high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

QR decomposition on GPUs

Andrew Kerr, Dan Campbell, Mark Richards

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix decomposition, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280

February 5, 2011 by hgpu

Real-Time Prediction of Brain Shift Using Nonlinear Finite Element Algorithms

Grand Roman Joldes, Adam Wittek, Mathieu Couton, Simon K. Warfield and Karol Miller

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Tags: CUDA, Finite element method, Image processing, Image registration, Medicine, MRI, nVidia

February 5, 2011 by hgpu

GPGPU-compatible archive based stochastic ranking evolutionary algorithm (G-ASREA) for multi-objective optimization

Deepak Sharma, Pierre Collet

Tags: Algorithms, Computer science, Evolutionary Computations

February 4, 2011 by hgpu

Accelerating total variation regularization for matrix-valued images on GPUs

Maryam Moazeni, Alex A. T. Bui, Majid Sarrafzadeh

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia Quadro FX 5600

February 4, 2011 by hgpu

Lattice Based Volumetric Global Illumination

Feng Qiu, Fang Xu, Zhe Fan, Neophytou Neophytos, Arie Kaufman, Klaus Mueller

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Tags: 3D Graphics and Realism, Algorithms, Computer science, nVidia, nVidia GeForce 8800 GTX, Rendering, Visualization

February 4, 2011 by hgpu

QUDA programming for staggered quarks

Steven Gottlieb, Guochun Shi, Aaron Torok, Volodymyr Kindratenko

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package, Physics, QCD, Tesla C1060, Tesla C2050, Tesla S1070

February 4, 2011 by hgpu

Phoenix: A Runtime Environment for High Performance Computing on Chip Multiprocessors

Avneesh Pant, Hassan Jafri, Volodymyr Kindratenko

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Tags: Algorithms, Computer science, MPI

February 4, 2011 by hgpu

QP: A Heterogeneous Multi-Accelerator Cluster

Michael Showerman, Jeremy Enos, Avneesh Pant, Volodymyr Kindratenko, Craig Steffen, Robert Pennington, Wen-mei Hwu

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Tags: Computer science, CUDA, FPGA, GPU cluster, nVidia, nVidia Quadro FX 5600, Review

February 4, 2011 by hgpu

On testing GPU memory for hard and soft errors

Guochun Shi, Jeremy Enos, Michael Showerman, Volodymyr Kindratenko

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Tags: Computer science, CUDA, Hardware Architecture, Memory, nVidia, Package, Tesla C1060, Tesla S1070

February 3, 2011 by hgpu

Quantifying the Impact of GPUs on Performance and Energy Efficiency in HPC Clusters

J. Enos, C. Steffen, J. Fullop, M. Showerman, G. Shi, K. Esler, V. Kindratenko, J. Stone, J. Phillips

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Tags: Computer science, CUDA, Energy-efficient computing, GPU cluster, nVidia, Performance

February 3, 2011 by hgpu

MILC on GPUs

Gushing Shi, Steven Gottlieb, Volodymyr Kindratenko

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Tags: Conjugate gradient solver, CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, Physics, QCD

February 3, 2011 by hgpu

3I: A tool for visualizing and processing in parallel 2D & 3D images

Juan P.D'Amato, Maria V.Cifuentes, Pablo Lotito

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Tags: 3D Graphics and Realism, CUDA, Image processing, nVidia, nVidia GeForce GTX 285

February 3, 2011 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

QR decomposition on GPUs

Real-Time Prediction of Brain Shift Using Nonlinear Finite Element Algorithms

GPGPU-compatible archive based stochastic ranking evolutionary algorithm (G-ASREA) for multi-objective optimization

Accelerating total variation regularization for matrix-valued images on GPUs

Lattice Based Volumetric Global Illumination

QUDA programming for staggered quarks

Phoenix: A Runtime Environment for High Performance Computing on Chip Multiprocessors

QP: A Heterogeneous Multi-Accelerator Cluster

On testing GPU memory for hard and soft errors

Quantifying the Impact of GPUs on Performance and Energy Efficiency in HPC Clusters

MILC on GPUs

3I: A tool for visualizing and processing in parallel 2D & 3D images

Recent source codes

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

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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