high performance computing on graphics processing units: hgpu.org

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High Performance Computing with GPUs

Nikita Vakulin, Riley Shaw, Timothy Livingston

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Tags: Computer science, CUDA, Differential equations, Finite element method, nVidia, Package

April 25, 2013 by hgpu

Directive-based Approach to Heterogeneous Computing

Ruyman Reyes Castro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Package, Python, Tesla C1060, Thesis

April 25, 2013 by hgpu

Solving Wave Equations on Unstructured Geometries

Andreas Klockner, Timothy Warburton, Jan S. Hesthaven

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Tags: Computer science, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX 295, OpenCL, Package, Python, Wave equation

April 23, 2013 by hgpu

GPU Scripting and Code Generation with PyCUDA

Andreas Klockner, Nicolas Pinto, Bryan Catanzaro, Yunsup Lee, Paul Ivanov, Ahmed Fasih

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Package, PyOpenCL, Python

April 23, 2013 by hgpu

SW# – GPU enabled exact alignments on genome scale

Matija Korpar, Mile Sikic

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Tags: Bioinformatics, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 570, nVidia GeForce GTX 690, Package, Sequence alignment, Smith-Waterman algorithm

April 23, 2013 by hgpu

Computer Simulation of Saturn’s Ring Structure

Cole Kendrick

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Tags: Astrophysics, ATI, ATI Radeon HD 5850, Gravitation, MPI, N-body simulation, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Tesla S2050

April 21, 2013 by hgpu

MrBayes tgMC3: A Tight GPU Implementation of MrBayes

Cheng Ling, Tsuyoshi Hamada, Jianing Bai, Xianbin Li, Douglas Chesters, Weimin Zheng, Weifeng Shi

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Tags: Algorithms, Bayesian, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package

April 18, 2013 by hgpu

A Many-core Machine Model for Designing Algorithms with Minimum Parallelism Overheads

Sardar Anisul Haque, Marc Moreno Maza, Ning Xie

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Tags: Algorithms, CUDA, Package

April 15, 2013 by hgpu

B-Calm: an Open-Source Multi-Gpu-Based 3D-FDTD with Multi-Pole Dispersion for Plasmonics

Pierre Wahl, Dany-Sebastien Ly-Gagnon, Christof Debaes, Jurgen Van Erps, Nathalie Vermeulen, David A. B. Miller, Hugo Thienpont

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Tags: Algorithms, CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, Package, Tesla C2075

April 13, 2013 by hgpu

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Yongchao Liu, Adrianto Wirawan, Bertil Schmidt

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, PTX, Sequence alignment, Smith-Waterman algorithm

April 10, 2013 by hgpu

OpenCL Fast Fourier Transform

Ruobing Li

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Tags: Computer science, FFT, nVidia, OpenCL, Package, Tesla M2070

April 9, 2013 by hgpu

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

R. Capuzzo-Dolcettaa, M. Spera

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Tags: Astrophysics, ATI, ATI Radeon HD 6970, ATI Radeon HD 7870, ATI Radeon HD 7970, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Tesla C1060, Tesla C2050, Tesla K20

April 9, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

High Performance Computing with GPUs

Directive-based Approach to Heterogeneous Computing

Solving Wave Equations on Unstructured Geometries

GPU Scripting and Code Generation with PyCUDA

SW# – GPU enabled exact alignments on genome scale

Computer Simulation of Saturn’s Ring Structure

MrBayes tgMC3: A Tight GPU Implementation of MrBayes

A Many-core Machine Model for Designing Algorithms with Minimum Parallelism Overheads

B-Calm: an Open-Source Multi-Gpu-Based 3D-FDTD with Multi-Pole Dispersion for Plasmonics

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

OpenCL Fast Fourier Transform

A Performance Comparison of Different Graphics Processing Units Running Direct N-Body Simulations

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

Most viewed papers (last 30 days)