Despite being the world’s largest computer chip, the WSE-3 achieves 93% silicon utilization—higher than today’s leading GPU. A tiny core, a self-healing fabric, and a clean software abstraction – that’s how you do wafer scale.
AI HARDWARE
-
WSE Defect Tolerance: 164x Better Silicon Efficiency
By
–
One way to measure defect tolerance is to look at the amount of die area. Assuming 0.001 defects per mm^2, GPUs will see 59 defects disabling 361mm^2 of silicon. On the WSE, it sees 46 defects and loses just 2.2mm^2. That's a 164x reduction in dead silicon area!
-
H100 vs WSE: Wafer-Scale Architecture Comparison at 5nm
By
–
Let’s compare at the wafer level. At 5nm, here’s what an H100 sized chip and WSE look like side by side. A 300mm wafer yields ~72 GPUs or one Wafer Scale Engine.
-
Fault-Tolerant Network Fabric with Redundant Communication Pathways
By
–
Our network fabric is also fault tolerant. When a defect is detected, the chip automatically routes around it using redundant communication pathways. The software layer presents the chip as a 2D grid even when there are defects.
-
WSE Cores: Tiny Chips Enable Efficient Large-Scale Hardware
By
–
Before we set out to build a large chip, we first designed a tiny core. Each WSE core is just 0.05mm^2 or ~1% the size of an H100 core. When a defect occurs, we lose a tiny amount of silicon relative to GPUs.
-
GPU Manufacturing Defects Impact Chip Performance Yields
By
–
Modern computer chips are far too large to yield perfect chips economically. When you buy a flagship H100 GPU, a dozen cores are either defective or disabled to manage yield. Since GPU cores are fairly large, too many defects can hurt performance.
-
Cerebras Solves Wafer-Scale Chip Yield Problem With Defect Tolerance
By
–
How does Cerebras yield a wafer-scale chip? Our latest blog provides the answers. https://
cerebras.ai/blog/100x-defe
ct-tolerance-how-cerebras-solved-the-yield-problem
… -
CES 2025 AI News Trends Insights Weekly Briefing
By
–
Strange not being in Las Vegas last week for @CES
, but my latest weekly @Digiday AI Briefing captures some of the #CES-related news, trends & insights from #CES2025: -
AI-Powered Chips Transform Agricultural Computing Efficiency
By
–
The future of farming is #AI-powered, but speed is critical. Listen as our CEO explains how our chips make agricultural AI fast and efficient enough for real-world farming operations on @timhammerich
's #FarmOfTheFuture report. https://
aginfo.net/report/61564/F
arm-of-the-Future/Compute-Power-Needed-for-AI-on-the-Farm
… -
Edge AI Tracks Dozens Vehicles Real-Time Traffic Video
By
–
🚗 Real-time vehicle tracking with Edge AI! 🚦
— Axelera AI (@AxeleraAI) 13 janvier 2025
Axelera AI’s hardware tracks dozens of cars in traffic video – all in real time, processed locally.
Smarter, faster, and more efficient AI for next gen smart cities & transport.https://t.co/4Anjxke494#EdgeAI #ComputerVision pic.twitter.com/QuWvGobdXVReal-time vehicle tracking with Edge AI! Axelera AI’s hardware tracks dozens of cars in traffic video – all in real time, processed locally. Smarter, faster, and more efficient AI for next gen smart cities & transport. https://
axelera.ai #EdgeAI #ComputerVision