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A Survey of General-Purpose Computation on Graphics Hardware

John D. Owens, David Luebke, Naga Govindaraju, Mark Harris, Jens Kruger, Aaron E. Lefohn, and Timothy J. Purcell

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Tags: Algorithms, Computer science, Review

November 5, 2010 by hgpu

NVIDIA Tesla: A Unified Graphics and Computing Architecture

Erik Lindholm, J. Nickolls, S. Oberman, J. Montrym

Tags: Computer science, Hardware, nVidia, Review, Tesla

November 5, 2010 by hgpu

Accelerator: using data parallelism to program GPUs for general-purpose uses

David Tarditi, Sidd Puri, Jose Oglesby

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Tags: ATI, ATI Radeon X1800, ATI Radeon X850 XT, Computer science, High-level Languages, nVidia, nVidia GeForce 6800 Ultra, nVidia GeForce 7800 GTX

November 5, 2010 by hgpu

A translation system for enabling data mining applications on GPUs

Wenjing Ma, Gagan Agrawal

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Tags: Computer science, CUDA, Data mining, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GX2

November 5, 2010 by hgpu

A Task Parallel Algorithm for Computing the Costs of All-Pairs Shortest Paths on the CUDA-Compatible GPU

Tomohiro Okuyama, Fumihiko Ino, Kenichi Hagihara

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Tags: Algorithms, All-Pairs Distance, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, Path problems

November 5, 2010 by hgpu

ECM on Graphics Cards

Daniel Bernstein, Tien-Ren Chen, Chen-Mou Cheng, Tanja Lange, Bo-Yin Yang

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Tags: Computer science, CUDA, Edwards curves, Elliptic curves, Elliptic-curve method of factorization, Factorization, Modular arithmetic, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 260, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Security

November 5, 2010 by hgpu

Solving Path Problems on the GPU

Aydin Buluc, John R. Gilbert, Ceren Budak

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce 8800 Ultra, Package, Path problems

November 5, 2010 by hgpu

Parallel search on video cards

Tim Kaldewey, Jeff Hagen, Andrea Di Blas, Eric Sedlar

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

November 5, 2010 by hgpu

A Performance Comparison of CUDA and OpenCL

Kamran Karimi, Neil G. Dickson, Firas Hamze

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Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, OpenCL, Package, Performance

November 5, 2010 by hgpu

Faster matrix-vector multiplication on GeForce 8800GTX

N. Fujimoto

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 8800 GTX

November 5, 2010 by hgpu

Exploiting frame-to-frame coherence for accelerating high-quality volume raycasting on graphics hardware

T. Klein, M. Strengert, S. Stegmaier, T. Ertl

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Tags: 3D Graphics and Realism, Computer science, Image generation, nVidia, nVidia GeForce 7800 GTX, OpenGL, Raytracing, Visualization

November 5, 2010 by hgpu

GPUTeraSort: high performance graphics co-processor sorting for large database management

Naga Govindaraju, Jim Gray, Ritesh Kumar, Dinesh Manocha

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce 6800, nVidia GeForce 6800 Ultra, nVidia GeForce 7800 GT, Sorting

November 5, 2010 by hgpu

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

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

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

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

A Survey of General-Purpose Computation on Graphics Hardware

NVIDIA Tesla: A Unified Graphics and Computing Architecture

Accelerator: using data parallelism to program GPUs for general-purpose uses

A translation system for enabling data mining applications on GPUs

A Task Parallel Algorithm for Computing the Costs of All-Pairs Shortest Paths on the CUDA-Compatible GPU

ECM on Graphics Cards

Solving Path Problems on the GPU

Parallel search on video cards

A Performance Comparison of CUDA and OpenCL

Faster matrix-vector multiplication on GeForce 8800GTX

Exploiting frame-to-frame coherence for accelerating high-quality volume raycasting on graphics hardware

GPUTeraSort: high performance graphics co-processor sorting for large database management

Recent source codes

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

ROCm's implementation of Gromacs

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

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