high performance computing on graphics processing units: hgpu.org

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Fast parallel GPU-sorting using a hybrid algorithm

E. Sintorn, U. Assarsson

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Tags: Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce 8800 GTX, Sorting

October 27, 2010 by hgpu

GPU acceleration of a production molecular docking code

Bharat Sukhwani, Martin C. Herbordt

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Tags: Bioinformatics, Biophysics, Chemistry, FPGA, Molecular dynamics, nVidia, Tesla C1060

October 27, 2010 by hgpu

GPU accelerated molecular dynamics simulation of thermal conductivities

Juekuan Yang, Yujuan Wang, Yunfei Chen

Tags: Computational Physics, Molecular dynamics, nVidia, Physics

October 27, 2010 by hgpu

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

M. J. Harvey, G. Giupponi, G. De Fabritiis

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Tags: Biological Physics, Chemistry, Computational Physics, CUDA, GPU cluster, Molecular dynamics, nVidia, nVidia GeForce GTX 280, Package, Physics, Tesla C1060

October 27, 2010 by hgpu

GPU Cluster for High Performance Computing

Zhe Fan, Feng Qiu, A. Kaufman, S. Yoakum-Stover

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Tags: Computer science, Fluid dynamics, GPU cluster, Lattice Boltzmann model, nVidia, nVidia GeForce FX 5800 Ultra

October 27, 2010 by hgpu

GPU Gems 3

Hubert Nguyen

Tags: Book, Computer science, nVidia, Programming techniques

October 27, 2010 by hgpu

Simulating spin models on GPU

Martin Weigel

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Tags: CUDA, Ising model, Monte Carlo simulation, nVidia, Package, Physics, Statistical Mechanics, Tesla C1060

October 27, 2010 by hgpu

Fast fluid dynamics simulation on the GPU

Mark Harris

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Tags: Cg, Computer science, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia, Package, Programming techniques

October 27, 2010 by hgpu

Getting Started with GPU Programming

Michael A. Gray

Tags: Computer science, Macintosh, nVidia, Tutorial

October 27, 2010 by hgpu

GPU implementation of JPEG XR

Ming C. Che, Jie Liang

Tags: Algorithms, Computer science, CUDA, Image processing, nVidia

October 27, 2010 by hgpu

Monte Carlo integration on GPU

J. Kanzaki

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Tags: Computational Physics, CUDA, High Energy Physics - Experiment, High Energy Physics - Phenomenology, Monte Carlo integration, nVidia, nVidia GeForce GTX 285, Package, Physics

October 27, 2010 by hgpu

Computational advances in gravitational microlensing: a comparison of CPU, GPU, and parallel, large data codes

N. F. Bate, C. J. Fluke, B. R. Barsdell, H. Garsden, G. F. Lewis

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Tags: Astrophysics, CUDA, Gravitational lensing, Instrumentation and Methods for Astrophysics, nVidia, Tesla S1070

October 27, 2010 by hgpu

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

See all packages

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high performance computing on graphics processing units: hgpu.org

Fast parallel GPU-sorting using a hybrid algorithm

GPU acceleration of a production molecular docking code

GPU accelerated molecular dynamics simulation of thermal conductivities

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

GPU Cluster for High Performance Computing

GPU Gems 3

Simulating spin models on GPU

Fast fluid dynamics simulation on the GPU

Getting Started with GPU Programming

GPU implementation of JPEG XR

Monte Carlo integration on GPU

Computational advances in gravitational microlensing: a comparison of CPU, GPU, and parallel, large data codes

Recent source codes

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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