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Exploiting Unexploited Computing Resources for Computational Logics

Alessandro Dal Palu, Agostino Dovier, Andrea Formisano, Enrico Pontelli

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 560, SAT, Tesla C2075

June 14, 2012 by hgpu

Parakeet: A Just-In-Time Parallel Accelerator for Python

Alex Rubinsteyn, Eric Hielscher, Nathaniel Weinman, Dennis Shasha

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Tags: Computer science, CUDA, nVidia, Python, Tesla C1060

June 14, 2012 by hgpu

Using Fermi architecture knowledge to speed up CUDA and OpenCL programs

Yuri Torres, Arturo Gonzalez-Escribano, Diego R. Llanos

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Performance

June 13, 2012 by hgpu

Experiences with High-Level Programming Directives for Porting Applications to GPUs

Oscar Hernandez, Wei Ding, Barbara Chapman, Ramanan Sankaran, and Richard Graham

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Tags: Computer science, CUDA, nVidia, OpenCL, Tesla C2070

June 13, 2012 by hgpu

A comparison of CPU and GPU performance for Fourier pseudospectral simulations of the Navier-Stokes, Cubic Nonlinear Schrodinger and Sine Gordon Equations

B. Cloutier, B.K. Muite, P. Rigge

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Tags: Algorithms, CUDA, FFT, Fortran, Navier-Stokes equations, nVidia, OpenACC, OpenMP, Physics, Spectral methods, Tesla M2070

June 13, 2012 by hgpu

Fluid Dynamics Simulations on Multi-GPU Systems

Eugenio Rustico

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Tags: CUDA, Fluid dynamics, GPU cluster, nVidia, nVidia GeForce GTX 480, Thesis

June 13, 2012 by hgpu

Large, Pruned or Continuous Space Language Models on a GPU for Statistical Machine Translation

Holger Schwenk, Anthony Rousseau, Mohammed Attik

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Tags: Computational Complexity, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Package, Speech recognition, Tesla M2090

June 11, 2012 by hgpu

GPUSync: Architecture-Aware Management of GPUs for Predictable Multi-GPU Real-Time Systems

Glenn A. Elliott, Bryan C. Ward, James H. Anderson

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 470, Package, Performance

June 11, 2012 by hgpu

Range query processing in a multi-GPU environment

Ricardo J. Barrientos, Jose I. Gomez, Christian Tenllado, Manuel Prieto Matias, Mauricio Marin

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Tags: Algorithms, Biology, Computational biology, Computer science, CUDA, Databases, GPU cluster, nVidia, OpenMP, Tesla C1060

June 11, 2012 by hgpu

CUDAICA: GPU optimization of Infomax-ICA EEG analysis

Federico Raimondo, Juan Kamienkowski, Mariano Sigman, Diego Fernandez Slezak

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Tags: Algorithms, Biology, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, Neuroscience, nVidia, nVidia GeForce GTX 560, Package, Tesla C2070

June 11, 2012 by hgpu

Solving the Ghost-Gluon System of Yang-Mills Theory on GPUs

Markus Hopfer, Reinhard Alkofer, Gundolf Haase

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Tags: Computational Physics, CUDA, High Energy Physics - Phenomenology, High Energy Physics - Theory, Integral equations, nVidia, nVidia GeForce GTX 560 Ti, OpenMPI, Physics, QCD, Tesla C2070

June 11, 2012 by hgpu

Using the GPGPU for Scaling Up Mining Software Repositories

Rina Nagano, Hiroki Nakamura, Yasutaka Kamei, Bram Adams, Kenji Hisazumi, Naoyasu Ubayashi, Akira Fukuda

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Tags: Computer science, CUDA, Data mining, nVidia, nVidia GeForce GTX 480, Package

June 10, 2012 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

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

Generating Literature-Driven Scientific Theories at Scale

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

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

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high performance computing on graphics processing units: hgpu.org

Exploiting Unexploited Computing Resources for Computational Logics

Parakeet: A Just-In-Time Parallel Accelerator for Python

Using Fermi architecture knowledge to speed up CUDA and OpenCL programs

Experiences with High-Level Programming Directives for Porting Applications to GPUs

A comparison of CPU and GPU performance for Fourier pseudospectral simulations of the Navier-Stokes, Cubic Nonlinear Schrodinger and Sine Gordon Equations

Fluid Dynamics Simulations on Multi-GPU Systems

Large, Pruned or Continuous Space Language Models on a GPU for Statistical Machine Translation

GPUSync: Architecture-Aware Management of GPUs for Predictable Multi-GPU Real-Time Systems

Range query processing in a multi-GPU environment

CUDAICA: GPU optimization of Infomax-ICA EEG analysis

Solving the Ghost-Gluon System of Yang-Mills Theory on GPUs

Using the GPGPU for Scaling Up Mining Software Repositories

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

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

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

Awesome LLM-Driven Kernel Generation

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