high performance computing on graphics processing units: hgpu.org

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Single stream parallelization of generalized LSTM-like RNNs on a GPU

Kyuyeon Hwang, Wonyong Sung

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Tags: Algorithms, Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K40

March 22, 2015 by hgpu

Fast Sparse Matrix Multiplication on GPU

Lukas Polok, Viorela Ila, Pavel Smrz

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Sorting, Sparse matrix, Tesla K40

March 18, 2015 by hgpu

Accelerating Direction-Optimized Breadth First Search on Hybrid Architectures

Scott Sallinen, Abdullah Gharaibeh, Matei Ripeanu

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla K40

March 18, 2015 by hgpu

Stochastic Gradient Descent on GPUs

Rashid Kaleem, Sreepathi Pai, Keshav Pingali

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Tags: Algorithms, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla K40

February 22, 2015 by hgpu

NUPAR: A Benchmark Suite for Modern GPU Architectures

Yash Ukidave, Fanny Nina Paravecino, Leiming Yu, Charu Kalra, Amir Momeni, Zhongliang Chen, Nick Materise, Brett Daley, Perhaad Mistry, David Kaeli

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Tags: ATI, ATI Radeon HD 7970, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Package, Tesla C2070, Tesla K40

February 13, 2015 by hgpu

Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations

Simon Perkins, Patrick Maraism, Jonathan Zwart, Iniyan Natarajan, Oleg Smirnov

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Tags: Astrophysics, Bayesian, Computer science, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Package, Python, Tesla K40

February 2, 2015 by hgpu

Gunrock: A High-Performance Graph Processing Library on the GPU

Yangzihao Wang, Andrew Davidson, Yuechao Pan, Yuduo Wu, Andy Riffel, John D. Owens

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Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla K40

January 23, 2015 by hgpu

Batched Matrix Computations on Hardware Accelerators Based on GPUs

Azzam Haidar, Tingxing Dong, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, nVidia, Tesla K40

January 15, 2015 by hgpu

Hierarchical DAG Scheduling for Hybrid Distributed Systems

Wei Wu, Aurelien Bouteiller, George Bosilca, Mathieu Faverge, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla K40, Tesla M2090

January 5, 2015 by hgpu

GPU-based acceleration of free energy calculations in solid state physics

Michal Januszewski, Andrzej Ptok, Dawid Crivelli, Bartlomiej Gardas

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Tags: Algorithms, Computational Physics, CUDA, Fortran, nVidia, Physics, Tesla K40

January 2, 2015 by hgpu

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Nicolas Vasilache, Jeff Johnson, Michael Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun

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Tags: Algorithms, CNN, Computer science, CUDA, FFT, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Package, Tesla K40

December 26, 2014 by hgpu

Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification

Hongsheng Li, Rui Zhao, Xiaogang Wang

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, Tesla K40

December 16, 2014 by hgpu

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Single stream parallelization of generalized LSTM-like RNNs on a GPU

Fast Sparse Matrix Multiplication on GPU

Accelerating Direction-Optimized Breadth First Search on Hybrid Architectures

Stochastic Gradient Descent on GPUs

NUPAR: A Benchmark Suite for Modern GPU Architectures

Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations

Gunrock: A High-Performance Graph Processing Library on the GPU

Batched Matrix Computations on Hardware Accelerators Based on GPUs

Hierarchical DAG Scheduling for Hybrid Distributed Systems

GPU-based acceleration of free energy calculations in solid state physics

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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