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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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Source codes

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

Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model

Benjamin Block,Peter Virnau,Tobias Preis

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Tags: CUDA, GPU cluster, Ising model, Monte Carlo simulation, nVidia, Package, Physics, Tesla C1060

October 27, 2010 by hgpu

Optimization principles and application performance evaluation of a multithreaded GPU using CUDA

Shane Ryoo, Christopher I. Rodrigues, Sara S. Baghsorkhi, Sam S. Stone, David B. Kirk, Wen-mei W. Hwu

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques

October 27, 2010 by hgpu

A GPU based real-time software correlation system for the Murchison Widefield Array prototype

Randall B. Wayth,Lincoln J. Greenhill,Frank H. Briggs

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, Signal processing, Tesla C1060

October 27, 2010 by hgpu

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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high performance computing on graphics processing units: hgpu.org

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

Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model

Optimization principles and application performance evaluation of a multithreaded GPU using CUDA

A GPU based real-time software correlation system for the Murchison Widefield Array prototype

Recent source codes

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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