This post analyzes matrix multiplication performance on Intel Xeon CPUs and NVIDIA V100 GPUs, comparing results across C++, OpenMP, CUDA, MPI, NVSHMEM, and Python frameworks like NumPy and CuPy.
Recently, I undertook a rather challenging task: to fully reproduce a paper titled “Physics-informed deep generative learning for quantitative assessment of the retina” on a High-Performance Computing (HPC) cluster. The core software repository for this paper is RetinaSim. The goal was not merely to run the code, but to completely replicate its complex software stack and simulation workflow in a strictly managed computational environment, one that likely differed significantly from the original developers’. This blog post will chronicle my entire journey from the initial attempt to the final successful run, focusing on my chain of thought as I diagnosed and resolved a series of tricky issues. ...
This post details how to build an interactive urban planning visualization system using Python, Geopandas, and Folium by integrating housing pipelines, crime data, and socioeconomic metrics.
Learn how to reverse-engineer a university’s private timetable API using browser developer tools and write a Python script to convert the JSON data into a universally importable iCalendar (.ics) file for your personal calendar.