high performance computing on graphics processing units: hgpu.org

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clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs

Bor-Yiing Su, Kurt Keutzer

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Tags: ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sparse matrix

May 30, 2012 by hgpu

Effective Sparse Matrix Representation for the GPU Architectures

B. Neelima, Prakash S. Raghavendra

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 525 M, Optimization, Sparse matrix

May 25, 2012 by hgpu

The Linear Direct Sparse Solver on GPU for Bundle Adjustment Method

Ivaneik Ondrej, Ivan Simecek

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce GTX 570, Package, Sparse matrix, Thesis

May 19, 2012 by hgpu

Accurate CUDA Performance Modeling for Sparse Matrix-Vector Multiplication

Ping Guo, Liqiang Wang

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

May 19, 2012 by hgpu

The BiConjugate gradient method on GPUs

G. Ortega, E. M. Garzon, F. Vazquez, I. Garcia

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Tags: Algorithms, Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

May 15, 2012 by hgpu

High-performance sparse matrix-vector multiplication on GPUs for structured grid computations

Jeswin Godwin, Justin Holewinski, P. Sadayappan

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla C2050

April 25, 2012 by hgpu

Exposing Fine-Grained Parallelism in Algebraic Multigrid Methods

Nathan Bell, Steven Dalton, Luke N. Olson

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Tags: Algorithms, CUDA, Mathematics, nVidia, Package, Sparse matrix, Tesla C2050

April 11, 2012 by hgpu

Adaptive Row-grouped CSR Format for Storing of Sparse Matrices on GPU

Martin Heller, Tomas Oberhuber

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla C2070

March 27, 2012 by hgpu

Accelerating Sparse Matrix Vector Multiplication on Many-Core GPUs

Weizhi Xu, Zhiyong Liu, Dongrui Fan, Shuai Jiao, Xiaochun Ye, Fenglong Song, Chenggang Yan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 295, Performance, Sparse matrix

March 21, 2012 by hgpu

Generating optimal CUDA sparse matrix-vector product implementations for evolving GPU hardware

Ahmed H. El Zein, Alistair P. Rendell

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 295, Performance, Sparse matrix, Tesla S2050

March 19, 2012 by hgpu

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Dimitar Lukarski

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Tags: Algorithms, Computer science, CUDA, Differential equations, Factorization, FEM, Finite difference, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla M1060, Tesla S1070, Thesis

March 16, 2012 by hgpu

Iterative Statistical Kernels on Contemporary GPUs

Thilina Gunarathne, Bimalee Salpitikorala, Arun Chauhan, Geoffrey Fox

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Tags: Algorithms, Cloud, Clustering, Computer science, nVidia, OpenCL, Sparse matrix, Tesla C1060, Tesla C2070, Tesla M2050

March 15, 2012 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs

Effective Sparse Matrix Representation for the GPU Architectures

The Linear Direct Sparse Solver on GPU for Bundle Adjustment Method

Accurate CUDA Performance Modeling for Sparse Matrix-Vector Multiplication

The BiConjugate gradient method on GPUs

High-performance sparse matrix-vector multiplication on GPUs for structured grid computations

Exposing Fine-Grained Parallelism in Algebraic Multigrid Methods

Adaptive Row-grouped CSR Format for Storing of Sparse Matrices on GPU

Accelerating Sparse Matrix Vector Multiplication on Many-Core GPUs

Generating optimal CUDA sparse matrix-vector product implementations for evolving GPU hardware

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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