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TimeGraph: GPU scheduling for real-time multi-tasking environments

Shinpei Kato, Karthik Lakshmanan, Ragunathan Rajkumar, Yutaka Ishikawa

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Tags: Benchmarking, Computer science, nVidia, nVidia GeForce 9800 GT, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenGL, Operating systems, Package, Real-time graphics, Task scheduling

September 11, 2011 by hgpu

KAdvice: infering synchronization patterns from an existing codebase

Alexander Schmidt, Andreas Polze

Tags: Computer science, Operating systems

September 9, 2011 by hgpu

Pegasus: coordinated scheduling for virtualized accelerator-based systems

Vishakha Gupta, Karsten Schwan, Niraj Tolia, Vanish Talwar, Parthasarathy Ranganathan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GTX, Operating systems, Task scheduling, Virtualization

September 7, 2011 by hgpu

Operating systems must support GPU abstractions

Christopher J. Rossbach, Jon Currey, Emmett Witchel

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Tags: Computer science, nVidia, nVidia GeForce GT 230, Operating systems

September 7, 2011 by hgpu

Resource Sharing in GPU-Accelerated Windowing Systems

Shinpei Kato, Karthik Lakshmanan, Yutaka Ishikawa, Ragunathan (Raj) Rajkumar

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Tags: Computer science, nVidia, nVidia GeForce 9500 GT, OpenGL, Operating systems, Rendering

June 22, 2011 by hgpu

GPU-based X server on top of EGL and openVG

Dongkyun Jeong, Kamalneet Singh, Namin Kim, Soochan Lim

Tags: Computer science, Energy-efficient computing, Operating systems

May 16, 2011 by hgpu

The multikernel: a new OS architecture for scalable multicore systems

Andrew Baumann, Paul Barham, Pierre E. Dagand, Tim Harris, Rebecca Isaacs, Simon Peter, Timothy Roscoe, Adrian Schüpbach, Akhilesh Singhania

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Tags: Computer science, Operating systems

November 27, 2010 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

TimeGraph: GPU scheduling for real-time multi-tasking environments

KAdvice: infering synchronization patterns from an existing codebase

Pegasus: coordinated scheduling for virtualized accelerator-based systems

Operating systems must support GPU abstractions

Resource Sharing in GPU-Accelerated Windowing Systems

GPU-based X server on top of EGL and openVG

The multikernel: a new OS architecture for scalable multicore 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

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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