Tracing Data Movements within MPI Collectives

Brown, K.; Domke, Jens; Matsuoka, Satoshi

doi:10.1145/2642769.2642789

Cited by 9 publications

(6 citation statements)

References 8 publications

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“…This method provides an opportunity to gather information on state-changes inside the MPI library and gain detailed insight on what type of data (i.e., point-to-point or collectives) is exchanged between processes, as well as how and when. This technique has been used in [4,12].…”

Section: Related Workmentioning

confidence: 99%

Improving MPI Application Communication Time with an Introspection Monitoring Library

Jeannot

Sartori

2020

2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

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In this report we describe how to improve communication time of MPI parallel applications with the use of a library that enables to monitor MPI applications and allows for introspection (the program itself can query the state of the monitoring system). Based on previous work, this library is able to see how collective communications are decomposed into point-to-point messages. It also features monitoring sessions that allow suspending and restarting the monitoring, limiting it to specific portions of the code. Experiments show that the monitoring overhead is very small and that the proposed features allow for dynamic and efficient rank reordering enabling up to 2-time reduction of communication parts of some program.

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Section: Related Workmentioning

confidence: 99%

Improving MPI Application Communication Time with an Introspection Monitoring Library

Jeannot

Sartori

2020

2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

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“…PERUSE was an international effort to design a callback interface to collect internal information from MPI implementations. PERUSE was implemented in Open MPI [16] and used by selected projects in the MPI community [3,4,17].…”

Section: Perusementioning

confidence: 99%

Enabling callback-driven runtime introspection via MPI_T

Hermanns

Hjlem

Knobloch

et al. 2018

Proceedings of the 25th European MPI Users' Group Meeting

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Understanding the behavior of parallel applications that use the Message Passing Interface (MPI) is critical for optimizing communication performance. Performance tools for MPI currently rely on the PMPI Profiling Interface or the MPI Tools Information Interface, MPI_T, for portably collecting information for performance measurement and analysis. While tools using these interfaces have proven to be extremely valuable for performance tuning, these interfaces only provide synchronous information, i.e., when an MPI or an MPI_T function is called. There is currently no option for collecting information about asynchronous events from within the MPI library. In this work we propose a callback-driven interface for event notification from MPI implementations. Our approach is integrated in the existing MPI_T interface and provides a portable API for tools to discover and register for events of interest. We demonstrate the functionality and usability of the interface with a prototype implementation in Open MPI, a small logging tool (MEL) and the measurement infrastructure Score-P. CCS CONCEPTS• General and reference → Measurement; Performance; • Software and its engineering → Software libraries and repositories; KEYWORDS MPI, callback functions, runtime introspection ACM Reference Format:

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Section: Related Workmentioning

confidence: 99%

Online Dynamic Monitoring of MPI Communications

Bosilca

Foyer

Jeannot

et al. 2017

Lecture Notes in Computer Science

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Abstract. As the complexity and diversity of computer hardware and the elaborateness of network technologies have made the implementation of portable and efficient algorithms more challenging, the need to understand application communication patterns has become increasingly relevant. This paper presents details of the design and evaluation of a communication-monitoring infrastructure developed in the Open MPI software stack that can expose a dynamically configurable level of detail concerning application communication patterns.

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Tracing Data Movements within MPI Collectives

Cited by 9 publications

References 8 publications

Improving MPI Application Communication Time with an Introspection Monitoring Library

Improving MPI Application Communication Time with an Introspection Monitoring Library

Enabling callback-driven runtime introspection via MPI_T

Online Dynamic Monitoring of MPI Communications

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