Value Iteration on Multicore Processors

被引:0
|
作者
Jain, Anuj [1 ]
Sahni, Sartaj [2 ]
机构
[1] Adobe Syst Inc, Lehi, UT 84043 USA
[2] Univ Florida, CISE Dept, Gainesville, FL USA
基金
美国国家科学基金会;
关键词
Reinforcement Learning; Markov Decision Process; Value Iteration; Multicore; Parallelization;
D O I
10.1109/ISSPIT51521.2020.9408773
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Value Iteration (VI) is a powerful, though time consuming, approach to solve reinforcement learning problems modeled as Markov Decision Processes (MDPs). In this paper, we explore strategies to run the sate-of-the-art cache efficient algorithm for VI developed by us [1], [2] on a multicore processor. We demonstrate a speedup of up to 2.59 on a 10-core multiprocessor using 20 threads on popular benchmark data. The speedup for the parallelized portion of the computation is up to 5.89.
引用
收藏
页数:7
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