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From Pixels to Torques: Policy Learning using Deep Dynamical Convolutional Networks

John-Alexander M. Assael

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Tags: CNN, Computer science, CUDA, Deep learning, Lua, Machine learning, nVidia, Package, Tesla K40, Thesis

September 26, 2015 by hgpu

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

Hasmik Osipyan, Martin Krulis, Stephane Marchand-Maillet

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Tags: Algorithms, Computer science, CUDA, Machine learning, Multidimensional scaling, nVidia, nVidia GeForce GT 740 M, Pattern recognition

September 26, 2015 by hgpu

A GPU accelerated Barnes-Hut Tree Code for FLASH4

Gunther Lukat, Robi Banerjee

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Tags: Astrophysics, CUDA, Fortran, Gravitation, Instrumentation and Methods for Astrophysics, nVidia, Package, Python, Tesla C2075

September 26, 2015 by hgpu

Efficient Simulation Techniques for Large-Scale Applications

Jen-Cheng Huang

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Tags: Analytical model, Computer science, CUDA, nVidia, nVidia Quadro 6000, Performance, Thesis

September 26, 2015 by hgpu

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Vlad Olaru, Mihai Florea, Cristian Sminchisescu

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Tags: Algorithms, Computer science, Computer vision, CUDA, Matlab, nVidia, nVidia GeForce GTX Titan Black, Package, Tesla K40

September 24, 2015 by hgpu

Parallel Decompression of Seismic Data on GPU Using a Lifting Wavelet Algorithm

Jairo A. Castelar, Carlos A. Angulo, Carlos A. Fajardo

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Tags: Algorithms, CUDA, Earth and Space Sciences, GPU cluster, nVidia, nVidia GeForce GTX 660, Wavelet

September 19, 2015 by hgpu

Efficient Kernel Fusion Techniques for Massive Video Data Analysis on GPGPUs

Asif M Adnan, Sridhar Radhakrishnan, Suleyman Karabuk

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Tags: Algorithms, CUDA, Image processing, Neuroscience, nVidia, nVidia GeForce GTX 750 Ti, Tesla C1060, Tesla K20

September 17, 2015 by hgpu

gSLICr: SLIC superpixels at over 250Hz

Carl Yuheng Ren, Victor Adrian Prisacariu, Ian D Reid

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Tags: Clustering, Computer science, Computer vision, CUDA, nVidia, OpenCV, Package

September 17, 2015 by hgpu

Scalable Metropolis Monte Carlo for simulation of hard shapes

Joshua A. Anderson, M. Eric Irrgang, Sharon C. Glotzer

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Tags: Benchmarking, Chemistry, Condensed matter, CUDA, Monte Carlo simulation, nVidia, Physics, Soft Condensed Matter, Tesla K20

September 17, 2015 by hgpu

linalg: Matrix Computations in Apache Spark

Reza Bosagh Zadeh, Xiangrui Meng, Burak Yavuz, Aaron Staple, Li Pu, Shivaram Venkataraman, Evan Sparks, Alexander Ulanov, Matei Zaharia

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, Linear Algebra, Machine learning, Matrix multiplication, nVidia, Package, Scala, Tesla M2050

September 15, 2015 by hgpu

Refinements in Syntactic Parsing

David Hall

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Tags: Computer science, CUDA, Machine learning, NLP, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, Scala, Thesis

September 15, 2015 by hgpu

Efficient Convolutional Neural Networks for Pixelwise Classification on Heterogeneous Hardware Systems

Fabian Tschopp

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Tags: AMD FirePro W9100, Artificial intelligence, ATI, Caffe, CNN, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Thesis

September 15, 2015 by hgpu

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

Inside VOLT: Designing an Open-Source GPU Compiler (Tool)

SciDef: Automated Definition Extraction from Scientific Literature

SciDef: Automating Definition Extraction from Academic Literature with Large Language Models

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

Programming

From Pixels to Torques: Policy Learning using Deep Dynamical Convolutional Networks

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

A GPU accelerated Barnes-Hut Tree Code for FLASH4

Efficient Simulation Techniques for Large-Scale Applications

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Parallel Decompression of Seismic Data on GPU Using a Lifting Wavelet Algorithm

Efficient Kernel Fusion Techniques for Massive Video Data Analysis on GPGPUs

gSLICr: SLIC superpixels at over 250Hz

Scalable Metropolis Monte Carlo for simulation of hard shapes

linalg: Matrix Computations in Apache Spark

Refinements in Syntactic Parsing

Efficient Convolutional Neural Networks for Pixelwise Classification on Heterogeneous Hardware Systems

Recent source codes

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

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