A tool to analyze the performance of multithreaded programs on NUMA architectures

Abstract

Almost all of today's microprocessors contain memory controllers and directly attach to memory. Modern multiprocessor systems support non-uniform memory access (NUMA): it is faster for a microprocessor to access memory that is directly attached than it is to access memory attached to another processor. Without careful distribution of computation and data, a multithreaded program running on such a system may have high average memory access latency. To use multiprocessor systems efficiently, programmers need performance tools to guide the design of NUMA-aware codes. To address this need, we enhanced the HPCToolkit performance tools to support measurement and analysis of performance problems on multiprocessor systems with multiple NUMA domains. With these extensions, HPCToolkit helps pinpoint, quantify, and analyze NUMA bottlenecks in executions of multithreaded programs. It computes derived metrics to assess the severity of bottlenecks, analyzes memory accesses, and provides a wealth of information to guide NUMA optimization, including information about how to distribute data to reduce access latency and minimize contention. This paper describes the design and implementation of our extensions to HPCToolkit. We demonstrate their utility by describing case studies in which we use these capabilities to diagnose NUMA bottlenecks in four multithreaded applications.