high performance computing on graphics processing units: hgpu.org

hgpu.org » Sparse matrix

Compressed Multiple-Row Storage Format

Zbigniew Koza, Maciej Matyka, Sebastian Szkoda, Lukasz Miroslaw

View

Tags: Algorithms, Compression, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 480, Physics, Sparse matrix, Tesla C2070

March 15, 2012 by hgpu

Efficient Performance Evaluation of Memory Hierarchy for Highly Multithreaded Graphics Processors

Sara S. Baghsorkhi, Isaac Gelado, Matthieu Delahaye, Wen-mei W. Hwu

View

Download (PDF)

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

March 2, 2012 by hgpu

An improved implementation of Preconditioned Conjugate Gradient Method on GPU

Yechen Gui, Guijuan Zhang

View

Download (PDF)

Tags: Algorithms, CUDA, Laplace and Poisson equation, nVidia, Optimization, Physics, Poisson equation, Sparse matrix

February 27, 2012 by hgpu

Multifrontal Sparse Matrix Factorization on Graphics Processing Units

Robert F. Lucas, Gene Wagenbreth, John J. Tran, Dan M. Davis

View

Download (PDF)

Tags: Computer science, CUDA, Factorization, nVidia, nVidia GeForce 8800, Sparse matrix

January 25, 2012 by hgpu

Cost Efficient PageRank Computation using GPU

Praveen K., Vamshi Krishna K., Anil Sri Harsha B., S. Balasubramanian, P.K. Baruah

View

Download (PDF)

Tags: Algorithms, Computer science, CUBLAS, CUDA, List ranking, nVidia, Sparse matrix, Tesla T20

January 24, 2012 by hgpu

A Highly Efficient GPU-CPU Hybrid Parallel Implementation of Sparse LU Factorization

Liu Li, Liu Li, Yang Guangwen

View

Download (PDF)

Tags: Algorithms, Compression, Computer science, CUDA, Factorization, nVidia, Sparse matrix, Tesla C1060

January 8, 2012 by hgpu

Optimising the DBCSR GPU Implementation

Jay Chetty

View

Download (PDF)

Tags: Algorithms, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tesla C2050, Thesis

December 31, 2011 by hgpu

Multifrontal Factorization of Sparse SPD Matrices on GPUs

Thomas George, Vaibhav Saxena, Anshul Gupta, Amik Singh, Anamitra R. Choudhury

View

Download (PDF)

Tags: Computer science, CUDA, Factorization, nVidia, Sparse matrix, Tesla S1070

December 26, 2011 by hgpu

Sparse matrix-vector multiplication on GPGPU clusters: A new storage format and a scalable implementation

Moritz Kreutzer, Georg Hager, Gerhard Wellein, Holger Fehske, Achim Basermann, Alan R. Bishop

View

Download (PDF)

Tags: Computer science, GPU cluster, nVidia, Performance, Sparse matrix, Tesla C2050, Tesla C2070

December 26, 2011 by hgpu

GPU-Accelerated Preconditioned Iterative Linear Solvers

Ruipeng Li, Yousef Saad

View

Download (PDF)

Tags: Computer science, Conjugate gradient solver, CUDA, Factorization, Linear Algebra, nVidia, Overview, Sparse matrix, Tesla C1060

December 19, 2011 by hgpu

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

Pramod Kumbhar

View

Download (PDF)

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

Sparse-Matrix-CG-Solver in CUDA

Dominik Michels

View

Download (PDF)

Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 480, Sparse matrix

December 7, 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

* * *

high performance computing on graphics processing units: hgpu.org

Compressed Multiple-Row Storage Format

Efficient Performance Evaluation of Memory Hierarchy for Highly Multithreaded Graphics Processors

An improved implementation of Preconditioned Conjugate Gradient Method on GPU

Multifrontal Sparse Matrix Factorization on Graphics Processing Units

A Highly Efficient GPU-CPU Hybrid Parallel Implementation of Sparse LU Factorization

Optimising the DBCSR GPU Implementation

Multifrontal Factorization of Sparse SPD Matrices on GPUs

Sparse matrix-vector multiplication on GPGPU clusters: A new storage format and a scalable implementation

GPU-Accelerated Preconditioned Iterative Linear Solvers

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

Sparse-Matrix-CG-Solver in CUDA

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

Most viewed papers (last 30 days)