared to conventional CPU lookup depending on workload characteristics.

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