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A parallel algorithm for implicit depletant simulations

Jens Glaser, Andrew S. Karas, Sharon C. Glotzer

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Tags: Condensed matter, CUDA, Molecular dynamics, nVidia, Package, Physics, Soft Condensed Matter, Tesla K20, Tesla K80

August 31, 2015 by hgpu

An Asynchronous Event Communication Technique for Soft Real-Time GPGPU Applications

Alexander Vestman

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Tags: Computer science, nVidia, nVidia GeForce GTX 760, OpenGL, Thesis

August 31, 2015 by hgpu

Boosting Java Performance using GPGPUs

James Clarkson, Christos Kotselidis, Gavin Brown, Mikel Lujan

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Java, nVidia, Performance, Tesla K20

August 28, 2015 by hgpu

High-Speed Object Detection: Design, Study and Implementation of a Detection Framework using Channel Features and Boosting

Tom Runia

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Tags: ATI, ATI Radeon HD 6450, Computer science, Computer vision, Image processing, Machine learning, nVidia, nVidia Jetson TK1, nVidia Tegra, OpenCL, OpenCV, Thesis

August 28, 2015 by hgpu

Deep Convolutional Neural Networks for Smile Recognition

Patrick O. Glauner

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Tags: Computer science, CUDA, Deep learning, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K40, Thesis

August 28, 2015 by hgpu

A Parallel Algorithm to Test Chordality of Graphs

Agnieszka Lupinska

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Tags: Computer science, CUDA, Data Structures and Algorithms, Graph theory, nVidia, nVidia GeForce GTX 560 Ti, Thesis

August 28, 2015 by hgpu

CudaChain: A Practical GPU-accelerated 2D Convex Hull Algorithm

Gang Mei

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Tags: Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX 660 M, Sorting

August 27, 2015 by hgpu

gScan: Accelerating Graham Scan on the GPU

Gang Mei

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Tags: Algorithms, Computational Geometry, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX 660 M, Sorting

August 27, 2015 by hgpu

Adaptive Multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model

C. A. Navarro, Huang Wei, Youjin Deng

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, Physics, Spin Systems, Tesla K40

August 27, 2015 by hgpu

MemcachedGPU: Scaling-up Scale-out Key-value Stores

Tayler H. Hetherington, Mike O'Connor, Tor M. Aamodt

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Tags: Computer science, CUDA, Databases, Energy-efficient computing, nVidia, nVidia GeForce GTX 750 Ti, Package, Tesla K20, Tesla K40

August 27, 2015 by hgpu

Performance Evaluations of Document-Oriented Databases using GPU and Cache Structure

Shin Morishima, Hiroki Matsutani

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 980, Performance

August 24, 2015 by hgpu

Viability of Feature Detection on Sony Xperia Z3 using OpenCL

Max Danielsson, Thomas Sievert

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Tags: Android, Computer science, Computer vision, Embedded high-performance computing, nVidia, nVidia GeForce GTX 660, OpenCL, Package, Thesis

August 24, 2015 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

A parallel algorithm for implicit depletant simulations

An Asynchronous Event Communication Technique for Soft Real-Time GPGPU Applications

Boosting Java Performance using GPGPUs

High-Speed Object Detection: Design, Study and Implementation of a Detection Framework using Channel Features and Boosting

Deep Convolutional Neural Networks for Smile Recognition

A Parallel Algorithm to Test Chordality of Graphs

CudaChain: A Practical GPU-accelerated 2D Convex Hull Algorithm

gScan: Accelerating Graham Scan on the GPU

Adaptive Multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model

MemcachedGPU: Scaling-up Scale-out Key-value Stores

Performance Evaluations of Document-Oriented Databases using GPU and Cache Structure

Viability of Feature Detection on Sony Xperia Z3 using OpenCL

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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