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Parallelized Segmentation of CT-Angiography datasets using CUDA

Daniel Fischl

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GT 425 M, Thesis

October 29, 2012 by hgpu

Engineering Concurrent Software Guided by Statistical Performance Analysis

Clemens Grelck, Kevin Hammond, Heinz Hertlein, Philip Holzenspies, Chris Jesshope, Raimund Kirner, Bernd Scheuermann, Alex Shafarenko, Iraneus Te Boekhorst, Volkmar Wieser

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 425 M, Performance, Visualization

December 29, 2011 by hgpu

GPU-Based Image Processing Use Cases: A High-Level Approach

Volkmar Wieser, Clemens Grelck, Holger Schoner, Peter Haslinger, Karoly Bosa, Bernhard Moser

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Tags: Benchmarking, CUDA, Image processing, nVidia, nVidia GeForce GT 425 M, Software Engineering, Virtualization

November 21, 2011 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

Parallelized Segmentation of CT-Angiography datasets using CUDA

Engineering Concurrent Software Guided by Statistical Performance Analysis

GPU-Based Image Processing Use Cases: A High-Level Approach

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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