high performance computing on graphics processing units: hgpu.org

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Fine-grained Parallel ILU Preconditioners with Fill-ins for Multi-core CPUs and GPUs

Vincent Heuveline, Dimitar Lukarski and Jan-philipp Weiss

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Tags: Algorithms, Computer science, FEM, Finite element method, Heterogeneous systems, Numerical simulation, OpenCL, Package, Partial differential equations, PDEs

October 4, 2011 by hgpu

Real-time, accurate depth of field using anisotropic diffusion and programmable graphics cards

Marcelo Bertalmio, Pere Fort, Daniel Sanchez-Crespo

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Tags: 3D Graphics and Realism, Algorithms, Computer science, Differential equations, nVidia, nVidia GeForce FX 5950 Ultra, Partial differential equations, PDEs, Rendering

September 1, 2011 by hgpu

Potential contribution of CNN-based solving of stiff ODEs and PDEs to enabling real-time Computational Engineering

J.C. Chedjou, K. Kyamakya, U.A. Khan, M.A. Latif

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Tags: Cellular neural networks, CNN, Computational Engineering, Computer science, Differential equations, DSP, FPGA, Maxwell's equations, Neural networks, ODEs, Optimization, Ordinary differential equations, Partial differential equations, PDEs

August 2, 2011 by hgpu

Near-real-time simulations of biolelectric activity in small mammalian hearts using graphical processing units

E.J. Vigmond, P.M. Boyle, L.J. Leon, G. Plank

Tags: Biology, Heart, Medicine, ODEs, Ordinary differential equations, Partial differential equations, PDEs

July 27, 2011 by hgpu

High-Performance Reverse Time Migration on GPU

Javier Cabezas, Mauricio Araya-Polo, Isaac Gelado, Nacho Navarro, Enric Morancho, Jose M. Cela

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Tags: CUDA, Earth and Space Sciences, Finite difference, Geoscience, nVidia, nVidia GeForce GTX 280, Partial differential equations, PDEs

July 22, 2011 by hgpu

Improving the Performance of the Sparse Matrix Vector Product with GPUs

F. Vazquez, G. Ortega, J.J. Fernandez, E.M. Garzon

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Partial differential equations, PDEs, Sparse matrix

July 17, 2011 by hgpu

A multi-platform linear algebra toolbox for finite element solvers on heterogeneous clusters

V. Heuveline, C. Subramanian, D. Lukarski, J.-P. Weiss

Tags: Finite element method, Heterogeneous systems, Linear Algebra, Mathematics, Partial differential equations, PDEs

June 14, 2011 by hgpu

A framework for parallel unstructured grid applications on GPUs

Mike Giles

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Tags: Code generation, Computer science, CUDA, GPU cluster, MPI, nVidia, OpenCL, OpenMP, Package, PDEs, Presentation

June 5, 2011 by hgpu

Solving Parabolic Problems Using Multithread and GPU

Chih-Wei Hsieh, Sheng-Hsiu Kuo, Fang-An Kuo, Chau-Yi Chou

Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GT 200, Partial differential equations, PDEs

April 26, 2011 by hgpu

Automatically Tuning Sparse Matrix-Vector Multiplication for GPU Architectures

Alexander Monakov, Anton Lokhmotov, Arutyun Avetisyan

Tags: Computer science, Partial differential equations, PDEs, Sparse matrix

April 21, 2011 by hgpu

GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations

Vaclav Simek, Radim Dvorak, Frantisek Zboril, Vladimir Drabek

Tags: CUDA, Diffusion equation, Earth and Space Sciences, nVidia, Partial differential equations, PDEs

April 3, 2011 by hgpu

Scandalously Parallelizable Mesh Generation

David Bortz, Andrew Christlieb

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Tags: Algorithms, Mathematics, Numerical Analysis, Partial differential equations, PDEs

March 29, 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

Fine-grained Parallel ILU Preconditioners with Fill-ins for Multi-core CPUs and GPUs

Real-time, accurate depth of field using anisotropic diffusion and programmable graphics cards

Potential contribution of CNN-based solving of stiff ODEs and PDEs to enabling real-time Computational Engineering

Near-real-time simulations of biolelectric activity in small mammalian hearts using graphical processing units

High-Performance Reverse Time Migration on GPU

Improving the Performance of the Sparse Matrix Vector Product with GPUs

A multi-platform linear algebra toolbox for finite element solvers on heterogeneous clusters

A framework for parallel unstructured grid applications on GPUs

Solving Parabolic Problems Using Multithread and GPU

Automatically Tuning Sparse Matrix-Vector Multiplication for GPU Architectures

GPU Accelerated Solver of Time-Dependent Air Pollutant Transport Equations

Scandalously Parallelizable Mesh Generation

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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