Cache-coherent non-uniform memory access (ccNUMA) systems enable parallel applications to scale-up to thousands of cores and many terabytes of main memory. However, since remote accesses come at an increased cost, extra measures are necessitated to scale the applications to high core-counts and process far greater amounts of data than a typical server can hold. In a similar manner to how applications are optimized to improve cache utilization, applications also need to be optimized to improve data-locality on ccNUMA systems to use larger topologies effectively. The first step to optimizing an application is to understand what slows it down. Consequently, profiling tools, or manual instrumentation, are necessary to achieve this. When optimizing applications on large ccNUMA systems, however, there are limited mechanisms to capture and present actionable telemetry. This is partially driven by the proprietary nature of such interconnects, but also by the lack of development of a common and accessible (read open-source) framework that developers or vendors can leverage.
In this paper, we present an open-source, extensible framework that captures high-rate on-chip events with low overhead (<10% single-core utilization). The presented framework can operate in live or record mode, allowing both real-time monitoring or capture for later post-workload or offline analysis. High-resolution visualization is available either through a standards-based (web) interactive graphical interface or through a convenient textual interface for quick-look analysis.