Over the past few weeks, I have added several new pages to Xe-Diagrams, with more details about GPU systems and how different parts of the stack work together.
Continue reading “Xe-Diagram updates v0.5.1”2 Layers below Xe-Diagram, one become confidential
I have finished a prototype of a beast application tool, but feel uncertain if I have the passion to keep improving that.
I have finalized the basic idea of project Xe-Diagram – aiming to show case a project that can visualize public architecture view. I am very satisfied on the current status. With sub pages reworked, reviewed and published, I think my project can sit better than the public Programmer’s Reference Manuals and can serve better as a knowledge base like MCP server for Intel post-si GPUs.
Continue reading “2 Layers below Xe-Diagram, one become confidential”Thoughts on Architecture-Awareness Performance Diagnosis
Today marks one year since the Intel GPA project was discontinued.
At the time, I felt a real sense of emptiness. GPA was an external-facing tool, and working on something used by people outside my immediate team gave me a strong feeling of purpose. It was not only a technical project to me; it also became part of my professional identity and even helped support my extraordinary ability visa case.
Over the past year, working in architecture modeling has changed how I think about GPU performance analysis. I started to look less at application behavior as a black box, and more at the command streams submitted to the GPU, the hardware blocks they touch, and the metrics that describe how those blocks behave. That perspective made me rethink what future GPU tuning workflows could look like.
Continue reading “Thoughts on Architecture-Awareness Performance Diagnosis”Xe-Diagram Page published (Finished!)
Glad to have published my vibe Xe-Diagram
Link: https://xwang186.com/xe-diagram/ (also can be accessed thru blog menu)
Architecture: Xe-HPG(A770)
Referred docs: Intel® Graphics for Linux* – Programmer’s Reference Manuals
(6/16/2026 update: seems the orginal link https://www.x.org/docs/intel/ACM/ — become unavailable now)
5/19/2026 – Finished! Glad to have included all my initial thoughts into the plugin!
Continue reading “Xe-Diagram Page published (Finished!)”Core skill/How to stand out?
Have been using Claude AI in day to day work in the past months, and have been felt humbled.
If we have a smaller team maintaining the project, what will be everyone’s role then?
Continue reading “Core skill/How to stand out?”Happen to find the “shift” of ChatGPT answer
Today I had a surprisingly satisfying conversation with ChatGPT. I asked it to design a logic puzzle for me — something like an engineering-flavored investigation with access control, logs, time stamps, and suspicious statements. On the surface, it looked good: the framing was serious, the setup was detailed, and the tone suggested a real deduction problem.
Continue reading “Happen to find the “shift” of ChatGPT answer”Way I want to use blog
I have been spent quite long time with ChatGPT, on different topics. I am the 1% top user , without using any token api but just chat on web/app.
I have found it less meaningful to summarize “domain knowledge” into articles. This is a waste of time because AI agent can do 20x better than me.
Continue reading “Way I want to use blog”Travel 2 LA
By Train from SAC
Revisit of my NVDLA adaption project in Novumind
Introduction to NVDLA
The NVIDIA Deep Learning Accelerator (NVDLA) is an open-source hardware project designed to accelerate deep learning inference tasks. Its flexible, scalable architecture enables developers to implement AI acceleration on various platforms, from FPGAs to ASICs. By offering a complete stack of hardware and software, NVDLA has become a cornerstone for many projects in the AI hardware space, making it an invaluable tool for prototyping and development.
Continue reading “Revisit of my NVDLA adaption project in Novumind”3 Weeks before finishing the MSEM degree
as title. relief
Update 10/19: 1 week left
Everything done