high performance computing on graphics processing units: hgpu.org

Programming

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Fully accelerating quantum Monte Carlo simulations of real materials on GPU clusters

Kenneth P. Esler, Jeongnim Kim, David M. Ceperley

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Tags: CUDA, GPU cluster, Monte Carlo simulation, MPI, nVidia, Package, Physics, QMC, Tesla T10

February 18, 2011 by hgpu

Sparse systems solving on GPUs with GMRES

Raphael Couturier, Stephane Domas

Tags: Computer science, CUBLAS, CUDA, nVidia, Sparse linear iterative solvers, Sparse matrix

February 18, 2011 by hgpu

Accelerating Power Flow studies on Graphics Processing Unit

Jaideep Singh, Ipseeta Aruni

Tags: Computer science, CUDA, nVidia, Performance

February 18, 2011 by hgpu

Performance Comparison of Cholesky Decomposition on GPUs and FPGAs

Depeng Yang, Junqing Sun, JunKu Lee, Getao Liang, David D. Jenkins, Gregory D. Peterson, and Husheng Li

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Tags: Computer science, FPGA, Matrix decomposition, nVidia, nVidia GeForce GTX 480, OpenCL, Performance

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

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

GPU Accelerated Particle System for Triangulated Surface Meshes

Brad Peterson, Manasi Datar, Mary Hall, Ross Whitaker

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Particle simulation, Triangular meshes

February 17, 2011 by hgpu

Medium-Grained Functions Mapping using Modern GPUs

Jiri Filipovic, Jan Fousek

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, Performance

February 17, 2011 by hgpu

Simulations of Large Membrane Regions using GPU-enabled Computations – Preliminary Results

Narayan Ganesan, Michela Taufer, Sandeep Patel

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Tags: Chemistry, CUDA, Membrane computing, Molecular dynamics, nVidia, Performance

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

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

Pei-Hung Lin, Jagan Jayaraj, and Paul R. Woodward

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Tags: Cell processor, Code generation, Compilers, Computer science, CUDA, Fortran, High-level Languages, Memory model, nVidia, Tesla C1060

February 17, 2011 by hgpu

Accelerating Algorithms on GPUs in SCIRun: the Conjugate Gradient Case Study

Devon Yablonski, Miriam Leeser, Dana Brooks

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

February 17, 2011 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

Programming

Fully accelerating quantum Monte Carlo simulations of real materials on GPU clusters

Sparse systems solving on GPUs with GMRES

Accelerating Power Flow studies on Graphics Processing Unit

Performance Comparison of Cholesky Decomposition on GPUs and FPGAs

OpenCL Evaluation for Numerical Linear Algebra Library Development

Evaluating one-sided programming models for GPU cluster computations

GPU Accelerated Particle System for Triangulated Surface Meshes

Medium-Grained Functions Mapping using Modern GPUs

Simulations of Large Membrane Regions using GPU-enabled Computations – Preliminary Results

Dynamically scheduled Cholesky factorization on multicore architectures with GPU accelerators

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

Accelerating Algorithms on GPUs in SCIRun: the Conjugate Gradient Case Study

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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