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Exploiting Limited Access Distance of ODE Systems for Parallelism and Locality in Explicit Methods

Matthias Korch

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Tags: Computer science, Differential equations, nVidia, nVidia GeForce GTX 580, ODEs, OpenCL, Ordinary differential equations, Partial differential equations, PDEs

October 2, 2012 by hgpu

Multi-Moment Methods for PDEs and GPUs for Large-Scale Scientific Computations

Sarah Amalie King

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Tags: Algorithms, CUDA, Differential equations, Mathematics, nVidia, nVidia GeForce GT 640 M, Optimization, Partial differential equations, PDEs, Tesla C2050, Thesis

September 7, 2012 by hgpu

Numerical Study of Geometric Multigrid Methods on CPU–GPU Heterogeneous Computers

Chunsheng Feng, Shi Shu, Jinchao Xu, Chen-Song Zhang

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Tags: Computational Physics, CUDA, Differential equations, FFT, Heterogeneous systems, Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX 480, Partial differential equations, PDEs, Poisson equation

August 22, 2012 by hgpu

Development of a GPU-accelerated MIKE 21 Solver for Water Wave Dynamics

Peter Edward Aackermann, Peter J. Dinesen Pedersen

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Tags: Algorithms, CUDA, Differential equations, Fluid dynamics, nVidia, nVidia GeForce GTX 590, Partial differential equations, PDEs, Thesis

August 10, 2012 by hgpu

Block-Relaxation Methods for 3D Constant-Coefficient Stencils on GPUs and Multicore CPUs

Manuel Rodriguez Rodriguez, Bobby Philip, Zhen Wang, Mark Berrill

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Tags: Algorithms, Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla C2050, Tesla X2090

August 10, 2012 by hgpu

CUDA-Accelerated HD-ODETLAP: Lossy High Dimensional Gridded Data Compression

W. Randolph Franklin, You Li, Tsz-Yam Lau, Peter Fox

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

August 8, 2012 by hgpu

Fast Algorithms for the Solution of Stochastic Partial Differential Equations

Christopher William Miller

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

July 11, 2012 by hgpu

Stencil-Aware GPU Optimization of Iterative Solvers

Chekuri Choudary, Jeswin Godwin, Justin Holewinski, Deepan Karthik, Daniel Lowell, Azamat Mametjanov, Boyana Norris, Gerald Sabin, P. Sadayappan

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Tags: Computer science, CUDA, Differential equations, nVidia, Optimization, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070

July 11, 2012 by hgpu

GPU-based Assembly of Stiffness Matrices in the Parallel Multilevel Partition of Unity Method

Sebastian Kanis

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Tags: Differential equations, Mathematics, nVidia, nVidia GeForce GTX 560 Ti, Partial differential equations, PDEs, Thesis

July 5, 2012 by hgpu

Shallow Water Simulation on GPUs for Sparse Domains

Martin L. Saetra

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Tags: CUDA, Fluid dynamics, nVidia, Partial differential equations, PDEs

June 29, 2012 by hgpu

Autotuning Stencil-Based Computations on GPUs

Azamat Mametjanov, Daniel Lowell, Ching-Chen May, Boyana Norris

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Source codes

Tags: Computer science, CUDA, Differential equations, nVidia, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C1060, Tesla C2070

June 9, 2012 by hgpu

High Accuracy Gravitational Waveforms from Black Hole Binary Inspirals Using OpenCL

Justin McKennon, Gary Forrester, Gaurav Khanna

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Tags: ATI, ATI Radeon HD 7970, Differential equations, General Relativity and Quantum Cosmology, Gravitation, Gravitational waves, nVidia, OpenCL, Partial differential equations, PDEs, Physics, Tesla C2050

June 4, 2012 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

TensorCorePTX: PTX Tensor Core GEMM Exploration

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

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

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

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

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high performance computing on graphics processing units: hgpu.org

Exploiting Limited Access Distance of ODE Systems for Parallelism and Locality in Explicit Methods

Multi-Moment Methods for PDEs and GPUs for Large-Scale Scientific Computations

Numerical Study of Geometric Multigrid Methods on CPU–GPU Heterogeneous Computers

Development of a GPU-accelerated MIKE 21 Solver for Water Wave Dynamics

Block-Relaxation Methods for 3D Constant-Coefficient Stencils on GPUs and Multicore CPUs

CUDA-Accelerated HD-ODETLAP: Lossy High Dimensional Gridded Data Compression

Fast Algorithms for the Solution of Stochastic Partial Differential Equations

Stencil-Aware GPU Optimization of Iterative Solvers

GPU-based Assembly of Stiffness Matrices in the Parallel Multilevel Partition of Unity Method

Shallow Water Simulation on GPUs for Sparse Domains

Autotuning Stencil-Based Computations on GPUs

High Accuracy Gravitational Waveforms from Black Hole Binary Inspirals Using OpenCL

Recent source codes

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

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

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