Visible to the public Optimization of Hardware-oblivious and Hardware-conscious Hash-join Algorithms on KNL

TitleOptimization of Hardware-oblivious and Hardware-conscious Hash-join Algorithms on KNL
Publication TypeConference Paper
Year of Publication2019
AuthorsTang, Deyou, Zhang, Yazhuo, Zeng, Qingmiao
Conference Name2019 4th International Conference on Cloud Computing and Internet of Things (CCIOT)
Date Publisheddec
Keywordsalgorithm optimization, compositionality, hardware architecture features, hardware-conscious hash join algorithms, hardware-oblivious hash join algorithms, hash algorithms, hash join, Knights Landing, KNL hardware characteristics, manycore platforms, memory allocation, multi-threading, multicore servers, multiprocessing systems, multithreading, parallel computing, parallel processing, pubcrawl, Resiliency, storage management
AbstractInvestigation of hash join algorithm on multi-core and many-core platforms showed that carefully tuned hash join implementations could outperform simple hash joins on most multi-core servers. However, hardware-oblivious hash join has shown competitive performance on many-core platforms. Knights Landing (KNL) has received attention in the field of parallel computing for its massively data-parallel nature and high memory bandwidth, but both hardware-oblivious and hardware-conscious hash join algorithms have not been systematically discussed and evaluated for KNL's characteristics (high bandwidth, cluster mode, etc.). In this paper, we present the design and implementation of the state-of-the-art hardware-oblivious and hardware-conscious hash joins that are tuned to exploit various KNL hardware characteristics. Using a thorough evaluation, we show that:1) Memory allocation strategies based on KNL's architecture are effective for both hardware-oblivious and hardware-conscious hash join algorithms; 2) In order to improve the efficiency of the hash join algorithms, hardware architecture features are still non-negligible factors.
Citation Keytang_optimization_2019