high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

FPGA vs. GPU for sparse matrix vector multiply

Yan Zhang, Yasser H. Shalabi, Rishabh Jain, Krishna K. Nagar, Jason D. Bakos

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Tags: Computer science, CUDA, FPGA, Linear Algebra, nVidia, nVidia GeForce GTX 260, Sparse matrix

March 18, 2011 by hgpu

A Quantitative Performance Analysis Model for GPU Architectures

Yao Zhang, John D. Owens

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Tags: Computer science, CUDA, Hardware Architecture, Linear Algebra, nVidia, nVidia GeForce GTX 285, Optimization

March 13, 2011 by hgpu

GEMM on a GPU

Jonathan Monette

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro FX 5800, Poster

March 12, 2011 by hgpu

The GPU as a high performance computational resource

Tor Dokken, Trond R Hagen, Jon M Hjelmervik

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Tags: Computer science, Linear Algebra, Mathematical Software, Partial differential equations, PDEs, Review

March 11, 2011 by hgpu

Dense Matrix Algebra on the GPU

Adam Moravanszky

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Tags: ATI, ATI Radeon 9500 Pro, ATI Radeon 9700 Pro, Computer science, DirectX, Linear Algebra, Matrix multiplication

February 24, 2011 by hgpu

Accelerating the ANSYS Direct Sparse Solver with GPUs

Geraud P. Krawezik, Gene Poole

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Tags: Computer science, CUDA, Linear Algebra, Mixed precision, nVidia, Sparse direct solvers, Tesla C1060

February 22, 2011 by hgpu

Energy efficiency of mixed precision iterative refinement methods using hybrid hardware platforms

Hartwig Anzt, Bjorn Rocker, Vincent Heuveline

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Tags: Computer science, Energy-efficient computing, Linear Algebra, Mixed precision, nVidia, Tesla C1060, Tesla S1070

February 22, 2011 by hgpu

High Performance Relevance Vector Machine on GPUs

Depeng Yang, Getao Liang, David D. Jenkins, Gregory D. Peterson, and Husheng Li

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Tags: Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 480, OpenCL

February 19, 2011 by hgpu

Power-aware Performance of Mixed Precision Linear Solvers for FPGAs and GPGPUs

JunKyu Lee, Junqing Sun, Gregory D. Peterson, Robert J. Harrison, Robert J. Hinde

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Tags: Computer science, Energy-efficient computing, FPGA, Linear Algebra, Mixed precision, nVidia, Performance, Tesla C1060

February 18, 2011 by hgpu

OpenCL Evaluation for Numerical Linear Algebra Library Development

Peng Du, Piotr Luszczek, Jack Dongarra

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Tags: ATI Radeon HD 5870, Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 280, OpenCL, Performance, Tesla C2050

February 17, 2011 by hgpu

Dynamically scheduled Cholesky factorization on multicore architectures with GPU accelerators

Emmanuel Agullo, Cedric Augonnet, Jack Dongarra, Hatem Ltaief, Raymond Namyst, Jean Roman, Samuel Thibault, Stanimire Tomov

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro FX 5800, Task scheduling

February 17, 2011 by hgpu

Automatically Tuned Dense Linear Algebra for Multicore+GPU

Xing Fu, Xue Li, Gregory D. Peterson

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Source codes

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

February 17, 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

FPGA vs. GPU for sparse matrix vector multiply

A Quantitative Performance Analysis Model for GPU Architectures

GEMM on a GPU

The GPU as a high performance computational resource

Dense Matrix Algebra on the GPU

Accelerating the ANSYS Direct Sparse Solver with GPUs

Energy efficiency of mixed precision iterative refinement methods using hybrid hardware platforms

High Performance Relevance Vector Machine on GPUs

Power-aware Performance of Mixed Precision Linear Solvers for FPGAs and GPGPUs

OpenCL Evaluation for Numerical Linear Algebra Library Development

Dynamically scheduled Cholesky factorization on multicore architectures with GPU accelerators

Automatically Tuned Dense Linear Algebra for Multicore+GPU

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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