high performance computing on graphics processing units: hgpu.org

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A Switched Dynamical System Framework for Analysis of Massively Parallel Asynchronous Numerical Algorithms

Kooktae Lee, Raktim Bhattacharya, Vijay Gupta

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Tags: Algorithms, Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla C2050

March 18, 2015 by hgpu

Extending the Gotran framework: LATEX and GPU acceleration

George Bahijevitch Bahij

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Tags: Computational modelling, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX Titan, ODEs, Ordinary differential equations, Python, Thesis

February 6, 2015 by hgpu

Nucleation Studies on Graphics Processing Units

Benjamin J. Block

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Tags: Anisotropy, ATI, ATI Radeon HD 6970, Biology, Chemistry, Differential equations, Ising model, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, OpenCL, Physics, Tesla K20, Thesis

February 6, 2015 by hgpu

Performance Analysis and Optimization of Hermite Methods on NVIDIA GPUs Using CUDA

Evan T. Dye

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Tags: Algorithms, Computer science, CUDA, Differential equations, Mathematics, nVidia, nVidia GeForce GTX 560 Ti, Partial differential equations, PDEs, Thesis

February 2, 2015 by hgpu

Productive and Efficient Computational Science Through Domain-specific Abstractions

Florian Rathgeber

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Tags: Computer science, CUDA, Differential equations, FEM, Finite element method, nVidia, OpenCL, Partial differential equations, PDEs, Thesis

February 1, 2015 by hgpu

A CUDA implementation of the High Performance Conjugate Gradient benchmark

Everett Phillips, Massimiliano Fatica

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla K20

November 29, 2014 by hgpu

A stencil-based implementation of Parareal in the C++ domain specific embedded language STELLA

Andrea Arteaga, Daniel Ruprecht, Rolf Krause

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Tags: Computer science, CUDA, Differential equations, MPI, nVidia, Partial differential equations, PDEs, Tesla K20

October 3, 2014 by hgpu

GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA

J. Spiechowicz, M. Kostur, L. Machura

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Tags: Computational Physics, CUDA, Differential equations, Monte Carlo integration, Monte Carlo simulation, nVidia, nVidia GeForce GTX 680, Physics, Stochastic simulation

September 19, 2014 by hgpu

A CUDA Back-End for the Equelle Compiler

Havard Heitlo Holm

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Tags: Compilers, Computer science, CUDA, Differential equations, Finite volume method, Heterogeneous systems, nVidia, nVidia Quadro NVS 5200 M, Package, Partial differential equations, PDEs, Tesla K40, Thesis

September 8, 2014 by hgpu

Algorithms for Solving Non-Stationary Heat Conduction Problem for Design of a Technical Device

Alexander Ayriyan, Jan Busa Jr., Eugeny E. Donets, Hovik Grigorian, Jan Pribis

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Tags: Algorithms, Computational Physics, Differential equations, Finite difference, nVidia, nVidia GeForce GTX 470, OpenCL, Partial differential equations, PDEs, Physics

August 27, 2014 by hgpu

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Moritz Schmid, Oliver Reiche, Christian Schmitt, Frank Hannig, Jurgen Teich

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Tags: ARM, Code generation, Compilers, Computational Complexity, Computer science, Differential equations, FPGA, Image processing, Partial differential equations, PDEs

August 23, 2014 by hgpu

Numerical Computations with GPUs

Volodymyr Kindratenko

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Tags: Algorithms, ATI, Book, Computer science, CUDA, Differential equations, FFT, Linear Algebra, Mathematics, Numerical simulation, nVidia, OpenCL, Pseudo-random number generators, Software Engineering

August 13, 2014 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

A Switched Dynamical System Framework for Analysis of Massively Parallel Asynchronous Numerical Algorithms

Extending the Gotran framework: LATEX and GPU acceleration

Nucleation Studies on Graphics Processing Units

Performance Analysis and Optimization of Hermite Methods on NVIDIA GPUs Using CUDA

Productive and Efficient Computational Science Through Domain-specific Abstractions

A CUDA implementation of the High Performance Conjugate Gradient benchmark

A stencil-based implementation of Parareal in the C++ domain specific embedded language STELLA

GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA

A CUDA Back-End for the Equelle Compiler

Algorithms for Solving Non-Stationary Heat Conduction Problem for Design of a Technical Device

Code Generation for High-Level Synthesis of Multiresolution Applications on FPGAs

Numerical Computations with GPUs

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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