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On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

K. A. Hawick, D. P. Playne

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Software Engineering

May 25, 2013 by hgpu

OpenCL Performance Evaluation on Modern Multi Core CPUs

Joo Hwan Lee, Kaushik Patel, Nimit Nigania, Hyojong Kim, Hyesoon Kim

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, OpenCL, Performance

May 25, 2013 by hgpu

Quantifying the Energy Efficiency of FFT on Heterogeneous Platforms

Yash Ukidave, Amir Kavyan Ziabari, Perhaad Mistry, Gunar Schirner, David Kaeli

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Tags: ATI, ATI Radeon HD 7770, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Signal processing

May 25, 2013 by hgpu

GEMTC: GPU Enabled Many-Task Computing

Scott Krieder, Ioan Raicu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 670, Performance

May 25, 2013 by hgpu

JPEG-GPU:: a GPGPU Implementation of JPEG Core Coding Systems

Ang Li

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Tags: Compression, CUDA, Image processing, nVidia, Tesla K20

May 25, 2013 by hgpu

Graphics Processing Unit (GPU) Implementation Methodology of AERMOD Model

Neelima B., Anirudh Udupa G., Jane Shailoh Quadras, Gururaja Rao P.

Tags: CUDA, Earth and Space Sciences, nVidia

May 23, 2013 by hgpu

Composing multiple StarPU applications over heterogeneous machines: a supervised approach

A.-E Hugo A. Guermouche P.-A. Wacrenier R. Namyst

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Tesla M2070

May 23, 2013 by hgpu

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Derek R. Hower, Bradford M. Beckmann, Benedict R. Gaster, Blake A. Hechtman, Mark D. Hill, Steven K. Reinhardt, David A. Wood

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Tags: Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, OpenCL, Performance

May 23, 2013 by hgpu

Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

Salvatore Cuomo, Ardelio Gallettiy, Giulio Giuntay, Alfredo Staracey

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Tesla C1060

May 23, 2013 by hgpu

GPU Enhancement of the Trigger to Extend Physics Reach at the LHC

V. Halyo, A. Hunt, P. Jindal, P. LeGresley, P. Lujan

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Tags: Algorithms, CUDA, Hadronic Colliders, High Energy Physics - Experiment, nVidia, Physics, Tesla K20

May 23, 2013 by hgpu

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

Simon John Pennycook

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Tags: Algorithms, ATI, ATI FirePro V7800, Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GT, nVidia GeForce GTX 680, OpenCL, Performance, Tesla C1060, Tesla C2050, Thesis

May 21, 2013 by hgpu

Implementing Continuous Integration Software in an Established Computational Chemistry Software Package

Robin M. Betz, Ross C. Walker

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Tags: Benchmarking, Chemistry, Computational chemistry, CUDA, Molecular dynamics, nVidia, Software Engineering, Tesla M2090

May 21, 2013 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

On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

OpenCL Performance Evaluation on Modern Multi Core CPUs

Quantifying the Energy Efficiency of FFT on Heterogeneous Platforms

GEMTC: GPU Enabled Many-Task Computing

JPEG-GPU:: a GPGPU Implementation of JPEG Core Coding Systems

Graphics Processing Unit (GPU) Implementation Methodology of AERMOD Model

Composing multiple StarPU applications over heterogeneous machines: a supervised approach

Sequential Consistency for Heterogeneous-Race-Free: Programmer-centric Memory Models for Heterogeneous Platforms

Surface Reconstruction from Scattered Point via RBF Interpolation on GPU

GPU Enhancement of the Trigger to Extend Physics Reach at the LHC

Evaluating the Performance of Legacy Applications on Emerging Parallel Architectures

Implementing Continuous Integration Software in an Established Computational Chemistry Software Package

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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