Compute-in-Memory (CIM) Chips
AI, we have a "memory" problem. New computing architectures and chip designs that make more intelligent use of new memory technologies are key to unlocking extreme energy efficiency. We push the frontier of compute-in-memory AI chips through co-designs and prototyping.
Our ongoing research and tapeouts:
- Novel circuit and macro designs for resistive RAM (RRAM), embedded DRAM (eDRAM), and beyond.
- Energy-efficient, precision-configurable, heterogeneous CIM chip for edge transformer acceleration.
- On-chip learning enablement and prototyping.
- We seek new collaborations to apply our unique co-design ideas towards chip prototyping with ferroelectric and magnetic memories!
SAPIENS is the first integrated chip demonstrating on-chip, one-shot learning, enabled by a ‘CMOS+X’ approach for memory-augmented neural networks in hardware. The architecture features a non-volatile associative memory with fully integrated RRAM + CMOS in 40 nm.
Related publications:
VLSI 2021, TED 2021