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Analysing the Performance of GPU Hash Tables for State Space Exploration

Nathan Cassee, Anton Wijs

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Tags: Computer science, CUDA, Design space exploration, Hashing, nVidia, nVidia GeForce GT 750 M, Performance

January 6, 2018 by hgpu

Accelerate Local Tone Mapping for High Dynamic Range Images Using OpenCL with GPU

Kuo-Feng Liao, Yarsun Hsu

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Tags: Algorithms, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GT 750 M, OpenCL

August 26, 2017 by hgpu

Real-time colouring and filtering with graphics shaders

Dany Vohl, Christopher J. Fluke, David G. Barnes, Amr H. Hassan

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Tags: Algorithms, Astrophysics, Filtering, GLSL, Image processing, nVidia, nVidia GeForce GT 750 M, nVidia GeForce GTX Titan X, nVidia Grid K1, Package, Rendering

July 5, 2017 by hgpu

Sound Synthesis Using Physical Modeling on Heterogeneous Computing Platforms

M. Pluta, B. Borkowski, I. Czajka, K. Suder-Debska

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Tags: Acoustics, Algorithms, Computer science, Finite difference, Heterogeneous systems, nVidia, nVidia GeForce GT 750 M, OpenCL

July 29, 2015 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

Analysing the Performance of GPU Hash Tables for State Space Exploration

Accelerate Local Tone Mapping for High Dynamic Range Images Using OpenCL with GPU

Real-time colouring and filtering with graphics shaders

Sound Synthesis Using Physical Modeling on Heterogeneous Computing Platforms

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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