Filters approximately store a set of items while trading off accuracy for space-efficiency and can address the limited memory on accelerators, such as GPUs. However, there is a lack of high-performance and feature-rich GPU filters as most advancements in filter research has focused on CPUs.
In this paper, we explore the design space of filters with a goal to develop massively parallel, high performance, and feature rich filters for GPUs. We evaluate various filter designs in terms of performance, usability, and supported features and identify two filter designs that offer the right trade off in terms of performance, features, and usability.
We present two new GPU-based filters, the TCF and GQF, that can be employed in various high performance data analytics applications. The TCF is a set membership filter and supports faster inserts and queries, whereas the GQF supports counting which comes at an additional performance cost. Both the GQF and TCF provide point and bulk insertion API and are designed to exploit the massive parallelism in the GPU without sacrificing usability and necessary features. The TCF and GQF are up to 4.4× and 1.4× faster than the previous GPU filters in our benchmarks and at the same time overcome the fundamental constraints in performance and usability in current GPU filters.
Mon 27 FebDisplayed time zone: Eastern Time (US & Canada) change
15:40 - 17:00 | Session 3: PracticeMain Conference at Montreal 4 Chair(s): I-Ting Angelina Lee Washington University in St. Louis, USA | ||
15:40 20mTalk | A Scalable Hybrid Total FETI Method for Massively Parallel FEM Simulations Main Conference Kehao Lin Hangzhou Dianzi University, Chunbao Zhou Computer Network Information Center, Chinese Academy of Sciences, Yan Zeng Hangzhou Dianzi University, Ningming Nie Computer Network Information Center, Chinese Academy of Sciences, Jue Wang Computer Network Information Center, Chinese Academy of Sciences, Shigang Li Beijing University of Posts and Telecommunications, Yangde Feng Computer Network Information Center, Chinese Academy of Sciences, Yangang Wang Computer Network Information Center, Chinese Academy of Sciences, Kehan Yao Hangzhou Dianzi University, Tiechui Yao Computer Network Information Center, Chinese Academy of Sciences, Jilin Zhang Hangzhou Dianzi University, Jian Wan Hangzhou Dianzi University | ||
16:00 20mTalk | Lifetime-based Optimization for Simulating Quantum Circuits on a New Sunway Supercomputer Main Conference Yaojian Chen Tsinghua University, Yong Liu National Supercomputer center in wuxi, Xinmin Shi Information Engineering University, Jiawei Song National Supercomputer center in wuxi, Xin Liu National Supercomputer center in wuxi, Lin Gan Tsinghua University, Chu Guo Information Engineering University, Haohuan Fu Tsinghua University, Jie Gao National Research Centre of Parallel Engineering and Technology, Dexun Chen National Supercomputer center in wuxi, Guangwen Yang Tsinghua University | ||
16:20 20mTalk | High-Performance Filters for GPUs Main Conference Hunter James McCoy University of Utah, Steven Hofmeyr Lawrence Berkeley National Laboratory, Katherine Yelick University of California at Berkeley & Lawrence Berkeley National Lab, Prashant Pandey University of Utah | ||
16:40 20mTalk | High-Performance and Scalable Agent-Based Simulation with BioDynaMo Main Conference Lukas Breitwieser European Organization for Nuclear Research (CERN), ETH Zurich, Ahmad Hesam Delft University of Technology, Fons Rademakers European Organization for Nuclear Research (CERN), Juan Gómez Luna ETH Zurich, Onur Mutlu ETH Zurich Pre-print Media Attached | ||