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Sparse regularization in MRI iterative reconstruction using GPUs

Yue Zhuo, Bradley Sutton, Xiao-Long Wu, Justin Haldar, Wen-mei Hwu, Zhipei Liang

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Tags: CUDA, Image processing, Image reconstruction, MRI, nVidia, nVidia GeForce GTX 280, Sparse matrix

January 24, 2011 by hgpu

Efficient Sparse Matrix-Vector Multiplication on CUDA

Nathan Bell and Michael Garland

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 280, Sparse matrix

January 24, 2011 by hgpu

FSAI preconditioned CG algorithm combined with GPU technique for the finite element analysis of electromagnetic scattering problems

K. Xu, D. Z. Ding, Z. H. Fan, R. S. Chen

Tags: Conjugate gradient solver, Electrodynamics, Finite element method, Sparse matrix

January 14, 2011 by hgpu

Taming irregular EDA applications on GPUs

Yangdong S. Deng, Bo D. Wang, Shuai Mu

Tags: CAD, Computer science, Programming techniques, Sparse matrix

January 13, 2011 by hgpu

Efficient gather and scatter operations on graphics processors

Bingsheng He, Naga K. Govindaraju, Qiong Luo, Burton Smith

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800, Search, Sorting, Sparse matrix

January 6, 2011 by hgpu

GPU based sparse grid technique for solving multidimensional options pricing PDEs

Abhijeet Gaikwad, Ioane Muni Toke

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Tags: Computational finance, CUDA, Finance, Linear Algebra, nVidia, Sparse matrix, Tesla C870

December 28, 2010 by hgpu

Concurrent Number Cruncher: An Efficient Sparse Linear Solver on the GPU

Luc Buatois, Guillaume Caumon, Bruno Levy

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Tags: 3D Graphics and Realism, ATI, ATI Radeon X1900, Computer science, Linear Algebra, OpenGL, Sparse matrix

December 22, 2010 by hgpu

New Row-grouped CSR format for storing the sparse matrices on GPU with implementation in CUDA

Tomas Oberhuber, Atsushi Suzuki, Jan Vacata

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Sparse matrix

December 13, 2010 by hgpu

Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy

Alfredo Buttari, Jack Dongarra, Jakub Kurzak, Piotr Luszczek, Stanimir Tomov

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Tags: Algorithms, Computer science, Linear Algebra, Mixed precision, Sparse matrix

December 12, 2010 by hgpu

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Mingliang Wang, Hector Klie, Manish Parashar, Hari Sudan

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla T10P

November 27, 2010 by hgpu

Exact Sparse Matrix-Vector Multiplication on GPU’s and Multicore Architectures

Brice Boyer, Jean-Guillaume Dumas, Pascal Giorgi

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Source codes

Tags: Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GTX 280, OpenMP, Package, Sparse matrix, Symbolic Computation

November 11, 2010 by hgpu

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

Antonio Wendell De Oliveira Rodrigues, Frederic Guyomarch, Yvonnick Le Menach, Jean-Luc Dekeyser

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Tags: Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla C870

November 9, 2010 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

Sparse regularization in MRI iterative reconstruction using GPUs

Efficient Sparse Matrix-Vector Multiplication on CUDA

FSAI preconditioned CG algorithm combined with GPU technique for the finite element analysis of electromagnetic scattering problems

Taming irregular EDA applications on GPUs

Efficient gather and scatter operations on graphics processors

GPU based sparse grid technique for solving multidimensional options pricing PDEs

Concurrent Number Cruncher: An Efficient Sparse Linear Solver on the GPU

New Row-grouped CSR format for storing the sparse matrices on GPU with implementation in CUDA

Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Exact Sparse Matrix-Vector Multiplication on GPU’s and Multicore Architectures

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

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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