<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>3d-Dram on Best of AI</title><link>https://bestofai.io/tags/3d-dram/</link><description>Recent content in 3d-Dram on Best of AI</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Sat, 05 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://bestofai.io/tags/3d-dram/index.xml" rel="self" type="application/rss+xml"/><item><title>d-Matrix Raptor</title><link>https://bestofai.io/hardware/d-matrix-raptor/</link><pubDate>Sat, 05 Sep 2026 00:00:00 +0000</pubDate><guid>https://bestofai.io/hardware/d-matrix-raptor/</guid><description>&lt;p&gt;d-Matrix presented Raptor at Hot Chips 2026, which it calls the first 3D-DRAM accelerator built for generative inference. Rather than routing through a conventional memory PHY, Raptor bonds a TSMC 4nm compute die face-to-face onto a custom-designed DRAM die at a 36-micron pitch, delivering 100 TB/s of bandwidth from 32GB of memory per card at roughly 0.37 picojoules per bit, well below the energy cost of moving data into an HBM4 base die. d-Matrix&amp;rsquo;s accompanying ISCA 2026 paper projects about 4.7 times higher inference throughput per card than HBM-based designs. The company&amp;rsquo;s CEO has said Raptor is on track to launch in 2027.&lt;/p&gt;</description></item></channel></rss>