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Efficient mapping of the training of Convolutional Neural Networks to a CUDA-based cluster

Jonatan Ward, Sergey Andreev, Francisco Heredia, Bogdan Lazar, Zlatka Manevska

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Tags: Algorithms, CNN, Computer science, CUDA, GPU cluster, Neural networks, nVidia, nVidia GeForce GTX 570, Performance

January 4, 2012 by hgpu

Speed sign detection and recognition by convolutional neural networks

Maurice Peemen, Bart Mesman, Henk Corporaal

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Image recognition, Neural networks, nVidia, nVidia GeForce GTX 460

December 15, 2011 by hgpu

Potential contribution of CNN-based solving of stiff ODEs and PDEs to enabling real-time Computational Engineering

J.C. Chedjou, K. Kyamakya, U.A. Khan, M.A. Latif

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Tags: Cellular neural networks, CNN, Computational Engineering, Computer science, Differential equations, DSP, FPGA, Maxwell's equations, Neural networks, ODEs, Optimization, Ordinary differential equations, Partial differential equations, PDEs

August 2, 2011 by hgpu

GPU powered CNN simulator (SIMCNN) with graphical flow based programmability

B. G. Soos, A. Rak, J. Veres, G. Cserey

Tags: Cellular neural networks, CNN, Computer science, Neural networks

November 2, 2010 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

Agentic Code Optimization via Compiler-LLM Cooperation

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

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

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

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

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

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

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

Hunting CUDA Bugs at Scale with cuFuzz

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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