#chips

Solving the Yield Problem #

How we solved the yield problem

via Hacker News

This was a fun read, especially after already having a bit of background knowledge on chip manufacturing. Cerebras and Groq both utilize custom chips to power their ridiculously fast AI inference, but I hadn’t previously considered the widely differing order of magnitudes these chips have compared to traditional GPUs. As an example, Cerebras cites their WSE-3 as having 900,000 cores compared to individual H100s which have only 144.

Cerebras’ method for reducing the impact of defects feels quite straightforward—reducing core sizes and having a surplus of cores means that individual core defects are able to be had at an extremely small scale while having almost no impact on the overall chip. Additionally, Cerebras uses a special routing architecture to ensure that cores are able to route around disabled cores, meaning that disabling cores creates no interference. Through these methods, Cerebras notes the WSE-3 as having a high 93% core utilization, compared to H100s with a 92% utilization.