high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Multilevel Multidimensional Scaling on the GPU

Stephen F. Ingram, Stephen

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Tags: Computer science, nVidia, nVidia GeForce 7800 GS, nVidia GeForce 8800 GTX, Thesis, Visualization

November 4, 2010 by hgpu

High performance volume splatting for visualization of neurovascular data

F. Vega-Higuera, P. Hastreiter, R. Fahlbusch, G. Greiner

Tags: 3D Graphics and Realism, Computer science, Visualization

November 4, 2010 by hgpu

Fast multipole methods on graphics processors

Nail A. Gumerov, Ramani Duraiswami

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX

November 4, 2010 by hgpu

Solving Dense Linear Systems on Graphics Processors

Sergio Barrachina, Maribel Castillo, Francisco D. Igual, Rafael Mayo, Enrique S. Quintana Ort'?

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 8800 Ultra

November 4, 2010 by hgpu

Parallel Computing Experiences with CUDA

M. Garland, S. Le Grand, J. Nickolls, J. Anderson, J. Hardwick, S. Morton, E. Phillips, Yao Zhang, V. Volkov

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Tags: Computer science, CUDA, High-level Languages, nVidia

November 4, 2010 by hgpu

Issues and challenges in compiling for graphics processors

Norm Rubin

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Tags: Computer science, High-level Languages, Presentation, Review

November 4, 2010 by hgpu

GPUCV: A Framework for Image Processing Acceleration with Graphics Processors

Jean-philippe Farrugia, Patrick Horain, Erwan Guehenneux, Yannick Alusse

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Tags: Computer science, Computer vision, GLSL, Image processing, nVidia, nVidia GeForce 7800 GTX, OpenGL, Package

November 4, 2010 by hgpu

Relational joins on graphics processors

Bingsheng He, Ke Yang, Rui Fang, Mian Lu, Naga Govindaraju, Qiong Luo, Pedro Sander

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Tags: Algorithms, ATI, ATI CAL, ATI R600, ATI Stream, Computer science, CUDA, Join, nVidia, nVidia GeForce 8800 GTX, Sorting

November 4, 2010 by hgpu

Approximate Dynamic Programming and Neural Networks on Game Hardware

R. J. Meuth, D. C. Wunsch

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Tags: Computer science, Neural networks, Review

November 4, 2010 by hgpu

Artificial neural network computation on graphic process unit

Zhongwen Luo, Hongzhi Liu, Xincai Wu

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Tags: ATI, ATI Radeon 9550, Computer science, Neural networks, nVidia, nVidia GeForce 6200, nVidia GeForce 6xxx, OpenGL

November 4, 2010 by hgpu

Implementing sparse matrix-vector multiplication on throughput-oriented processors

Nathan Bell, Michael Garland

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Package, Sparse matrix

November 4, 2010 by hgpu

CuPP – A framework for easy CUDA integration

Jens Breitbart

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Tags: Computer science, CUDA, High-level Languages, nVidia, Package

November 4, 2010 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

Applications

Multilevel Multidimensional Scaling on the GPU

High performance volume splatting for visualization of neurovascular data

Fast multipole methods on graphics processors

Solving Dense Linear Systems on Graphics Processors

Parallel Computing Experiences with CUDA

Issues and challenges in compiling for graphics processors

GPUCV: A Framework for Image Processing Acceleration with Graphics Processors

Relational joins on graphics processors

Approximate Dynamic Programming and Neural Networks on Game Hardware

Artificial neural network computation on graphic process unit

Implementing sparse matrix-vector multiplication on throughput-oriented processors

CuPP – A framework for easy CUDA integration

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)