Affiliation:
1. University of California, Riverside
Abstract
Schedulers used by modern OSs (e.g., Oracle Solaris 11™ and GNU/Linux) balance load by balancing the number of threads in run queues of different cores. While this approach is effective for a single CPU multicore system, we show that it can lead to a significant load imbalance across CPUs of a multi-CPU multicore system. Because different threads of a multithreaded application often exhibit different levels of CPU utilization, load cannot be measured in terms of the number of threads alone. We propose
Tumbler
that migrates the threads of a multithreaded program across multiple CPUs to balance the load across the CPUs. While Tumbler distributes the threads equally across the CPUs, its assignment of threads to CPUs is aimed at minimizing the variation in utilization of different CPUs to achieve load balance. We evaluated Tumbler using a wide variety of 35 multithreaded applications, and our experimental results show that Tumbler outperforms both Oracle Solaris 11™ and GNU/Linux.
Funder
University of California Riverside
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Hardware and Architecture,Information Systems,Software
Cited by
3 articles.
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1. Efficient Synchronization-Light Work Stealing;Proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures;2023-06-17
2. AMBITION: Ambient Temperature Aware VM Allocation for Edge Data Centers;IEEE Access;2023
3. SCALO;ACM Transactions on Architecture and Code Optimization;2017-12-31