Our partner the Goethe University Frankfurt am Main had a paper accepted for 25th Workshop on Advances in Parallel and Distributed Computational Models (APDCM’23), held in conjunction with IPDPS’23.
In this work, we propose the Network Performance Collector (NPC) workflow for automated network performance characterization. The workflow relies on the collection, processing, and visualization of network performance metrics such as throughput and latency, and can be used for analysis with various network performance models. Depending on the selected model, benchmark tools such as iperf or sockperf and microbenchmarks specific to parallel programming models can be automated and orchestrated for data collection using the NPC. The data obtained can then be used by NPC to, for example, validate and characterize the performance of the underlying network or to analyze the system limitations for a given application.