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Title: Enabling communication concurrency through flexible MPI endpoints

Journal Article · · International Journal of High Performance Computing Applications
 [1];  [2];  [3];  [4];  [5];  [3];  [3]
  1. Intel Corporation, Hudson, MA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Argonne National Lab. (ANL), Argonne, IL (United States)
  4. Cisco Systems Inc., San Jose, CA (United States)
  5. International Business Machines Corporation, Rochester, MN (United States)
+ Show Author Affiliations

MPI defines a one-to-one relationship between MPI processes and ranks. This model captures many use cases effectively; however, it also limits communication concurrency and interoperability between MPI and programming models that utilize threads. Our paper describes the MPI endpoints extension, which relaxes the longstanding one-to-one relationship between MPI processes and ranks. Using endpoints, an MPI implementation can map separate communication contexts to threads, allowing them to drive communication independently. Also, endpoints enable threads to be addressable in MPI operations, enhancing interoperability between MPI and other programming models. Furthermore, these characteristics are illustrated through several examples and an empirical study that contrasts current multithreaded communication performance with the need for high degrees of communication concurrency to achieve peak communication performance.

Research Organization:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC04-94AL85000
OSTI ID:
1140752
Report Number(s):
SAND2014-0614J; 498469
Journal Information:
International Journal of High Performance Computing Applications, Vol. 28, Issue 4; ISSN 1094-3420
Publisher:
SAGECopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 30 works
Citation information provided by
Web of Science

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Cited By (6)

Optimizing point‐to‐point communication between adaptive MPI endpoints in shared memory journal March 2018
A survey of MPI usage in the US exascale computing project: A survey of MPI usage in the U. S. exascale computing project journal September 2018
Hardware MPI message matching: Insights into MPI matching behavior to inform design
  • Ferreira, Kurt; Grant, Ryan E.; Levenhagen, Michael J.
  • Concurrency and Computation: Practice and Experience, Vol. 32, Issue 3 https://doi.org/10.1002/cpe.5150
journal February 2019
Tail queues: A multi‐threaded matching architecture
  • Dosanjh, Matthew G. F.; Grant, Ryan E.; Schonbein, Whit
  • Concurrency and Computation: Practice and Experience, Vol. 32, Issue 3 https://doi.org/10.1002/cpe.5158
journal February 2019
Finepoints: Partitioned Multithreaded MPI Communication
  • Grant, Ryan E.; Dosanjh, Matthew G. F.; Levenhagen, Michael J.
  • High Performance Computing: 34th International Conference, ISC High Performance 2019, Frankfurt/Main, Germany, June 16–20, 2019, Proceedings, p. 330-350 https://doi.org/10.1007/978-3-030-20656-7_17
book May 2019
MPI Sessions: Leveraging Runtime Infrastructure to Increase Scalability of Applications at Exascale conference January 2016

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Related Subjects

97 MATHEMATICS AND COMPUTING
MPI
endpoints
hybrid parallel programming
interoperability
communication concurrency