Partial differential equations | Page 13

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Mixing Multi-Core CPUs and GPUs for Scientific Simulation Software

K.A. Hawick, A. Leist, and D.P. Playne

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Tags: Cell processor, Computer science, CUDA, Data parallelism, Finite difference, nVidia, nVidia GeForce GTX 295, OpenCL, Partial differential equations, PDEs, Playstation, Pseudo-random number generators

February 14, 2011 by hgpu

Automated and parallel code generation for finite-differencing stencils with arbitrary data types

K.A. Hawick and D.P. Playne

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Tags: Code generation, Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 295, Partial differential equations, PDEs

February 13, 2011 by hgpu

Comparison of GPU Architectures for Asynchronous Communication with Finite-Differencing Applications

D.P. Playne, K.A. Hawick

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Tags: Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Partial differential equations, PDEs

February 13, 2011 by hgpu

Weak execution ordering – exploiting iterative methods on many-core GPUs

Jianmin Chen, Zhuo Huang, Feiqi Su, Jih-Kwon Peir, Jeff Ho, Lu Peng

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Tags: Computer vision, CUDA, Image processing, nVidia, Partial differential equations, PDEs, Tesla C1060

January 26, 2011 by hgpu

Acceleration of cardiac tissue simulation with graphic processing units

Daisuke Sato, Yuanfang Xie, James Weiss, Zhilin Qu, Alan Garfinkel, Allen Sanderson

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Tags: CUDA, Medicine, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 9800 GX2, ODEs, Ordinary differential equations, Partial differential equations, PDEs

December 15, 2010 by hgpu

Low viscosity flow simulations for animation

Jeroen Molemaker, Jonathan M. Cohen, Sanjit Patel, Jonyong Noh

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Tags: 3D Graphics and Realism, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce 8800 GTX, Partial differential equations, PDEs

December 12, 2010 by hgpu

Simulation of atmospheric binary mixtures based on two-fluid model

S. Liu, Z. Wang, Z. Gong, Q. Peng

Tags: Earth and Space Sciences, Fluid dynamics, Navier-Stokes equations, NSEs, Partial differential equations

December 12, 2010 by hgpu

Towards Accelerated Computation of Atmospheric Equations Using CUDA

Vaclav Simek, Radim Dvorak, Frantisek Zboril, Jiri Kunovsky

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

November 27, 2010 by hgpu

SBLOCK: A Framework for Efficient Stencil-Based PDE Solvers on Multi-core Platforms

Tobias Brandvik, Graham Pullan

Tags: Computer science, CUDA, nVidia, Partial differential equations, PDEs

November 20, 2010 by hgpu

Parallel Implementation on GPUs of ADI Finite Difference Methods for Parabolic PDEs with Applications in Finance

Duy M. Dang, Christina Christara, Kenneth R. Jackson

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Tags: CUDA, Finance, Finite difference, nVidia, Partial differential equations, PDEs, Tesla T10

November 19, 2010 by hgpu

A framework for exploring numerical solutions of advection-reaction-diffusion equations using a GPU-based approach

Allen Sanderson, Miriah Meyer, Robert Kirby, Chris Johnson

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Tags: Cg, Diffusion equation, Mathematics, nVidia, nVidia GeForce 6800 Ultra, Partial differential equations, PDEs

November 8, 2010 by hgpu

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

See all packages

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high performance computing on graphics processing units: hgpu.org

Mixing Multi-Core CPUs and GPUs for Scientific Simulation Software

Automated and parallel code generation for finite-differencing stencils with arbitrary data types

Comparison of GPU Architectures for Asynchronous Communication with Finite-Differencing Applications

Weak execution ordering – exploiting iterative methods on many-core GPUs

Acceleration of cardiac tissue simulation with graphic processing units

Low viscosity flow simulations for animation

Simulation of atmospheric binary mixtures based on two-fluid model

Towards Accelerated Computation of Atmospheric Equations Using CUDA

SBLOCK: A Framework for Efficient Stencil-Based PDE Solvers on Multi-core Platforms

Parallel Implementation on GPUs of ADI Finite Difference Methods for Parabolic PDEs with Applications in Finance

A framework for exploring numerical solutions of advection-reaction-diffusion equations using a GPU-based approach

Recent source codes

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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