Cerebras Architecture Deep Dive: First Look Inside the HW/SW Co-Design for Deep Learning [Updated] - Cerebras

This post provides a deep dive into the Cerebras architecture, focusing on its HW/SW co-design for deep learning. It details the core architecture with its distributed memory (48KB SRAM per core with high bandwidth), fine-grained dataflow scheduling, and hardware support for tensor instructions. It explains how this enables full performance across all BLAS levels and native acceleration of unstructured sparsity. The post also touches upon scale-up and scale-out strategies to address the Grand ML Demand Challenge.