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Understanding the use of message passing interface in exascale proxy applications
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/cpe.4851openalex-snapshot
A survey of MPI usage in the US exascale computing project
inferredcites →https://doi.org/10.1007/3-540-47789-6_66openalex-snapshot
hypre: A Library of High Performance Preconditioners
inferredcites →https://doi.org/10.1007/978-1-4613-1401-1_5openalex-snapshot
Overview of the MPI-IO Parallel I/O Interface
inferredcites →https://doi.org/10.1007/978-3-0348-8534-8_21openalex-snapshot
The MPI Message Passing Interface Standard
inferredcites →https://doi.org/10.1007/978-3-540-30218-6_19openalex-snapshot
Open MPI: Goals, Concept, and Design of a Next Generation MPI Implementation
inferredcites →https://doi.org/10.1016/0167-8191(96)00024-5openalex-snapshot
A high-performance, portable implementation of the MPI message passing interface standard
inferredcites →https://doi.org/10.1109/clustr.2009.5289150openalex-snapshot
24/7 Characterization of petascale I/O workloads
inferredcites →https://doi.org/10.1109/ipdps.2002.1015504openalex-snapshot
Communication characteristics of large-scale scientific applications for contemporary cluster architectures
inferredcites →https://doi.org/10.1109/ipdps.2009.5160935openalex-snapshot
Sparse collective operations for MPI
inferredcites →https://doi.org/10.1109/ipdps.2011.249openalex-snapshot
Characterization of the Communication Patterns of Scientific Applications on Blue Gene/P
inferredcites →https://doi.org/10.1109/sc.2002.10036openalex-snapshot
An Empirical Performance Evaluation of Scalable Scientific Applications
inferredcites →https://doi.org/10.1109/sc.2018.00033openalex-snapshot
Characterization of MPI Usage on a Production Supercomputer
inferredcites →https://doi.org/10.1109/spdp.1995.530729openalex-snapshot
Dynamic process management in an MPI setting
inferredcites →https://doi.org/10.1145/173682.165124openalex-snapshot
Architectural requirements of parallel scientific applications with explicit communication
inferredcites →https://doi.org/10.1145/331532.331573openalex-snapshot
Architectural requirements and scalability of the NAS parallel benchmarks
inferredcites →https://doi.org/10.1177/1094342006064482openalex-snapshot
The Tau Parallel Performance System
inferredcites →https://doi.org/10.1504/ijhpcn.2006.010633openalex-snapshot
Implications of application usage characteristics for collective communication offload
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.70158openalex-snapshot
Mpisee: Communicator‐Centric Profiling of MPI Applications
inferred← citeshttps://doi.org/10.1002/cpe.7540openalex-snapshot
PB3Opt: Profile‐based biased Bayesian optimization to select computing clusters on the cloud
inferred← citeshttps://doi.org/10.1007/s00366-026-02391-5openalex-snapshot
Distributed semi-speculative parallel anisotropic mesh adaptation
inferred← citeshttps://doi.org/10.1016/j.parco.2021.102825openalex-snapshot
Evaluating MPI resource usage summary statistics
inferred← citeshttps://doi.org/10.1016/j.parco.2021.102853openalex-snapshot
An international survey on MPI users
inferred← citeshttps://doi.org/10.1109/cluster52292.2023.00013openalex-snapshot
Generalized Collective Algorithms for the Exascale Era
inferred← citeshttps://doi.org/10.1109/cluster52292.2023.00031openalex-snapshot
Uniform Algorithms for Reduce-scatter and (most) other Collectives for MPI
inferred← citeshttps://doi.org/10.1109/cluster59578.2024.00017openalex-snapshot
MPI Collective Algorithm Selection in the Presence of Process Arrival Patterns
inferred← citeshttps://doi.org/10.1109/eecsi67060.2025.11290155openalex-snapshot
Optimizing Parallel Computing Using a Raspberry Pi Cluster with the Message Passing Interface (MPI) Protocol
inferred← citeshttps://doi.org/10.1109/exampi52011.2020.00011openalex-snapshot
Extending the MPI Stages Model of Fault Tolerance
inferred← citeshttps://doi.org/10.1109/ipdpsw63119.2024.00090openalex-snapshot
Benchmarking Variables for Checkpointing in HPC Applications
inferred← citeshttps://doi.org/10.1109/mchpc54807.2021.00009openalex-snapshot
Performance and Energy Improvement of ECP Proxy App SW4lite under Various Workloads
inferred← citeshttps://doi.org/10.1109/pmbs56514.2022.00016openalex-snapshot
OMPICollTune: Autotuning MPI Collectives by Incremental Online Learning
inferred← citeshttps://doi.org/10.1109/sc41406.2024.00105openalex-snapshot
AutoCheck: Automatically Identifying Variables for Checkpointing by Data Dependency Analysis
inferred← citeshttps://doi.org/10.1145/3526063.3535353openalex-snapshot
An Overhead Analysis of MPI Profiling and Tracing Tools
inferred← citeshttps://doi.org/10.1145/3615318.3615322openalex-snapshot
Investigating the Usage of MPI at Argument-Granularity in HPC Codes
inferred← citeshttps://doi.org/10.1145/3615318.3615325openalex-snapshot
Synchronizing MPI Processes in Space and Time
inferred← citeshttps://doi.org/10.1145/3624062.3624109openalex-snapshot
Using Mixed-Radix Decomposition to Enumerate Computational Resources of Deeply Hierarchical Architectures
inferred← citeshttps://doi.org/10.1145/3624062.3625532openalex-snapshot
Verifying Performance Guidelines for MPI Collectives at Scale
inferred← citeshttps://doi.org/10.1145/3673897openalex-snapshot
A Toolset for Predicting Performance of Legacy Real-Time Software Based on the RAST Approach
inferred← citeshttps://doi.org/10.1155/2022/1121822openalex-snapshot
Computation Offloading in Mobile Cloud Computing and Mobile Edge Computing: Survey, Taxonomy, and Open Issues
inferred← citeshttps://doi.org/10.35444/ijana.2023.15106openalex-snapshot
Image Processing on Agricultural Dataset Using Parallel Processing Based on Python
inferred← citeshttps://doi.org/10.3844/jcssp.2022.860.867openalex-snapshot
Framework for Containers Orchestration to handle the Scientific Workloads using Kubernetes
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