Reiner Pope – Chip design from the bottom up This article explains the fundamental building blocks of computer chips, starting with logic gates and progressing to complex operations like multiply-accumulate, which is crucial for AI chips. It details how systolic arrays optimize matrix multiplication by baking loops into hardware, reducing data movement costs. The discussion also covers clock cycles, pipeline registers, and the trade-offs between FPGAs and ASICs, highlighting how design choices impact performance, area, and energy efficiency.

• Chips are built from fundamental logic gates like AND, OR, and NOT.
• The multiply-accumulate operation is a core primitive for AI chips, essential for matrix multiplication.
• Systolic arrays are designed to bake matrix multiplication loops into hardware, significantly reducing data movement costs compared to traditional CPU/GPU cores.
• Clock cycles synchronize parallel operations in chips; inserting pipeline registers can increase clock speed but also area.
• FPGAs offer flexibility and deterministic latency for frequently changing workloads, while ASICs are more cost-effective and performant for fixed designs.
• CPU cores are larger than GPU cores primarily due to extensive cache systems and branch predictors, which are largely absent in GPUs.
• The human brain operates with unstructured sparsity and co-located memory and compute, differing from the structured parallelism and separate memory hierarchies in chips.
• GPUs can be seen as tiled arrangements of many smaller, similar units, akin to many tiny TPUs, each with local memory and compute capabilities. Continue reading https://foxvector.com/articles/97d2ac6f-75fe-435a-aabd-1ed79b6f98c3