Preserving time in large-scale communication traces
Proceedings of the 22nd annual international conference on Supercomputing
Scalable load-balance measurement for SPMD codes
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
On-Line Performance Modeling for MPI Applications
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
Deterministic replay for message-passing-based concurrent programs
ACM Transactions on Design Automation of Electronic Systems (TODAES) - Special section on verification challenges in the concurrent world
Auto-generation of communication benchmark traces
ACM SIGMETRICS Performance Evaluation Review
Retrospect: deterministic replay of MPI applications for interactive distributed debugging
PVM/MPI'07 Proceedings of the 14th European conference on Recent Advances in Parallel Virtual Machine and Message Passing Interface
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Characterizing the communication behavior of large-scale applications is a difficult and costly task due to code and system complexity as well as the time to execute such codes. An alternative to run actual codes is to gather their communication traces and then replay them, which facilitates application tuning and future procurements. While past approaches lacked lossless scalable trace collection, we contribute an approach that provides near constant-size communication traces regardless of the number of nodes while preserving structural information. We introduce intra- and inter-node compression techniques of MPI events and present results of our implementation. Given this novel capability, we discuss its impact on communication tuning and beyond.