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Spatial interpolation in massively parallel computing environments

Katharina Hennebohl, Marius Appel, Edzer Pebesma

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Tags: Algorithms, CUDA, Earth and Space Sciences, nVidia, nVidia Quadro FX 4800

November 20, 2011 by hgpu

Soft Error Resilient QR Factorization for Hybrid System

Peng Du, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Fault tolerance, Hybrid computing, Linear Algebra, nVidia, Tesla C2050, Tesla M2070

November 20, 2011 by hgpu

Using mobile GPU for general-purpose computing – a case study of face recognition on smartphones

Kwang-Ting (Tim) Cheng, Yi-Chu Wang

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Tags: ARM, Computer science, Computer vision, FFT, Image recognition, nVidia, nVidia Tegra

November 20, 2011 by hgpu

Autotuning GEMMs for Fermi

Jakub Kurzak, Stanimire Tomov, Jack Dongarra

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Tags: Benchmarking, BLAS, Computer science, CUDA, Linear Algebra, Mathematical Software, Matrix multiplication, nVidia, Package, Tesla S2050

November 20, 2011 by hgpu

Efficient Support for Matrix Computations on Heterogeneous Multi-core and Multi-GPU Architectures

Fengguang Song, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, BLAS, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Tesla M2070

November 20, 2011 by hgpu

Optimizing Symmetric Dense Matrix-Vector Multiplication on GPUs

Rajib Nath, Stanimire Tomov, Tingxing "Tim" Dong, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Package, Performance, Tesla C2050

November 20, 2011 by hgpu

Using the High Productivity Language Chapel to Target GPGPU Architectures

Albert Sidelnik, Maria J. Garzaran, David Padua, Bradford L. Chamberlain

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 280, Optimization

November 19, 2011 by hgpu

Anisotropic mesh coarsening and refinement on GPU architecture

Matthew Potter

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Tags: Algorithms, CUDA, Differential equations, Finite volume method, Fluid dynamics, nVidia, Partial differential equations, PDEs, Tesla M2050, Thesis

November 19, 2011 by hgpu

Exploiting concurrent kernel execution on graphic processing units

Lingyuan Wang, Miaoqing Huang, Tarek El-Ghazawi

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques, Tesla C2070

November 19, 2011 by hgpu

Towards Efficient GPU Sharing on Multicore Processors

Lingyuan Wang, Miaoqing Huang, Tarek El-Ghazawi

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Tags: Computer science, CUDA, GPU cluster, nVidia, Performance, Programming techniques, Tesla C1060, Tesla C2070

November 19, 2011 by hgpu

ShoveRand: a model-driven framework to easily generate random numbers on GP-GPU

Jonathan Passerat-Palmbach, Claude Mazel, David R.C. Hill

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Tags: Computer science, CUDA, nVidia, Pseudo-random number generators, Stochastic simulation, Tesla C1060

November 19, 2011 by hgpu

SGPU 2: a runtime system for using large applications on clusters of hybrid nodes

Matthieu Ospici, Dimitri Komatitsch, Jean-Francois Mehaut, Thierry Deutsch

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Tags: Benchmarking, Computer science, CUDA, Hybrid computing, nVidia, Tesla T10

November 19, 2011 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Spatial interpolation in massively parallel computing environments

Soft Error Resilient QR Factorization for Hybrid System

Using mobile GPU for general-purpose computing – a case study of face recognition on smartphones

Autotuning GEMMs for Fermi

Efficient Support for Matrix Computations on Heterogeneous Multi-core and Multi-GPU Architectures

Optimizing Symmetric Dense Matrix-Vector Multiplication on GPUs

Using the High Productivity Language Chapel to Target GPGPU Architectures

Anisotropic mesh coarsening and refinement on GPU architecture

Exploiting concurrent kernel execution on graphic processing units

Towards Efficient GPU Sharing on Multicore Processors

ShoveRand: a model-driven framework to easily generate random numbers on GP-GPU

SGPU 2: a runtime system for using large applications on clusters of hybrid nodes

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

Most viewed papers (last 30 days)