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AMD and Cerebras announced a joint AI inference solution combining AMD Helios rackscale solutions with Cerebras Wafer-Scale Engine, aiming for ultra-low latency and high throughput. The disaggregated inference workflow is expected to deliver up to 5x higher tokens per second per watt.
Cerebras co-founder explains the fundamental difference between WSE (Wafer Scale Engine) and NVIDIA GPU: GPU is designed for graphics, runs AI by stacking cores and NVLink interconnect, while WSE makes the entire wafer into a single chip, with on-chip interconnect bandwidth and memory bandwidth far exceeding GPU clusters, greatly leading in inference speed.
The article analyzes the AI inference ASIC architectures of Groq, SambaNova, Tenstorrent, and Cerebras, highlighting Cerebras's unique wafer-scale engine design. It discusses the benefits of deterministic latency and high bandwidth for LLM inference, while noting challenges like yield, cost, and KV cache bottlenecks.