An MRAM-Based Deep In-Memory Architecture for Deep Neural Networks
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Bibliographic record
Abstract
This paper presents an MRAM-based deep in-memory architecture (MRAM-DIMA) to efficiently implement multi-bit matrix vector multiplication for deep neural networks using a standard MRAM bitcell array. The MRAM-DIMA achieves an 4.5 × and 70× lower energy and delay, respectively, compared to a conventional digital MRAM architecture. Behavioral models are developed to estimate the impact of circuit non-idealities, including process variations, on the DNN accuracy. An accuracy drop of ≤ 0.5% (≤ 1%) is observed for LeNet-300-100 on the MNIST dataset (a 9-layer CNN on the CIFAR-10 dataset), while tolerating 24% (12%) variation in cell conductance in a commercial 22 nm CMOS-MRAM process.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it