🌄🌱👑’s 🌌
ai analog-design backpropagation benchmarking blog cadence car chiplets claude digital design dns eda email git ic ieee innovus latex linux llm mac machine learning matplotlib microsoft office network nginx ngspice notes on-chip-training pdf phd physical-design programming python razavi research rtl svg transformer verilog visualization vt window wordpress
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git Note
I’ve always trying to summarize an article of how to use git, but there has been a lot of resistance of doing so, one reason is that there are sufficient material that have enough info of how to use git. Although they provide a very detailed info regarding how to use git, I or beginners…
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Train a Transformer on Silicon: #1 Backprop on a Chip
Most AI chips run a model someone else trained; this one does the training itself — forward pass, backpropagation, and weight update, in fixed-point RTL, all the way down to a 45 nm layout.
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Publication-Quality Chip Layout Figures from Innovus, Headlessly
Innovus has no vector export and its GUI screenshots don’t scale. Here’s a fully scripted pipeline: a headless 16,000-pixel render, block coordinates pulled from the P&R database, a zero-residual pixel-to-micron calibration, and a matplotlib wrapper that turns it all into a self-describing PDF/SVG figure.
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Benchmarking 17 AI Models on Razavi’s Analog Design Questions
I re-ran Behzad Razavi’s ‘Analog Mind’ LLM experiments across 17 model configurations, with a controlled anonymized grader and ngspice as the referee. The methodology moved scores as much as the models did.
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One Prompt, One Complete IEEE Transactions Project with Claude Code
A single copy-pasteable prompt that makes Claude Code scaffold a complete IEEE Transactions LaTeX project: main manuscript, S-numbered supplementary materials, a shared author file, and a full revision workflow – with no dependencies beyond a TeX distribution and make.
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Train a Transformer on Silicon: #0 The Genesis
Start here — the series hub A short intro to a series where I build a chip that trains a transformer — and document the whole thing, mistakes included. What this is I’m building a digital chip that trains a transformer on-chip — not just runs it, but actually learns: forward pass, backpropagation, and weight…
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Hello from WP-CLI: KaTeX & Code Block Pro
This post was created from the terminal with WP-CLI, then edited again from the terminal to add the two elements below — a live equation and a syntax-highlighted code block, both rendered by this blog’s existing plugins. A little math, via the KaTeX plugin Euler’s identity sits inline in the text: . A display equation…
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Replacing Your Python Script With Another Program: os.execvp
I wanted a small launcher for Claude Code that read its settings from a YAML file — env vars, flags, working directory, that kind of thing. Something I could version-control and tweak without remembering a 200-character invocation. My first attempt printed the command line. My second attempt was better, and along the way I finally…
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Cadence IC25.1: “Failed to find licenses Virtuoso_ADE_Artist” and How to Fix the Virtuoso Hotfix Install
I spent a good chunk of time upgrading Cadence Virtuoso’s optimizer (AOP) from IC25.1 base to the ISR4 hotfix. What should’ve been a routine update turned into two rabbit holes: the optimizer was checking for a license that doesn’t exist on most servers, and the hotfix installer kept dying on symlinks that point to each…
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Backprop is under the hood
In 1, the division of . 2 To illustrate why the dot products get large, assume that the components of q and k are independent random variables with mean and variance . Then their dot product, , has mean and variance . Vaswani, Ashish, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin. “Attention is all…
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Adding Sections to PowerPoint Files with Python and lxml
The python-pptx library is great for creating PowerPoint presentations programmatically, but it doesn’t support PowerPoint sections — the collapsible groups you see in the slide panel. This post shows how to add sections by directly manipulating the underlying XML with lxml. The OOXML Structure A .pptx file is a ZIP archive containing XML files. The…
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How to Make AI Coding Tools Preserve Your File Metadata
When AI tools like Claude Code edit a file, they typically delete it and write a brand new one. The content is correct, but the file’s metadata — creation timestamp, inode, ownership, permissions, ACLs, extended attributes — is silently destroyed. On a personal project this is a minor annoyance. On a production server with specific…
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Technical Blog Post Paradigm Shift
I write technical blog post for example tutorials to help people to handle certain issues, that could contain commands to be run, operations to be performed to solve issues or handle a specific problem, until recently I found out this may not be useful to readers in the AI/AI agent era. I would like to…
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What Really Happens When You Force Quit WindowServer on macOS
The Problem: High Memory Usage Without Wanting to Restart Like many developers and power users, I keep dozens of browser tabs, applications, and terminal sessions open at all times. The thought of restarting my Mac fills me with dread—not because of the reboot time, but because I’d lose all my carefully organized workspace: browser tabs,…
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Debugging a Rocky Linux Boot Nightmare: When GRUB Hides Configuration in Unexpected Places
A deep dive into troubleshooting persistent GRUB boot issues after SSD migration Background: The Migration Process My Rocky Linux 9.4 server was running on a traditional HDD, and I decided to upgrade to a faster NVMe SSD. Rather than doing a clean install, I wanted to migrate the existing system to preserve all configurations and…
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Weight-sparse transformers have interpretable circuits
Weight-sparse transformers have interpretable circuits1234: Train sparse model on weights and pruning to explain interpretability, find connections between sparse and dense models. Transform: Encoder, Decoder, from tokens to embeddings to tokens | from electricity to magnetics to electricity | Fourier Transform | LLM Visualization Overall Setup | Superposition 5 Sparse Model Training sparse models contain…
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