Explore technical articles related to optimization. Find in-depth analysis, tutorials, and insights.
An honest roundup of the resources I actually recommend for learning CUDA matrix multiplication optimization — from naive kernels to near-cuBLAS. Compares siboehm, Lei Mao, Salykova, NVIDIA docs, and one of my own deep dives, with explicit guidance on which to read first.
Step-by-step CUDA matrix multiplication optimization with 9 interactive visualizations. From naive kernels through shared memory tiling to near-cuBLAS speeds.
Visual exploration of floating-point arithmetic and numerical stability. Learn why NAdam fails in FP16 and how machine epsilon affects deep learning.
Master neural network quantization with interactive visualizations. Explore QAT, PTQ, GPTQ, AWQ, and SmoothQuant methods for efficient model deployment.
How C++ compilers transform source code through preprocessing, parsing, optimization, and code generation. Interactive visualizations included.