Darshan, a scalable HPC I/O characterization tool. Darshan is designed to capture an accurate picture of application I/O behavior, including properties such as patterns of access within files, with minimum overhead. The name is taken from a Sanskrit word for “sight” or “vision”.

Darshan can be used to investigate and tune the I/O behavior of complex HPC applications. In addition, Darshan’s lightweight design makes it suitable for full time deployment for workload characterization of large systems. We hope that such studies will help the storage research community to better serve the needs of scientific computing. Darshan was originally developed on the IBM Blue Gene series of computers deployed at the Argonne Leadership Computing Facility, but it is portable across a wide variety of platforms include the Cray XE6, Cray XC30, and Linux clusters. Darshan routinely instruments jobs using up to 786,432 compute cores on the Mira system at ALCF.



Score-P – Scalable Performance Measurement Infrastructure for Parallel Codes- The Score-P measurement infrastructure is a highly scalable and easy-to-use tool suite for profiling, event tracing, and online analysis of HPC applications. It has been created in the German BMBF project SILC and the US DOE project PRIMA and will be maintained and enhanced in a number of follow-up projects such as LMAC, Score-E, and HOPSA. Score-P is developed under a BSD 3-Clause License and governed by a meritocratic governance model.



Extra-P is an automatic performance-modeling tool that supports the user in the identification of scalability bugs. A scalability bug is a part of the program whose scaling behavior is unintentionally poor, that is, much worse than expected. A performance model is a formula that expresses a performance metric of interest such as execution time or energy consumption as a function of one or more execution parameters such as the size of the input problem or the number of processors.