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Stochastic Differential Equations simulation using GPU

Narayana Darapaneni, Prakalp Somawanshi, Meghana Joshi

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Tags: Algorithms, Computer science, CUDA, Differential equations, Finance, Monte Carlo simulation, nVidia, nVidia GeForce GTX 275, Pseudo-random number generators, Stochastic simulation

February 7, 2012 by hgpu

An OpenCL implementation for the solution of TDSE on GPU and CPU architectures

Cathal O'Broin, Lampros A. A. Nikolopoulos

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Tags: Algorithms, ATI, ATI FirePro V7800, Computational Physics, Differential equations, nVidia, ODEs, OpenCL, Ordinary differential equations, Physics, Quantum Physics, Tesla S1070

January 31, 2012 by hgpu

A GPU-Based Implementation of Differential Evolution for Solving the Gene Regulatory Network Model Inference Problem

Luis E. Ramirez-Chavez, Carlos A. Coello Coello, Eduardo Rodriguez-Tello

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Tags: Bioinformatics, Biology, CUDA, Differential equations, Differential evolution, nVidia, nVidia GeForce GTX 460, Optimization

January 23, 2012 by hgpu

Scientific Computation on Graphics Processing Unit using CUDA

Pradip Narendrakumar Panchal

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Tags: Computer science, CUDA, Differential equations, FDTD, Finite difference, Finite-difference time-domain, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 280, Partial differential equations, PDEs, Thesis

January 23, 2012 by hgpu

GPGPU calculations of gas thermodynamic quantities

Igor Mracka, Peter Somora, Tibor Zacik

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Tags: CUDA, Differential equations, Fluid dynamics, nVidia, nVidia GeForce GTX 570, Tesla C2050

January 21, 2012 by hgpu

An Adaptive Step Size GPU ODE Solver for Simulating the Electric Cardiac Activity

Victor M. Garcia, A. Liberos, A.M. Climent, A. Vidal, J. Millet, A. Gonzalez

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Tags: CUDA, Differential equations, Heart, Medicine, nVidia, ODEs, Ordinary differential equations

January 17, 2012 by hgpu

Acceleration of real-life stencil codes on GPUs

Youcef Barigou

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Tags: Algorithms, Computer science, CUDA, Differential equations, Electrodynamics, FDTD, Finite-difference time-domain, Maxwell's equations, nVidia, Optimization

January 2, 2012 by hgpu

Numerical solution of PDEs with hybrid and heterogeneous computing models

Markus Hegland

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Tags: Algorithms, CUDA, Differential equations, Fluid dynamics, Heterogeneous systems, nVidia, nVidia GeForce GTX 295, Partial differential equations, PDEs, Physics, Plasma physics, Review

December 23, 2011 by hgpu

Water Surface Animation using Damped Wave Equation and CUDA Acceleration

Gennadiy Nikishkov, Yohei Nishidate

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Tags: CUDA, Differential equations, Finite difference, Fluid dynamics, nVidia, nVidia Quadro FX 3800, Wave equation

December 14, 2011 by hgpu

Multi-Science Applications with Single Codebase – GAMER – for Massively Parallel Architectures

Hemant Shukla, Hsi-Yu Schive, Tak-Pong Woo, Tzihong Chiueh

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Tags: Algorithms, Astrophysics, Benchmarking, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Physics, Rendering, Tesla C2050

December 10, 2011 by hgpu

Playdoh: A lightweight Python library for distributed computing and optimisation

Cyrille Rossant, Bertrand Fontaine, Dan F.M. Goodman

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Source codes

Tags: Computer science, CUDA, Differential equations, Distributed computing, Monte Carlo simulation, nVidia, nVidia GeForce GTX 295, Package, Partial differential equations, PDEs, Python

December 10, 2011 by hgpu

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

Pramod Kumbhar

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Tags: ATI, ATI FireStream, Computer science, CUDA, Differential equations, GPU cluster, nVidia, OpenCL, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Thesis

December 8, 2011 by hgpu

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

pyATF: Constraint-Based Auto-Tuning in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

Checkpoint/Restore tool

CRIUgpu: Transparent Checkpointing of GPU-Accelerated Workloads

KernelBench: Can LLMs Write GPU Kernels?

KernelBench: Can LLMs Write Efficient GPU Kernels?

An MLIR-based toolchain for AMD AI Engine-enabled devices

Seamless acceleration of Fortran intrinsics via AMD AI engines

Forecasting time series with constraints

See all packages

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high performance computing on graphics processing units: hgpu.org

Stochastic Differential Equations simulation using GPU

An OpenCL implementation for the solution of TDSE on GPU and CPU architectures

A GPU-Based Implementation of Differential Evolution for Solving the Gene Regulatory Network Model Inference Problem

Scientific Computation on Graphics Processing Unit using CUDA

GPGPU calculations of gas thermodynamic quantities

An Adaptive Step Size GPU ODE Solver for Simulating the Electric Cardiac Activity

Acceleration of real-life stencil codes on GPUs

Numerical solution of PDEs with hybrid and heterogeneous computing models

Water Surface Animation using Damped Wave Equation and CUDA Acceleration

Multi-Science Applications with Single Codebase – GAMER – for Massively Parallel Architectures

Playdoh: A lightweight Python library for distributed computing and optimisation

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

Recent source codes

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

Checkpoint/Restore tool

KernelBench: Can LLMs Write GPU Kernels?

An MLIR-based toolchain for AMD AI Engine-enabled devices

Forecasting time series with constraints

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