Titlebook: Euro-Par 2024: Parallel Processing; 30th European Confer Jesus Carretero,Sameer Shende,Martin Schreiber Conference proceedings 2024 The Edi

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ADE-HGNN: Accelerating HGNNs Through Attention Disparity Exploitation dedicated hardware pruner to discard unimportant vertices. Given that the pruning overhead itself is non-negligible and cannot be amortized by conventional staged execution paradigm, an operation-fusion execution flow of HGNNs is introduced to overlap the pruning overhead while harnessing inter-sta

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Epithelium

PCTC: Hardware and Software Co-design for ,runed ,apsule Networks on ,ensor ,ores PCTC changes the sequence of matrix operations for capsule layers so that sparse operations are eliminated. PCTC further enhances the execution of CapsNets on TCs by eliminating those matrix operations that are not necessary to maintain the accuracy of the network. Quite often, CapsNets are designe

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Harnessing Data Movement Strategies to Optimize Performance-Energy Efficiency of Oil & Gas Simulatioto Hopper architectures, and NVIDIA GH200 Superchip), we show that employing the right data movement strategy can improve performance up to 62.2% and EDP up to 78.1%. We also shown that advances in the software and hardware layer of NVIDIA GPUs over generations have positively impacted the unified m

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https://doi.org/10.1007/978-94-009-0123-0ation. We discuss our design choices and the implementation of scalable parallel writing for ROOT’s RNTuple format. An evaluation of our approach shows perfect scalability only limited by storage bandwidth for a synthetic benchmark. Finally we evaluate the benefits for a real-world application of da

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