high performance computing on graphics processing units: hgpu.org

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GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian Movement

Sankha Baran Dutta

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Tags: Ant colony optimization, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, Thesis

June 5, 2014 by hgpu

Mapping parallel programs to heterogeneous multi-core systems

Dominik Grewe

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Tags: Algorithms, ATI, ATI Radeon HD 7990, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Thesis

June 5, 2014 by hgpu

A Comparative Study of Game Tree Searching Methods

Ahmed A. Elnaggar, Mostafa Abdel Aziem, Mahmoud Gadallah, Hesham El-Deeb

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Tags: Algorithms, Computer science, CUDA, nVidia, Search

June 5, 2014 by hgpu

Adventures in the microlensing cloud: large datasets, eResearch tools, and GPUs

Georgios Vernardos, Christopher J Fluke

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Package, Tesla C2070, Tesla M2090

June 5, 2014 by hgpu

Utilizing Graphics Processing Units for Rapid Facial Recognition Using Video Input

Charles J. Gala

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Pattern recognition, Tesla C2050, Thesis

June 3, 2014 by hgpu

Design Tools for Accelerating Development and Usage of Multi-Core Computing Platforms

Shuvra S. Bhattacharyya

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 285, Signal processing

June 3, 2014 by hgpu

Revisiting Edge and Node Parallelism for Dynamic GPU Graph Analytics

Adam McLaughlin, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 560, Tesla C2075

June 3, 2014 by hgpu

Visualization Tool for GPGPU Programming

Peter J. Zeno

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Tags: Computer science, CUDA, nVidia, OpenACC, OpenCL, Visualization

June 3, 2014 by hgpu

Cofactorization on Graphics Processing Units

Andrea Miele, Joppe W. Bos, Thorsten Kleinjung, Arjen K. Lenstra

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Tags: Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX 580, PTX, Security

June 3, 2014 by hgpu

Loo.py: transformation-based code generation for GPUs and CPUs

Andreas Klockner

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Tags: ATI, ATI Radeon HD 7990, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, Programming Languages, PyOpenCL, Python

June 2, 2014 by hgpu

Integrated Modelling of Hydrodynamic Processes, Faecal Indicator Organisms and Related Parameters with Improved Accuracy using Parallel (GPU) Computing

Brian Adjetey Boye

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Tags: CUDA, Earth and Space Sciences, nVidia, nVidia GeForce GTX 590, Tesla K10, Tesla K20, Thesis

June 2, 2014 by hgpu

Accelerating NTRU based Homomorphic Encryption using GPUs

Wei Dai, Yarkin Doroz, Berk Sunar

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Tags: AES, Block Ciphers, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Security

June 2, 2014 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

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

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

Applications

GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian Movement

Mapping parallel programs to heterogeneous multi-core systems

A Comparative Study of Game Tree Searching Methods

Adventures in the microlensing cloud: large datasets, eResearch tools, and GPUs

Utilizing Graphics Processing Units for Rapid Facial Recognition Using Video Input

Design Tools for Accelerating Development and Usage of Multi-Core Computing Platforms

Revisiting Edge and Node Parallelism for Dynamic GPU Graph Analytics

Visualization Tool for GPGPU Programming

Cofactorization on Graphics Processing Units

Loo.py: transformation-based code generation for GPUs and CPUs

Integrated Modelling of Hydrodynamic Processes, Faecal Indicator Organisms and Related Parameters with Improved Accuracy using Parallel (GPU) Computing

Accelerating NTRU based Homomorphic Encryption using GPUs

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

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

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

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

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