high performance computing on graphics processing units: hgpu.org

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Evaluating one-sided programming models for GPU cluster computations

Jeff R. Hammond and A. Eugene DePrince III

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Tags: Chemistry, Computer science, CUDA, GPU cluster, Matrix multiplication, nVidia, Tesla T10

February 17, 2011 by hgpu

Static Memory Access Pattern Analysis on a Massively Parallel GPU

Byunghyun Jang, Dana Schaa, Perhaad Mistry, and David Kaeli

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Tags: Computer science, Matrix multiplication, Memory model, nVidia, nVidia GeForce 8800 Ultra, nVidia GeForce GTX 285, OpenCL, Optimization

February 16, 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

An Improved Magma Gemm For Fermi Graphics Processing Units

Rajib Nath, Stanimire Tomov, Jack Dongarra

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Source codes

Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Package, Tesla C2050

January 23, 2011 by hgpu

Automatic tuning matrix multiplication performance on graphics hardware

Changhao Jiang, M. Snir

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Tags: Brook, Computer science, DirectX, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 6800 GT, nVidia GeForce 6800 Ultra, nVidia GeForce FX 5800 Ultra, nVidia Quadro FX 3400, OpenGL

November 30, 2010 by hgpu

Fast Conjugate Gradients with Multiple GPUs

Ali Cevahir, Akira Nukada, Satoshi Matsuoka

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Tags: Computer science, Conjugate gradient solver, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 8800 GTS

November 27, 2010 by hgpu

A Note on Auto-tuning GEMM for GPUs

Yinan Li, Jack Dongarra, Stanimire Tomov

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

November 27, 2010 by hgpu

Numerical linear algebra on emerging architectures: The PLASMA and MAGMA projects

Emmanuel Agullo, Jim Demmel, Jack Dongarra, Bilel Hadri, Jakub Kurzak, Julien Langou, Hatem Ltaief, Piotr Luszczek, Stanimire Tomov

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Tags: Algorithms, Computer science, Linear Algebra, Matrix multiplication

November 27, 2010 by hgpu

Molecular structural mechanics approach to carbon nanotubes on graphics processing units

Xia Jian-ming, Wei De-min

Tags: Matrix multiplication, Molecular modeling, Physics

November 25, 2010 by hgpu

Fast matrix multiplies using graphics hardware

E. Scott Larsen, David Mcallister

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Tags: Computer science, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 3, OpenGL

November 24, 2010 by hgpu

Power Efficient Large Matrices Multiplication by Load Scheduling on Multi-core and GPU Platform with CUDA

DaQi Ren, Reiji Suda

Tags: Computer science, CUDA, Energy-efficient computing, Matrix multiplication, nVidia

November 8, 2010 by hgpu

Solving Path Problems on the GPU

Aydin Buluc, John R. Gilbert, Ceren Budak

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce 8800 Ultra, Package, Path problems

November 5, 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

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high performance computing on graphics processing units: hgpu.org

Evaluating one-sided programming models for GPU cluster computations

Static Memory Access Pattern Analysis on a Massively Parallel GPU

Efficient Sparse Matrix-Vector Multiplication on CUDA

An Improved Magma Gemm For Fermi Graphics Processing Units

Automatic tuning matrix multiplication performance on graphics hardware

Fast Conjugate Gradients with Multiple GPUs

A Note on Auto-tuning GEMM for GPUs

Numerical linear algebra on emerging architectures: The PLASMA and MAGMA projects

Molecular structural mechanics approach to carbon nanotubes on graphics processing units

Fast matrix multiplies using graphics hardware

Power Efficient Large Matrices Multiplication by Load Scheduling on Multi-core and GPU Platform with CUDA

Solving Path Problems on the 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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