TA UoverSupermon: Low-Overhead Online Parallel Performance Monitoring

摘要

Online application performance monitoring allows tracking performance characteristics during execution as opposed to doing so post-mortem. This opens up several possibilities otherwise unavailable such as real-time visualization and application performance steering that can be useful in the context of long-running applications. As HPC systems grow in size and complexity, the key challenge is to keep the online performance monitor scalable and low overhead while still providing a useful performance reporting capability. Two fundamental components that constitute such a performance monitor are the measurement and transport systems. We adapt and combine two existing, mature systems -^sTAU and Supermon - to address this problem. TAU performs the measurement while Supermon is used to collect the distributed measurement state. Our experiments show that this novel approach leads to very low-overhead application monitoring as well as other benefits unavailable from using a transport such as NFS.