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MPI Alltoall Personalized Exchange on GPGPU Clusters: Design Alternatives and Benefit
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s00450-011-0170-4openalex-snapshot
High-performance and scalable non-blocking all-to-all with collective offload on InfiniBand clusters: a study with parallel 3D FFT
inferredcites →https://doi.org/10.1007/s00450-011-0171-3openalex-snapshot
MVAPICH2-GPU: optimized GPU to GPU communication for InfiniBand clusters
inferredcites →https://doi.org/10.1109/71.642949openalex-snapshot
Efficient algorithms for all-to-all communications in multiport message-passing systems
inferredcites →https://doi.org/10.1109/cluster.2011.42openalex-snapshot
Optimized Non-contiguous MPI Datatype Communication for GPU Clusters: Design, Implementation and Evaluation with MVAPICH2
inferredcites →https://doi.org/10.1109/clustr.2009.5289129openalex-snapshot
Message passing for GPGPU clusters: CudaMPI
inferredcites →https://doi.org/10.1109/ipdps.2008.4536141openalex-snapshot
Scaling alltoall collective on multi-core systems
inferredcites →https://doi.org/10.1109/sc.2008.5214716openalex-snapshot
Adapting a message-driven parallel application to GPU-accelerated clusters
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.4667openalex-snapshot
Design considerations for GPU‐aware collective communications in MPI
inferred← citeshttps://doi.org/10.1002/cpe.5470openalex-snapshot
Benchmarking multi‐GPU applications on modern multi‐GPU integrated systems
inferred← citeshttps://doi.org/10.1007/978-3-031-07312-0_1openalex-snapshot
Accelerating MPI All-to-All Communication with Online Compression on Modern GPU Clusters
inferred← citeshttps://doi.org/10.1007/978-3-031-92602-0_4openalex-snapshot
A Survey of Optimization Approaches for MPI_Alltoall and MPI_Alltoallv Collective Communication Operations
inferred← citeshttps://doi.org/10.1007/978-3-642-33518-1_16openalex-snapshot
OMB-GPU: A Micro-Benchmark Suite for Evaluating MPI Libraries on GPU Clusters
inferred← citeshttps://doi.org/10.1109/ccgrid.2014.21openalex-snapshot
Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs
inferred← citeshttps://doi.org/10.1109/ccgrid51090.2021.00021openalex-snapshot
Adaptive and Hierarchical Large Message All-to-all Communication Algorithms for Large-scale Dense GPU Systems
inferred← citeshttps://doi.org/10.1109/hipc.2014.7116873openalex-snapshot
Designing efficient small message transfer mechanism for inter-node MPI communication on InfiniBand GPU clusters
inferred← citeshttps://doi.org/10.1109/hipc.2014.7116875openalex-snapshot
A high performance broadcast design with hardware multicast and GPUDirect RDMA for streaming applications on Infiniband clusters
inferred← citeshttps://doi.org/10.1109/hpcc.2012.69openalex-snapshot
DMA-Assisted, Intranode Communication in GPU Accelerated Systems
inferred← citeshttps://doi.org/10.1109/icpp.2013.17openalex-snapshot
Efficient Inter-node MPI Communication Using GPUDirect RDMA for InfiniBand Clusters with NVIDIA GPUs
inferred← citeshttps://doi.org/10.1109/ipdpsw.2012.227openalex-snapshot
Efficient Intranode Communication in GPU-Accelerated Systems
inferred← citeshttps://doi.org/10.1109/ipdpsw55747.2022.00014openalex-snapshot
Highly Efficient Alltoall and Alltoallv Communication Algorithms for GPU Systems
inferred← citeshttps://doi.org/10.1109/sbac-pad.2016.15openalex-snapshot
MAGC: A Mapping Approach for GPU Clusters
inferred← citeshttps://doi.org/10.1109/tc.2015.2417526openalex-snapshot
DwarfCode: A Performance Prediction Tool for Parallel Applications
inferred← citeshttps://doi.org/10.1145/2462902.2462915openalex-snapshot
On the efficacy of GPU-integrated MPI for scientific applications
inferred← citeshttps://doi.org/10.1145/2642769.2642773openalex-snapshot
GPU-Aware Intranode MPI_Allreduce
inferred← citeshttps://doi.org/10.1145/2832241.2832247openalex-snapshot
Hyper-Q aware intranode MPI collectives on the GPU
inferred← citeshttps://doi.org/10.4304/jsw.9.9.2366-2377openalex-snapshot
High-accuracy Optimization by Parallel Iterative Discrete Approximation and GPU Cluster Computing
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