high performance computing on graphics processing units: hgpu.org

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PRAND: GPU accelerated parallel random number generation library: Using most reliable algorithms and applying parallelism of modern GPUs and CPUs

L.Yu. Barash, L.N. Shchur

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Tags: Algorithms, Computational Physics, Computer science, CUDA, Mathematical Software, nVidia, Package, Pseudo-random number generators, Tesla C2050

July 25, 2013 by hgpu

The Astrophysical Multipurpose Software Environment

F.I. Pelupessy, A. van Elteren, N. de Vries, S.L.W. McMillan, N. Drost, S.F. Portegies Zwart

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, MPI, nVidia, Package, Python

July 21, 2013 by hgpu

Image reconstruction in digital holographic microscopy on GPU

Andrej Krejcir

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Tags: Algorithms, CUDA, Image processing, Image reconstruction, Microscopy, nVidia, nVidia GeForce GTX 470, Optimization, Package, Thesis

July 21, 2013 by hgpu

GPU Computing in Economics

Eric M. Aldrich

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Tags: CUDA, Finance, nVidia, Package, Review, Tesla C2075

July 20, 2013 by hgpu

Early Experiences With The OpenMP Accelerator Model

Chunhua Liao, Yonghong Yan, Bronis R. de Supinski, Daniel J. Quinlan, Barbara Chapman

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Package, Tesla K20

July 17, 2013 by hgpu

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Dmitry Mikushin, Nikolay Likhogrud, Eddy Zheng Zhang, Christopher Bergstrom

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Tags: Code generation, Compilers, Computer science, CUDA, Fortran, nVidia, OpenACC, Package, PTX, Tesla K20

July 15, 2013 by hgpu

The CUDA Handbook: A Comprehensive Guide to GPU Programming

Nicholas Wilt

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Tags: Book, Computer science, CUDA, Image processing, N-body simulation, nVidia, Overview, Package

July 13, 2013 by hgpu

Parallel Graph Processing on Graphics Processors Made Easy

Jianlong Zhong, Bingsheng He

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Tesla C2050

July 12, 2013 by hgpu

ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

Nouredine Melab, The van Luong, Karima Boufaras, El-Ghazali Talbi

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 480, Package, Performance, Search

July 8, 2013 by hgpu

CrowdCL: Web-Based Volunteer Computing with WebCL

Tommy MacWilliam, Cris Cecka

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Tags: Computer science, Distributed computing, Java, nVidia, nVidia GeForce GT 320 M, OpenCL, Package, Tesla K20

July 7, 2013 by hgpu

A minimal model for acoustic forces on Brownian particles

F. Balboa Usabiaga, R. Delgado-Buscalioni

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Tags: Condensed matter, CUDA, Finite volume method, nVidia, Package, Soft Condensed Matter

July 3, 2013 by hgpu

Computing Strongly Connected Components with CUDA

Miroslav Stuhl

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Thesis

July 3, 2013 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

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

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

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

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high performance computing on graphics processing units: hgpu.org

PRAND: GPU accelerated parallel random number generation library: Using most reliable algorithms and applying parallelism of modern GPUs and CPUs

The Astrophysical Multipurpose Software Environment

Image reconstruction in digital holographic microscopy on GPU

GPU Computing in Economics

Early Experiences With The OpenMP Accelerator Model

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

The CUDA Handbook: A Comprehensive Guide to GPU Programming

Parallel Graph Processing on Graphics Processors Made Easy

ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

CrowdCL: Web-Based Volunteer Computing with WebCL

A minimal model for acoustic forces on Brownian particles

Computing Strongly Connected Components with CUDA

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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