high performance computing on graphics processing units: hgpu.org

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Data-parallel Acceleration of PARSEC Black-Scholes Benchmark

August Andren, Patrik Hagernas

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Tags: Benchmarking, Computer science, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenACC, Tesla C2050, Tesla M2090

September 30, 2013 by hgpu

A GPU cluster optimized multigrid scheme for computing unsteady incompressible fluid flow

Gyorgy Tegze, Gyula I. Toth

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Tags: ATI, ATI Radeon HD 7970, Fluid dynamics, GPU cluster, Mathematics, MPI, Numerical Analysis, Numerical simulation, nVidia, nVidia GeForce GTX 680, OpenCL

September 30, 2013 by hgpu

From OpenCL to Gates: the FFT

Joao Andrade, Vitor Silva, Gabriel Falcao

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Tags: Algorithms, Computer science, FFT, FPGA, nVidia, nVidia GeForce GTX 680, OpenCL

September 28, 2013 by hgpu

Evaluation of autoparallelization toolkits for commodity graphics hardware

David Williams, Valeriu Codreanu, Po Yang, Baoquan Liu, Feng Dong, Burhan Yasar, Babak Mahdian, Alessandro Chiarini, Xia Zhao, Jos B.T.M. Roerdink

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, OpenACC, Performance

September 24, 2013 by hgpu

Optimization solutions for the segmented sum algorithmic function

Alexandru Pirjan

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

September 21, 2013 by hgpu

A GPU-based Parallel Procedure for Nonlinear Analysis of Complex Structures Using a Coupled FEM/DEM Approach

Lixiang Wang, Shihai Li, Guoxin Zhang, Zhaosong Ma, Lei Zhang

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Tags: Computer science, CUDA, FEM, Finite element method, Nonlinear analysis, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 670, nVidia GeForce GTX 680

September 18, 2013 by hgpu

Optimal Configuration of GPU Cache Memory to Maximize the Performance

Leonid Djinevski, Sime Arsenovski, Sasko Ristov, Marjan Gusev

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, Memory, nVidia, nVidia GeForce GTX 680, Performance

September 16, 2013 by hgpu

A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

Roger V. Hoang, Devyani Tanna, Laurence C. Jayet Bray, Sergiu M. Dascalu, Frederick C. Harris Jr.

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Tags: Biology, CUDA, Neural networks, Neuroscience, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Tesla C2050

September 14, 2013 by hgpu

FuzzyGPU: a fuzzy arithmetic library for GPU

David Defour, Manuel Marin

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Source codes

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package

September 13, 2013 by hgpu

Simulation and modeling of physical broadcasts

Ahmed Ahmed

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Tags: Cellular automata, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 680, Thesis

September 13, 2013 by hgpu

GPU Implementations of Object Detection using HOG Features and Deformable Models

Manato Hirabayashi, Shinpei Kato, Masato Edahiro, Kazuya Takeda, Taiki Kawano, Seiichi Mita

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 580, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Tesla K20

September 11, 2013 by hgpu

Implementation of PDE models of cardiac dynamics on GPUs using OpenCL

Christopher D. Marcotte, Roman O. Grigoriev

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Tags: Chaotic Dynamics, Computational Physics, Nonlinear Sciences, nVidia, nVidia GeForce GTX 680, OpenCL, Partial differential equations, PDEs, Physics

September 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

Data-parallel Acceleration of PARSEC Black-Scholes Benchmark

A GPU cluster optimized multigrid scheme for computing unsteady incompressible fluid flow

From OpenCL to Gates: the FFT

Evaluation of autoparallelization toolkits for commodity graphics hardware

Optimization solutions for the segmented sum algorithmic function

A GPU-based Parallel Procedure for Nonlinear Analysis of Complex Structures Using a Coupled FEM/DEM Approach

Optimal Configuration of GPU Cache Memory to Maximize the Performance

A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

FuzzyGPU: a fuzzy arithmetic library for GPU

Simulation and modeling of physical broadcasts

GPU Implementations of Object Detection using HOG Features and Deformable Models

Implementation of PDE models of cardiac dynamics on GPUs using OpenCL

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)