<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Verilog on TiJet</title><link>https://www.tainuohc.com/en/tags/verilog/</link><description>Recent content in Verilog on TiJet</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 20 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.tainuohc.com/en/tags/verilog/index.xml" rel="self" type="application/rss+xml"/><item><title>FPGA-Accelerated Visual Inspection: How We Cut Latency from 200ms to 8µs</title><link>https://www.tainuohc.com/en/blog/2026-07-20-fpga-acceleration/</link><pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate><guid>https://www.tainuohc.com/en/blog/2026-07-20-fpga-acceleration/</guid><description>&lt;h2 id="1-the-problem-software-based-visual-inspection-hits-a-wall">1. The Problem: Software-Based Visual Inspection Hits a Wall&lt;/h2>
&lt;p>In Tainuo&amp;rsquo;s PCB printing pipeline, one of the most critical steps is real-time solder-paste inspection. Each board passing through the production line has less than 50ms total for defect detection — any slower and the line stalls.&lt;/p>
&lt;p>For years we ran a GPU-accelerated OpenCV pipeline on an x86 edge node. It worked — mostly. But under peak load with high-resolution 8K images, the pipeline occasionally hit 180–220ms per frame. That 180ms of jitter meant missed defects, false passes, and production-line backpressure. The root cause was architectural: a general-purpose GPU pipeline, no matter how optimized, introduces unpredictable scheduling latency and PCIe transfer overhead.&lt;/p></description></item></channel></rss>