A Tool for Top-down Performance Analysis of GPU-Accelerated Applications

Abstract

To support performance measurement and analysis of GPU-accelerated applications, we extended the HPCToolkit performance tools with several novel features. To support efficient monitoring of accelerated applications, HPCToolkit employs a new wait-free data structure to coordinate measurement and attribution between each application thread and a GPU monitor thread. To help developers understand the performance of accelerated applications, HPCToolkit attributes metrics to heterogeneous calling contexts that span both CPUs and GPUs. To support fine-grain analysis and tuning of GPU-accelerated code, HPCToolkit collects PC samples of both CPU and GPU activity to derive and attribute metrics at all levels in a heterogeneous calling context.

Publication
Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP)