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KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian Foster, Zhao Zhang

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia A100, nVidia DGX-A100, Package, Tesla V100

July 11, 2021 by hgpu

Performance analysis and optimization of highly diverging algorithms on GPUs

Hendrik Schwanekamp

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Tags: CUDA, nVidia, nVidia A100, nVidia GeForce GTX 1080, Performance, Physics

May 2, 2021 by hgpu

AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning

Yuhan Liu, Saurabh Agarwal, Shivaram Venkataraman

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Tags: Computer science, Deep learning, Machine learning, NLP, nVidia, nVidia A100, Package, Python, Tesla P100

February 7, 2021 by hgpu

NVIDIA SimNet: an AI-accelerated multi-physics simulation framework

Oliver Hennigh, Susheela Narasimhan, Mohammad Amin Nabian, Akshay Subramaniam, Kaustubh Tangsali, Max Rietmann, Jose del Aguila Ferrandis, Wonmin Byeon, Zhiwei Fang, Sanjay Choudhry

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Tags: cfd, CUDA, Fluid dynamics, Linear Algebra, Machine learning, Neural networks, nVidia, nVidia A100, Partial differential equations, PDEs, Physics, Tesla V100, Video

December 20, 2020 by hgpu

Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse Linear Algebra Computations

Yuhsiang Mike Tsai, Terry Cojean, Hartwig Anzt

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia A100, Performance, Sparse, Sparse matrix

August 23, 2020 by hgpu

Face.evoLVe: High-Performance Face Recognition Library based on PyTorch & PaddlePaddle

Face.evoLVe: A High-Performance Face Recognition Library

OpenCLDecompiler

A method for decompilation of AMD GCN kernels to OpenCL

PULP: a (Parallel Ultra-Low-Power) open-source multi-core computing platform

DNN is not all you need: Parallelizing Non-Neural ML Algorithms on Ultra-Low-Power IoT Processors

StreamBlocks: A compiler for heterogeneous dataflow computing

APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores

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high performance computing on graphics processing units: hgpu.org

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

Performance analysis and optimization of highly diverging algorithms on GPUs

AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning

NVIDIA SimNet: an AI-accelerated multi-physics simulation framework

Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse Linear Algebra Computations

Recent source codes

Face.evoLVe: High-Performance Face Recognition Library based on PyTorch & PaddlePaddle

OpenCLDecompiler

PULP: a (Parallel Ultra-Low-Power) open-source multi-core computing platform

StreamBlocks: A compiler for heterogeneous dataflow computing

Bempp-cl: a boundary element method library

futhark-stencil-benchmarks

POCL: Portable Computing Language

K-FAC: PyTorch Distributed K-FAC Preconditioner

pystencils

APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores

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Featured events

9th International Workshop on OpenCL and SYCL, 2021

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020