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Titlebook: Languages and Compilers for Parallel Computing; 33rd International W Barbara Chapman,José Moreira Conference proceedings 2022 Springer Natu

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Edward Stow,Riku Murai,Sajad Saeedi,Paul H. J. Kelly
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An Affine Scheduling Framework for Integrating Data Layout and Loop Transformationsed manner. To efficiently explore the broader optimization space, we build analytical memory and computational cost models that are parameterized with a range of machine features including hardware parallelism, cache and TLB locality, and vectorization. Experimental results obtained on 12-core Intel
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Optimized Code Generation for Deep Neural NetworksorFlow, TensorFlow with Intel MKL-DNN, TensorFlow with XLA, PyTorch with MKL-DNN and MXNet with MKL-DNN. The results show that a compiler-based approach for the BN operator can increase performance on CPU architectures.
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Thermal-Aware Compilation of Spiking Neural Networks to Neuromorphic Hardwareonsumption. We propose a novel technique to map neurons and synapses of SNN-based machine learning workloads to neuromorphic hardware. We make two novel contributions. First, we formulate a detailed thermal model for a crossbar in a neuromorphic hardware incorporating workload dependency, where the
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the econometric model indicated that the main beneficiaries of the 1990 contract were the practices which had expanded over the 1989–92 period, re-structured the GPs’ partnership and made use of managerial skills by employing a practice manager; those practices also had larger lists in 1992 and rel
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