<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Shidi Tang | HEAD Lab</title><link>https://verimaketest.github.io/author/shidi-tang/</link><atom:link href="https://verimaketest.github.io/author/shidi-tang/index.xml" rel="self" type="application/rss+xml"/><description>Shidi Tang</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Wed, 01 Jul 2026 00:00:00 +0000</lastBuildDate><image><url>https://verimaketest.github.io/author/shidi-tang/avatar_hu24ec4aee10eb436daff7b46d61c0dd52_338853_270x270_fill_lanczos_center_3.png</url><title>Shidi Tang</title><link>https://verimaketest.github.io/author/shidi-tang/</link></image><item><title>BenDan: Benchmarking DPU performance on FPGAs</title><link>https://verimaketest.github.io/publication/bao-2026-bendan/</link><pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/publication/bao-2026-bendan/</guid><description/></item><item><title>FANE: FPGA-Based FP8 Approximate Neural Network Engine</title><link>https://verimaketest.github.io/publication/bao-2026-fane/</link><pubDate>Mon, 01 Jun 2026 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/publication/bao-2026-fane/</guid><description/></item><item><title>Equicore: Accelerating Clebsch-Gordan Tensor Product of Equivariant Neural Networks on FPGA</title><link>https://verimaketest.github.io/publication/tang-2026-equicore/</link><pubDate>Wed, 01 Apr 2026 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/publication/tang-2026-equicore/</guid><description/></item><item><title>FP8ApproxLib: An FPGA-based approximate multiplier library for 8-bit floating point</title><link>https://verimaketest.github.io/publication/chen-2026-fp-8-approxlib/</link><pubDate>Wed, 01 Apr 2026 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/publication/chen-2026-fp-8-approxlib/</guid><description/></item><item><title>Gold Prize in the 2nd Global Digital Intelligence Education Innovation Competition</title><link>https://verimaketest.github.io/post/gold-prize-global-digital-intelligence-education-innovation-competition/</link><pubDate>Sat, 01 Nov 2025 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/post/gold-prize-global-digital-intelligence-education-innovation-competition/</guid><description>&lt;p>Our team won the Gold Prize (1st) in the AI for Science High-Performance Optimization group of the 2nd Global Digital Intelligence Education Innovation Competition.&lt;/p>
&lt;p>The team was led by Shidi Tang, with team members Yuedong Zhang, Ankun Tian, and Ruiqi Chen. The advisors were Ming Ling, Bruno da Silva, and Yanxiang Zhu.&lt;/p></description></item><item><title>Diff-DiT: Temporal Differential Accelerator for Low-bit Diffusion Transformers on FPGA</title><link>https://verimaketest.github.io/publication/tang-2025-diff/</link><pubDate>Wed, 01 Oct 2025 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/publication/tang-2025-diff/</guid><description/></item><item><title>FPGA-based Approximate Multiplier for FP8</title><link>https://verimaketest.github.io/publication/chen-2025-fpga/</link><pubDate>Thu, 01 May 2025 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/publication/chen-2025-fpga/</guid><description/></item><item><title>ATE-GCN: An FPGA-Based Graph Convolutional Network Accelerator with Asymmetrical Ternary Quantization</title><link>https://verimaketest.github.io/publication/chen-2025-ate/</link><pubDate>Sat, 01 Mar 2025 00:00:00 +0000</pubDate><guid>https://verimaketest.github.io/publication/chen-2025-ate/</guid><description/></item></channel></rss>