Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 193

The DOI matches its Crossref record.

Implementation and performance analysis of non-blocking collective operations for MPI

Hoefler, Torsten, Lumsdaine, Andrew, Rehm, Wolfgang·2007·Proceedings of the 2007 ACM/IEEE conference on Supercomputing

Abstract

Collective operations and non-blocking point-to-point operations have always been part of MPI. Although non-blocking collective operations are an obvious extension to MPI, there have been no comprehensive studies of this functionality. In this paper we present LibNBC, a portable high-performance library for implementing non-blocking collective MPI communication operations. LibNBC provides non-blocking versions of all MPI collective operations, is layered on top of MPI-1, and is portable to nearly all parallel architectures. To measure the performance characteristics of our implementation, we also present a microbenchmark for measuring both latency and overlap of computation and communication. Experimental results demonstrate that the blocking performance of the collective operations in our library is comparable to that of collective operations in other highperformance MPI implementations. Our library introduces a very low overhead between the application and the underlying MPI and thus, in conjunction with the potential to overlap communication with computation, offers the potential for optimizing real-world applications.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/1362622.1362692

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 193

Metadata

Authors
Hoefler, T., Lumsdaine, A., & Rehm, W.
Venue
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Publisher
ACM
Published
2007-11-10
Pages
1-10
ISSN
1063-9535 (ISSN-L)
OpenAlex
W2165808215
Cited by
193
References
0
FWCI
9.30
Type
conference paper
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Implementation and performance analysis of non-blocking collective operations for MPI. https://app.cochat.ai/papers/10.1145/1362622.1362692
The paper
Hoefler, T., Lumsdaine, A., & Rehm, W. (2007). Implementation and performance analysis of non-blocking collective operations for MPI. Proceedings of the 2007 ACM/IEEE conference on Supercomputing. https://doi.org/10.1145/1362622.1362692

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.