Flash code: studying astrophysical thermonuclear flashes
Computing in Science and Engineering
MPI-The Complete Reference, Volume 1: The MPI Core
MPI-The Complete Reference, Volume 1: The MPI Core
Runtime Checking of Datatype Signatures in MPI
Proceedings of the 7th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
A Portable Method for Finding User Errors in the Usage of MPI Collective Operations
International Journal of High Performance Computing Applications
MPIWiz: subgroup reproducible replay of mpi applications
Proceedings of the 14th ACM SIGPLAN symposium on Principles and practice of parallel programming
Correctness checking of MPI one-sided communication using marmot
EuroPVM/MPI'06 Proceedings of the 13th European PVM/MPI User's Group conference on Recent advances in parallel virtual machine and message passing interface
MPI runtime error detection with MUST: advances in deadlock detection
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Open issues in MPI implementation
ACSAC'07 Proceedings of the 12th Asia-Pacific conference on Advances in Computer Systems Architecture
Combining static and dynamic validation of MPI collective communications
Proceedings of the 20th European MPI Users' Group Meeting
Runtime MPI collective checking with tree-based overlay networks
Proceedings of the 20th European MPI Users' Group Meeting
MPI runtime error detection with MUST: Advances in deadlock detection
Scientific Programming - Selected Papers from Super Computing 2012
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An MPI profiling library is a standard mechanism for intercepting MPI calls by applications. Profiling libraries are so named because they are commonly used to gather performance data on MPI programs. Here we present a profiling library whose purpose is to detect user errors in the use of MPI’s collective operations. While some errors can be detected locally (by a single process), other errors involving the consistency of arguments passed to MPI collective functions must be tested for in a collective fashion. While the idea of using such a profiling library does not originate here, we take the idea further than it has been taken before (we detect more errors) and offer an open-source library that can be used with any MPI implementation. We describe the tests carried out, provide some details of the implementation, illustrate the usage of the library, and present performance tests.