high performance computing on graphics processing units: hgpu.org

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Accelerating non-linear image registration with GPUs

Paul Ross

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Tags: CUDA, Image processing, Image registration, nVidia, Tesla C2050, Thesis

December 12, 2011 by hgpu

Gyrokinetic Toroidal Simulations on Leading Multi-and Manycore HPC Systems

Kamesh Madduri, Khaled Z. Ibrahim, Samuel Williams, Eun-Jin Im, Stephane Ethier, John Shalf, Leonid Oliker

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Tags: CUDA, Fortran, Hybrid computing, MPI, nVidia, OpenMP, Optimization, Particle-in-cell methods, Physics, Plasma physics, Tesla C2050

December 11, 2011 by hgpu

Achieving High Throughput Sequencing with Graphics Processing Units

Su Chen, Chaochao Zhang, Feng Shen, Ling Bai, Hai Jiang, Damir Herman

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Tags: Algorithms, Bioinformatics, Computer science, CUDA, nVidia, Sequence alignment, Tesla C2050

December 10, 2011 by hgpu

Multi-Science Applications with Single Codebase – GAMER – for Massively Parallel Architectures

Hemant Shukla, Hsi-Yu Schive, Tak-Pong Woo, Tzihong Chiueh

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Tags: Algorithms, Astrophysics, Benchmarking, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Physics, Rendering, Tesla C2050

December 10, 2011 by hgpu

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

Pramod Kumbhar

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Tags: ATI, ATI FireStream, Computer science, CUDA, Differential equations, GPU cluster, nVidia, OpenCL, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Thesis

December 8, 2011 by hgpu

GPU Implementation of the Keccak Hash Function Family

Pierre-Louis Cayrel, Gerhard Hoffmann, Michael Schneider

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 295, Package, Security, Tesla C2050

December 7, 2011 by hgpu

GPU-based solution of Continuous Time Markov Chains using CUSP

Nicholas Dingle

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Tags: CUDA, Mathematics, nVidia, Probability, Tesla C2050

December 7, 2011 by hgpu

Soft Error Resilient QR Factorization for Hybrid System with GPGPU

Peng Du, Piotr Luszczek, Stan Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Hybrid computing, nVidia, Tesla C2050, Tesla M2070

December 5, 2011 by hgpu

Parallel Quadtree Coding of Large-Scale Raster Geospatial Data on GPGPUs

Jianting Zhang, Simin You, Le Gruenwald

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Tags: CUDA, Data parallelism, Earth and Space Sciences, Geoscience, nVidia, Sensing, Tesla C2050

December 5, 2011 by hgpu

Communication-avoiding QR decomposition for GPUs

Michael Anderson, Grey Ballard, James Demmel, Kurt Keutzer

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Tags: Algorithms, Computer science, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX 480, Tesla C2050

December 4, 2011 by hgpu

Global Point Mascon Models for Simple, Accurate and Parallel Geopotential Computation

Ryan P. Russell, Nitin Arora

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Tags: Earth and Space Sciences, Geoscience, nVidia, nVidia GeForce GTX 465, Tesla C2050

December 4, 2011 by hgpu

Programming hybrid systems with implicit memory based synchronization

Jens Breitbart

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Tags: Algorithms, Computer science, CUDA, Hybrid computing, nVidia, nVidia GeForce GTX 480, Package, Tesla C2050

December 3, 2011 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

Accelerating non-linear image registration with GPUs

Gyrokinetic Toroidal Simulations on Leading Multi-and Manycore HPC Systems

Achieving High Throughput Sequencing with Graphics Processing Units

Multi-Science Applications with Single Codebase – GAMER – for Massively Parallel Architectures

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

GPU Implementation of the Keccak Hash Function Family

GPU-based solution of Continuous Time Markov Chains using CUSP

Soft Error Resilient QR Factorization for Hybrid System with GPGPU

Parallel Quadtree Coding of Large-Scale Raster Geospatial Data on GPGPUs

Communication-avoiding QR decomposition for GPUs

Global Point Mascon Models for Simple, Accurate and Parallel Geopotential Computation

Programming hybrid systems with implicit memory based synchronization

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)