Performance analysis using the MIPS R10000 performance counters

摘要

Tuning supercomputer application performance often requires analyzing the interaction of the application and the underlying architecture. In this paper, we describe support in the MIPS R10000 for non-intrusively monitoring a variety of processor events -- support that is particularly useful for characterizing the dynamic behavior of multi-level memory hierarchies, hardware-based cache coherence, and speculative execution. We first explain how performance data is collected using an integrated set of hardware mechanisms, operating system abstractions, and performance tools. We then describe several examples drawn from scientific applications that illustrate how the counters and profiling tools provide information that helps developers analyze and tune applications.