CAMformer STUDIO

IEEE TCAS-I 2026 / INTERACTIVE RESEARCH COMPANION

Attention,
inside memory.

Follow a query from binary matches to a weighted answer. Then explore the hardware tradeoffs behind CAMformer.

Flip a bit. See what changes.
QUERY → ASSOCIATIVE MEMORY → CONTEXT
1 0 1 1 0 0 1 0
191queries / ms
9,045queries / mJ
0.258mm² core area

Published operating point
Simulation-based attention-layer results

ILLUSTRATIVE EXAMPLE

FROM BITS TO AN ANSWER

One bit can change who gets attention.

Click a query bit. Matching keys light up, selected scores become weights, and the output updates.

Stored keys

Match   Retained

CONTEXTUALIZATION

A weighted answer

Selected values contribute in proportion to their attention weights.

Synthetic values; floating-point demo arithmetic. The hardware uses BF16 values and MACs. This is not a trained-language-model evaluation.

BUILT ON REPRODUCIBLE RESEARCH

Every number has a source.

Published values, release-model outputs and illustrative interactions are labeled separately.

Traceability ledger ↗Reproduce the results ↗Download model snapshot ↓