
Developed and released a unified CUDA Convolution Lab feature for the ZJUSCT/HPC101 repository, consolidating Lab 3 into a comprehensive workflow for students and researchers. The work included end-to-end documentation covering deep learning fundamentals, GPU architecture, and optimization strategies, as well as navigation updates to streamline onboarding. Starter code for 2D convolution in both int8 and FP16 formats was provided, with detailed guidance on tiling and shared-memory usage. The feature integrated an Online Judge submission and scoring workflow, complete with updated visuals, leveraging C++, CUDA, and Markdown to enhance hands-on learning and automate evaluation within a high-performance computing context.
July 2025 summary for ZJUSCT/HPC101: Consolidated Lab 3 CUDA Convolution into a single feature with end-to-end documentation, starter code for 2D convolution (int8 and FP16), tiling/shared-memory guidance, and a complete Online Judge workflow with updated visuals. This work improves onboarding, accelerates hands-on progress, and strengthens automated evaluation.
July 2025 summary for ZJUSCT/HPC101: Consolidated Lab 3 CUDA Convolution into a single feature with end-to-end documentation, starter code for 2D convolution (int8 and FP16), tiling/shared-memory guidance, and a complete Online Judge workflow with updated visuals. This work improves onboarding, accelerates hands-on progress, and strengthens automated evaluation.

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