high performance computing on graphics processing units: hgpu.org

Charles Weill, Javier Gonzalvo, Vitaly Kuznetsov, Scott Yang, Scott Yak, Hanna Mazzawi, Eugen Hotaj, Ghassen Jerfel, Vladimir Macko, Ben Adlam, Mehryar Mohri, Corinna Cortes

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Tags: Algorithms, Computer science, Machine learning, Neural networks, nVidia, Package, TensorFlow, Tesla V100

May 5, 2019 by hgpu

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

Rod Burns, John Lawson, Duncan McBain, Daniel Soutar

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Tags: Computer science, Computer vision, Deep learning, Machine learning, Neural networks, nVidia, OpenCL, Package, SYCL

April 14, 2019 by hgpu

High Performance Monte Carlo Simulation of Ising Model on TPU Clusters

Kun Yang, Yi-Fan Chen, Georgios Roumpos, Chris Colby, John Anderson

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Tags: Cloud, CUDA, Ising model, Machine learning, Monte Carlo simulation, Neural networks, nVidia, Package, Physics, Tesla V100, TPU

April 7, 2019 by hgpu

swCaffe: a Parallel Framework for Accelerating Deep Learning Applications on Sunway TaihuLight

Jiarui Fang, Liandeng Li, Haohuan Fu, Jinlei Jiang, Wenlai Zhao, Conghui He, Xin You, Guangwen Yang

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Neural networks, nVidia, OpenMPI, Package, Tesla K40

March 24, 2019 by hgpu

Accelerating ternary quantized convolutional neural networks using OpenCL for FPGA

Victor Joos de ter Beerst, Antoine Vanderschueren

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Tags: Computer science, DSP, FPGA, Neural networks, OpenCL, Package, Thesis

March 24, 2019 by hgpu

Optimizing Network Performance for Distributed DNN Training on GPU Clusters: ImageNet/AlexNet Training in 1.5 Minutes

Peng Sun, Wansen Feng, Ruobing Han, Shengen Yan, Yonggang Wen

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Tags: Computer science, CUDA, Deep learning, GPU cluster, Neural networks, nVidia, OpenMPI, Performance, Tesla P100, Tesla V100

February 24, 2019 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Accelerating Deterministic and Stochastic Binarized Neural Networks on FPGAs Using OpenCL

OpenDNN: An Open-source, cuDNN-like Deep Learning Primitive Library

FPGA Implementation of Reduced Precision Convolutional Neural Networks

Predictable GPGPU Computing in DNN-Driven Autonomous Systems

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Full-stack Optimization for Accelerating CNNs with FPGA Validation

AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

swCaffe: a Parallel Framework for Accelerating Deep Learning Applications on Sunway TaihuLight

Accelerating ternary quantized convolutional neural networks using OpenCL for FPGA

Optimizing Network Performance for Distributed DNN Training on GPU Clusters: ImageNet/AlexNet Training in 1.5 Minutes

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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