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Importance of Data Loading Pipeline in Training Deep Neural Networks

Mahdi Zolnouri, Xinlin Li, Vahid Partovi Nia

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Package, Tesla V100

May 10, 2020 by hgpu

Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning

Weile Jia, Han Wang, Mohan Chen, Denghui Lu, Jiduan Liu, Lin Lin, Roberto Car, Weinan E, Linfeng Zhang

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Tags: Computational Physics, CUDA, HPC, Machine learning, Mixed precision, Molecular dynamics, Molecular simulation, MPI, nVidia, OpenMP, Physics, Tesla V100

May 10, 2020 by hgpu

Tools for GPU Computing – Debugging and Performance Analysis of Heterogenous HPC Applications

Michael Knobloch, Bernd Mohr

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Tags: Computer science, CUDA, HPC, nVidia, OpenACC, OpenCL, Performance

May 3, 2020 by hgpu

Tools for Reduced Precision Computation: A Survey

Stefano Cherubin, Giovanni Agosta

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Tags: Approximate computing and storage, Computer science, CUDA, HPC, Mixed precision, nVidia, OpenCL, Precision, survey

May 3, 2020 by hgpu

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy

Denghui Lu, Han Wang, Mohan Chen, Jiduan Liu, Lin Lin, Roberto Car, Weinan E, Weile Jia, Linfeng Zhang

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Tags: Computational Physics, CUDA, Heterogeneous systems, Molecular dynamics, Neural networks, nVidia, Package, Physics, Python, Tesla V100

May 3, 2020 by hgpu

cuda-kat: The CUDA Kernel Author’s Toolkit

Eyal Rozenberg

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Tags: cpp, CUDA, library, nVidia, Package

May 2, 2020 by epk

Automatic Parallelization for Heterogeneous Embedded Systems

Rokiatou Diarra

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro M 2000 M, nVidia Tegra TX1, OpenACC, OpenCL, Thesis

April 26, 2020 by hgpu

Accelerating Winograd Convolutions using Symbolic Computation and Meta-programming

Arya Mazaheri, Tim Beringer, Matthew Moskewicz, Felix Wolf, Ali Jannesari

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Tags: AMD Radeon RX 580, ATI, Code generation, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Performance, performance portability, Symbolic Computation, Vulkan

April 26, 2020 by hgpu

GEVO: GPU Code Optimization using Evolutionary Computation

Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu

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Tags: Computer science, CUDA, Evolutionary Computations, Machine learning, Neural and Evolutionary Computing, nVidia, Package, PTX, Tesla P100

April 26, 2020 by hgpu

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

Tsung-Wei Huang, Dian-Lun Lin, Yibo Lin, Chun-Xun Lin

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, Package, Performance

April 26, 2020 by hgpu

OpenCL-Darknet: implementation and optimization of OpenCL-based deep learning object detection framework

Yongbon Koo, Sunghoon Kim, Young-guk Ha

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Tags: AMD Radeon R7, Computer science, CUDA, Deep learning, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 1050 Ti, OpenCL, Package

April 19, 2020 by hgpu

FlexTensor: An Automatic Schedule Exploration and Optimization Framework for Tensor Computation on Heterogeneous System

Size Zheng, Yun Liang, Shuo Wang, Renze Chen, Kaiwen Sheng

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Tags: Algorithms, Computer science, CUDA, FPGA, Heterogeneous systems, Machine learning, nVidia, OpenCL, Package, Tesla V100

April 19, 2020 by hgpu

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

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high performance computing on graphics processing units: hgpu.org

Importance of Data Loading Pipeline in Training Deep Neural Networks

Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning

Tools for GPU Computing – Debugging and Performance Analysis of Heterogenous HPC Applications

Tools for Reduced Precision Computation: A Survey

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy

cuda-kat: The CUDA Kernel Author’s Toolkit

Automatic Parallelization for Heterogeneous Embedded Systems

Accelerating Winograd Convolutions using Symbolic Computation and Meta-programming

GEVO: GPU Code Optimization using Evolutionary Computation

Cpp-Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System at Scale

OpenCL-Darknet: implementation and optimization of OpenCL-based deep learning object detection framework

FlexTensor: An Automatic Schedule Exploration and Optimization Framework for Tensor Computation on Heterogeneous System

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Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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