high performance computing on graphics processing units: hgpu.org

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Design and evaluation of a parallel k-nearest neighbor algorithm on CUDA-enabled GPU

Shenshen Liang, Ying Liu, Cheng Wang, Liheng Jian

Tags: Computer science, CUDA, Nearest neighbour, nVidia

May 4, 2011 by hgpu

Parallel AES algorithm for fast Data Encryption on GPU

Deguang Le, Jinyi Chang, Xingdou Gou, Ankang Zhang, Conglan Lu

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Tags: AES, Computer science, CUDA, nVidia, nVidia GeForce GTS 250, Security

May 4, 2011 by hgpu

High performance predictable histogramming on GPUs: exploring and evaluating algorithm trade-offs

Cedric Nugteren, Gert J. van den Braak, Henk Corporaal, Bart Mesman

Tags: Computer science, CUDA, Image processing, nVidia

May 4, 2011 by hgpu

Graphics hardware & GPU computing: past, present, and future

David Luebke

Tags: Computer science, CUDA, Games, nVidia, nVidia GeForce GTX 280, Review

May 4, 2011 by hgpu

Accelerating scientific applications using GPU’s

M. Taher

Tags: Bioinformatics, Biology, Computer science, CUDA, FFT, nVidia, Security, Sequence alignment

May 3, 2011 by hgpu

GPU Implementation of Extended Gaussian Mixture Model for Background Subtraction

Vu Pham, Phong Vo, Vu Thanh Hung, Le Hoai Bac

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Source codes

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 9600 GT, Package

May 3, 2011 by hgpu

Parallel grid-based recursive Bayesian estimation using GPU for real-time autonomous navigation

Tomonari Furukawa, Benjamin Lavis, Hugh F. Durrant-Whyte

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Tags: Bayesian, Computer science, nVidia, nVidia GeForce 8800 GTS

May 3, 2011 by hgpu

Statistical power modeling of GPU kernels using performance counters

Hitoshi Nagasaka, Naoya Maruyama, Akira Nukada, Toshio Endo, Satoshi Matsuoka

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 285

May 3, 2011 by hgpu

GPU-based elastic-object deformation for enhancement of existing haptic applications

Cristian J. Luciano, P. Pat Banerjee, Silvio H. R. Rizzi

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Tags: Algorithms, Computed tomography, CT, Image processing, Magnetic resonance imaging, MRI, nVidia, nVidia Quadro FX 3400, OpenGL, Virtual reality

May 3, 2011 by hgpu

Realtime Simulation of Burning Solids on GPU with CUDA

Jian Zhu, Youquan Liu, Kai Bao, Yuanzhang Chang, Enhua Wu

Tags: CUDA, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia

May 3, 2011 by hgpu

GPU-CPU multi-core for real-time signal processing

Saraju P. Mohanty

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Tags: nVidia, nVidia GeForce FX 5200, OpenGL, Rendering, Signal processing

May 3, 2011 by hgpu

Acceleration of large-scale FDTD simulations on high performance GPU clusters

C. Ong, M. Weldon, D. Cyca, M. Okoniewski

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Tags: Electrodynamics, FDTD, Finite-difference time-domain, GPU cluster, nVidia, Tesla S870

May 3, 2011 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

Design and evaluation of a parallel k-nearest neighbor algorithm on CUDA-enabled GPU

Parallel AES algorithm for fast Data Encryption on GPU

High performance predictable histogramming on GPUs: exploring and evaluating algorithm trade-offs

Graphics hardware & GPU computing: past, present, and future

Accelerating scientific applications using GPU’s

GPU Implementation of Extended Gaussian Mixture Model for Background Subtraction

Parallel grid-based recursive Bayesian estimation using GPU for real-time autonomous navigation

Statistical power modeling of GPU kernels using performance counters

GPU-based elastic-object deformation for enhancement of existing haptic applications

Realtime Simulation of Burning Solids on GPU with CUDA

GPU-CPU multi-core for real-time signal processing

Acceleration of large-scale FDTD simulations on high performance GPU clusters

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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