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Implementation of PDE models of cardiac dynamics on GPUs using OpenCL

Christopher D. Marcotte, Roman O. Grigoriev

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Tags: Chaotic Dynamics, Computational Physics, Nonlinear Sciences, nVidia, nVidia GeForce GTX 680, OpenCL, Partial differential equations, PDEs, Physics

September 9, 2013 by hgpu

Dawn of GPU Era-Potentials of Chaos Theory

Saurabh Maniktala, Anisha Goel, A. B. Patki, R. C. Meharde

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Tags: Chaotic Dynamics, Computer science, CUDA, nVidia, nVidia GeForce 9400 GT

October 24, 2012 by hgpu

On the numerical solution of chaotic dynamical systems using extend precision floating point arithmetic and very high order numerical methods

Scott A. Sarra, Clyde Meador

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Tags: Chaotic Dynamics, CUDA, Extended precision, nVidia, nVidia GeForce GTX 280, ODEs, Ordinary differential equations, Package, Physics

December 15, 2011 by hgpu

Mapping the Arnold web with a graphic processing unit

A. Seibert, S. Denisov, Alexey V. Ponomarev, P. Hanggi

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Tags: Chaotic Dynamics, Computational Physics, CUDA, Nonlinear Sciences, nVidia, Physics, Tesla M2050

December 3, 2011 by hgpu

GPU Accelerated Numerical Solutions to Chaotic PDEs

J.R. Seaton, J.C Sprott

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Tags: Algorithms, Chaotic Dynamics, Differential equations, Nonlinear Sciences, nVidia, Partial differential equations, PDEs, Physics, Tesla C870

December 1, 2011 by hgpu

Odeint – Solving ordinary differential equations in C++

Karsten Ahnert, Mario Mulansky

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Tags: Chaotic Dynamics, Computational Physics, Computer science, CUDA, Differential equations, Mathematical Software, nVidia, ODEs, Ordinary differential equations, Package

October 18, 2011 by hgpu

Mapping the Arnold web with a GPU-supercomputer

A. Seibert, S. Denisov, Alexey V. Ponomarev, P. Hanggi

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Tags: Chaotic Dynamics, Computational Physics, CUDA, Nonlinear Sciences, nVidia, Physics, Tesla M2050

July 22, 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

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high performance computing on graphics processing units: hgpu.org

Implementation of PDE models of cardiac dynamics on GPUs using OpenCL

Dawn of GPU Era-Potentials of Chaos Theory

On the numerical solution of chaotic dynamical systems using extend precision floating point arithmetic and very high order numerical methods

Mapping the Arnold web with a graphic processing unit

GPU Accelerated Numerical Solutions to Chaotic PDEs

Odeint – Solving ordinary differential equations in C++

Mapping the Arnold web with a GPU-supercomputer

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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