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Articles

Tohoku and Aisin stash a whole model beside the arithmetic

A 16nm research chip holds its operating system and neural network weights in on-die MRAM, booting in 65.7 milliseconds without external memory.

AIWadmin
Last updated: November 2, 2026 7:30 pm
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ByAIWadmin
Global AI news & information.
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Engineers at Tohoku University and Aisin have built a 16nm FinFET system-on-chip with 32MB of embedded STT-MRAM, enough non-volatile storage to hold both a compact Linux image and a model’s weights. No DRAM or SSD sits outside it.

Contents
The numbers, and what was measuredFitting a model into 32 megabytes

The research comes out of Tetsuo Endoh’s group at CIEs, Tohoku’s integrated electronics centre, working alongside Aisin engineers.

The numbers, and what was measured

Power-on to operating-system kernel took 65.7ms, roughly 39 times faster than a conventional layout. Time to the first object detection result was 124.2ms, about 25 times better.

Those figures come from running Tiny YOLOv3 on an evaluation board, not from a production automotive controller. Inference energy was 50.7 mJ per frame, with the team claiming roughly a fiftieth of comparable mobile silicon.

Fitting a model into 32 megabytes

Squeezing the design into on-chip memory required weight sharing and mixed-precision arithmetic. The compute block pairs dual Cortex-A53 cores with a Mali-G31 GPU and a dedicated accelerator, aimed at vehicles and robotics.

For a surround-view camera or a factory robot, the appeal is not raw throughput. It is waking up and answering in a fraction of the time while drawing almost nothing from a battery in standby.

The open questions are automotive grade: temperature range, write endurance, and whether MRAM yield holds at volume. A prototype does not answer any of them.

TAGGED:AisinAutomotive AIEdge AIMRAMSemiconductorsTohoku University
SOURCES:International Business Times JapanAisin
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