high performance computing on graphics processing units: hgpu.org

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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

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

Efficient Parallel Nonnegative Least Squares on Multicore Architectures

Yuancheng Luo, Ramani Duraiswami

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Source codes

Tags: Algorithms, Computer science, CUDA, Factorization, Nonnegative matrix factorization, nVidia, Package, Tesla C2050

November 28, 2011 by hgpu

Soft Error Resilient QR Factorization for Hybrid System

Peng Du, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Fault tolerance, Hybrid computing, Linear Algebra, nVidia, Tesla C2050, Tesla M2070

November 20, 2011 by hgpu

Hierarchical QR factorization algorithms for multi-core cluster systems

Jack Dongarra, Mathieu Faverge, Thomas Herault, Julien Langou, Yves Robert

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Tags: Algorithms, BLAS, Computer science, Factorization, Linear Algebra

November 20, 2011 by hgpu

Efficient Support for Matrix Computations on Heterogeneous Multi-core and Multi-GPU Architectures

Fengguang Song, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, BLAS, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Tesla M2070

November 20, 2011 by hgpu

A Class of Hybrid LAPACK Algorithms for Multicore and GPU Architectures

Mitch Horton, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX 480, Tesla M2070

November 8, 2011 by hgpu

A Mutable Hardware Abstraction to Replace Threads

Jan Sukenik

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Tags: Algorithms, Factorization, Image processing, MapReduce

November 3, 2011 by hgpu

Performance Portability of a GPU Enabled Factorization with the DAGuE Framework

George Bosilca, Aurelien Bouteiller, Thomas Herault, Pierre Lemarinier, Narapat Ohm Saengpatsa, Stanimire Tomov, Jack J. Dongarra

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Tags: Computer science, Factorization, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla C1060, Tesla C2050, Tesla S1070

November 3, 2011 by hgpu

A scalable hybrid algorithm based on domain decomposition and algebraic multigrid for solving partial differential equations on a cluster of CPU/GPUs

Li Luo, Chao Yang, Yubo Zhao, Xiao-Chuan Cai

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Tags: Algorithms, Computer science, CUDA, Differential equations, Factorization, FFT, Finite difference, GPU cluster, nVidia, Partial differential equations, PDEs, Tesla C1060

October 30, 2011 by hgpu

A High Performance Parallel Sparse Linear Equation Solver Using CUDA

Andrew J. Martin

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX 570, Thesis

October 17, 2011 by hgpu

A GPU-Accelerated Parallel Preconditioner for the Solution of the Boltzmann Transport Equation for Semiconductors

Karl Rupp, Ansgar Jungel, Tibor Grasser

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Tags: Boltzmann equation, Computer science, Differential equations, Factorization, nVidia, nVidia GeForce GTX 580, OpenCL, Partial differential equations, PDEs

October 10, 2011 by hgpu

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Soft Error Resilient QR Factorization for Hybrid System with GPGPU

Communication-avoiding QR decomposition for GPUs

Efficient Parallel Nonnegative Least Squares on Multicore Architectures

Soft Error Resilient QR Factorization for Hybrid System

Hierarchical QR factorization algorithms for multi-core cluster systems

Efficient Support for Matrix Computations on Heterogeneous Multi-core and Multi-GPU Architectures

A Class of Hybrid LAPACK Algorithms for Multicore and GPU Architectures

A Mutable Hardware Abstraction to Replace Threads

Performance Portability of a GPU Enabled Factorization with the DAGuE Framework

A scalable hybrid algorithm based on domain decomposition and algebraic multigrid for solving partial differential equations on a cluster of CPU/GPUs

A High Performance Parallel Sparse Linear Equation Solver Using CUDA

A GPU-Accelerated Parallel Preconditioner for the Solution of the Boltzmann Transport Equation for Semiconductors

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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