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Topology-Aware GPU Selection on Multi-GPU Nodes

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-24449-0_7openalex-snapshot
Improving MPI Applications Performance on Multicore Clusters with Rank Reordering
inferredcites →https://doi.org/10.1007/978-3-642-24449-0_8openalex-snapshot
Multi-core and Network Aware MPI Topology Functions
inferredcites →https://doi.org/10.1007/s00450-011-0168-yopenalex-snapshot
Mapping communication layouts to network hardware characteristics on massive-scale blue gene systems
inferredcites →https://doi.org/10.1016/j.compfluid.2012.04.024openalex-snapshot
Automatically optimized core mapping to subdomains of domain decomposition method on multicore parallel environments
inferredcites →https://doi.org/10.1109/cluster.2011.30openalex-snapshot
Process Distance-Aware Adaptive MPI Collective Communications
inferredcites →https://doi.org/10.1109/hpcc.2012.69openalex-snapshot
DMA-Assisted, Intranode Communication in GPU Accelerated Systems
inferredcites →https://doi.org/10.1109/hpcsim.2014.6903671openalex-snapshot
Managing the topology of heterogeneous cluster nodes with hardware locality (hwloc)
inferredcites →https://doi.org/10.1109/ipdps.2009.5161094openalex-snapshot
An evaluative study on the effect of contention on message latencies in large supercomputers
inferredcites →https://doi.org/10.1109/ipdpsw.2012.228openalex-snapshot
Optimizing MPI Communication on Multi-GPU Systems Using CUDA Inter-Process Communication
inferredcites →https://doi.org/10.1109/iscc.2009.5202271openalex-snapshot
Multi-core aware process mapping and its impact on communication overhead of parallel applications
inferredcites →https://doi.org/10.1109/pdp.2010.67openalex-snapshot
hwloc: A Generic Framework for Managing Hardware Affinities in HPC Applications
inferredcites →https://doi.org/10.1145/2642769.2642773openalex-snapshot
GPU-Aware Intranode MPI_Allreduce

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Contention-Based Threats Between Single-Tenant Cloud FPGA Instances
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The Future of the Non-memory Semiconductor Industry
inferred← citeshttps://doi.org/10.1007/s11227-018-2246-4openalex-snapshot
Analysis of large deviations behavior of multi-GPU memory access in deep learning
inferred← citeshttps://doi.org/10.1016/j.ins.2021.11.042openalex-snapshot
An efficient GPU implementation and scaling for higher-order 3D stencils
inferred← citeshttps://doi.org/10.1016/j.jksuci.2020.05.011openalex-snapshot
An effective scheme for memory congestion reduction in multi-core environment
inferred← citeshttps://doi.org/10.1016/j.parco.2017.07.001openalex-snapshot
Exploiting heterogeneity of communication channels for efficient GPU selection on multi-GPU nodes
inferred← citeshttps://doi.org/10.1109/fccm51124.2021.00035openalex-snapshot
Cloud FPGA Cartography using PCIe Contention
inferred← citeshttps://doi.org/10.1109/host49136.2021.9702277openalex-snapshot
Cross-VM Information Leaks in FPGA-Accelerated Cloud Environments
inferred← citeshttps://doi.org/10.1109/ipdpsw.2019.00083openalex-snapshot
A GPU Inference System Scheduling Algorithm with Asynchronous Data Transfer
inferred← citeshttps://doi.org/10.1109/jiot.2021.3111624openalex-snapshot
A Comprehensive Survey on Training Acceleration for Large Machine Learning Models in IoT
inferred← citeshttps://doi.org/10.1109/lca.2019.2933842openalex-snapshot
Speeding up Collective Communications Through Inter-GPU Re-Routing
inferred← citeshttps://doi.org/10.1109/sbac-pad.2016.15openalex-snapshot
MAGC: A Mapping Approach for GPU Clusters
inferred← citeshttps://doi.org/10.1109/sc.2016.62openalex-snapshot
A PCIe Congestion-Aware Performance Model for Densely Populated Accelerator Servers
inferred← citeshttps://doi.org/10.1109/tnet.2024.3416419openalex-snapshot
Diagnosing End-Host Network Bottlenecks in RDMA Servers
inferred← citeshttps://doi.org/10.1109/tnse.2023.3344850openalex-snapshot
ENASFL: A Federated Neural Architecture Search Scheme for Heterogeneous Deep Models in Distributed Edge Computing Systems
inferred← citeshttps://doi.org/10.1109/tpds.2026.3716225openalex-snapshot
BandPilot: Toward Performance- and Contention-Aware GPU Dispatching in AI Clusters
inferred← citeshttps://doi.org/10.1145/3126908.3126933openalex-snapshot
Topology-aware GPU scheduling for learning workloads in cloud environments
inferred← citeshttps://doi.org/10.1145/3458817.3480853openalex-snapshot
MAPA
inferred← citeshttps://doi.org/10.1145/3534972openalex-snapshot
Cross-VM Covert- and Side-Channel Attacks in Cloud FPGAs
inferred← citeshttps://doi.org/10.1145/3635312openalex-snapshot
Covert-channels in FPGA-enabled SmartSSDs
inferred← citeshttps://doi.org/10.1177/10943420261465459openalex-snapshot
Optimizing GPU-aware halo exchange for computations on structured grids
inferred← citeshttps://doi.org/10.1360/ssv-2020-0158openalex-snapshot
Advances in X-ray imaging technology
inferred← citeshttps://doi.org/10.23919/isc.2024.10528923openalex-snapshot
ROCm-Aware Leader-based Designs for MPI Neighbourhood Collectives
inferred← citeshttps://doi.org/10.23919/isc.2025.11018266openalex-snapshot
Rail Optimized PCIe Topologies for LLMs
inferred← citeshttps://doi.org/10.48550/arxiv.2008.00409openalex-snapshot
P-Cloth: Interactive Complex Cloth Simulation on Multi-GPU Systems using Dynamic Matrix Assembly and Pipelined Implicit Integrators
inferred← citeshttps://doi.org/10.5821/dissertation-2117-132778openalex-snapshot
Improving resource efficiency in virtualized datacenters
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