high performance computing on graphics processing units: hgpu.org

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Evaluating Performance Portability of Accelerator Programming Models using SPEC ACCEL 1.2 Benchmarks

Swen Boehm, Swaroop Pophale, Veronica G. Vergara Larrea, Oscar Hernandez

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Tags: Benchmarking, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenACC, OpenCL, OpenMP, performance portability, Tesla K20, Tesla V100

September 23, 2018 by hgpu

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Jacob Lambert, Seyong Lee, Jungwon Kim, Jeffrey S. Vetter, Allen D. Malony

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Tags: Computer science, FPGA, nVidia, OpenACC, OpenCL, Tesla K40

July 1, 2018 by hgpu

Fast Simulation of Large-Scale Floods Based on GPU Parallel Computing

Qiang Liu, Yi Qin, Guodong Li

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Tags: Benchmarking, Earth and Space Sciences, Numerical simulation, nVidia, OpenACC, Tesla K20

May 5, 2018 by hgpu

MACC: An OpenACC Transpiler for Automatic Multi-GPU Use

Kazuaki Matsumura, Mitsuhisa Sato, Taisuke Boku, Artur Podobas, Satoshi Matsuoka

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Tags: Compilers, Computer science, nVidia, OpenACC, OpenMP, Tesla P100

March 22, 2018 by hgpu

New High Performance GPGPU Code Transformation Framework Applied to Large Production Weather Prediction Code

Michel Muller, Takayuki Aoki

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Tags: CUDA, Earth and Space Sciences, Fortran, nVidia, OpenACC, Tesla P100, Weather prediction, Weather Prediction Model

March 3, 2018 by hgpu

POMPEI: Programming with OpenMP4 for Exascale Investigations

Jack Dongarra, Azzam Haidar, Oscar Hernandez, Stanimire Tomov, Manjunath Gorentla Venkata

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Tags: Computer science, Intel Xeon Phi, Linear Algebra, nVidia, OpenACC, OpenMP, Programming techniques, Tesla M2090

December 15, 2017 by hgpu

GPU Parallelization for Unstructured Sparse Matrix Problems with OpenMP 4.5 and OpenACC

Stefan Rosenberger, Gundolf Haase

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 1060, OpenACC, OpenMP, Sparse matrix

November 21, 2017 by hgpu

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Wim Vanderbauwhede, Gavin Davidson

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Tags: Compilers, Computer science, Fortran, Heterogeneous systems, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP, Package

November 16, 2017 by hgpu

Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures

Przemyslaw Stpiczynski

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Tags: Algorithms, Computer science, Intel Xeon Phi, Monte Carlo integration, nVidia, OpenACC, OpenMP, Pseudo-random number generators, Tesla K40

November 12, 2017 by hgpu

Best Practice Guide – GPGPU

Momme Allalen, Vali Codreanu, Nevena Ilieva-Litova, Alan Gray, Anders Sjostrom, Volker Weinberg

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Tags: Computer science, CUDA, OpenACC, OpenCL, OpenMP, Review

November 12, 2017 by hgpu

Comparison of Parallelisation Approaches, Languages, and Compilers for Unstructured Mesh Algorithms on GPUs

G. D. Balogh, I. Z. Reguly, G. R. Mudalige

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, OpenACC, OpenMP, Performance, Tesla K40, Tesla P100

November 7, 2017 by hgpu

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

Michel Muller, Takayuki Aoki

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Tags: Earth and Space Sciences, Fortran, nVidia, OpenACC, OpenMP, Package, Tesla K20, Tesla P100, Weather prediction, Weather Prediction Model

October 29, 2017 by hgpu

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

CL-kmeans: Efficient k-Means in OpenCL

Efficient and Scalable k-Means on GPUs

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

pyJac: a Python package that generates source code used to analytically calculate chemical kinetics Jacobian matrices

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Integer sorting on multicore

A study of integer sorting on multicores

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high performance computing on graphics processing units: hgpu.org

Evaluating Performance Portability of Accelerator Programming Models using SPEC ACCEL 1.2 Benchmarks

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Fast Simulation of Large-Scale Floods Based on GPU Parallel Computing

MACC: An OpenACC Transpiler for Automatic Multi-GPU Use

New High Performance GPGPU Code Transformation Framework Applied to Large Production Weather Prediction Code

POMPEI: Programming with OpenMP4 for Exascale Investigations

GPU Parallelization for Unstructured Sparse Matrix Problems with OpenMP 4.5 and OpenACC

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures

Best Practice Guide – GPGPU

Comparison of Parallelisation Approaches, Languages, and Compilers for Unstructured Mesh Algorithms on GPUs

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

Recent source codes

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

CL-kmeans: Efficient k-Means in OpenCL

Doctor AI: Interpretable Deep Learning for Modeling Electronic Health Records

pyJac: a Python package that generates source code used to analytically calculate chemical kinetics Jacobian matrices

CUTLASS: CUDA Templates for Linear Algebra Subroutines

Integer sorting on multicore

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International Conference on Image, Video and Signal Processing (IVSP), 2019

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International Joint Conference on Robotics, Automation and Mechatronics (JCRAM), 2018

International Joint Conference on Robotics and Artificial Intelligence (JCRAI), 2018

International Joint Conference on Computer Vision and Pattern Recognition (CCVPR), 2018