Energy-Efficient Differential Spin Hall MRAM-Based 4-2 Magnetic Compressor
Bibliographic record
Abstract
The compressors are widely used as bit compressing cells having key applications with multi-operand addition and multiplication hardware. As the CMOS technology scales down below 45 nm technology nodes, static power dissipation becomes a major concern. To overcome this constraint, spin transfer torque magnetic random access memory (STT-MRAM)-based hybrid CMOS/MTJ architectures are being used. Inception of perpendicular magnetic tunnel junction (PMTJ) has enhanced the growth of spintronicsbased hybrid architectures, due to their low switching current, scalability, non-volatility, and CMOS compatibility. Recently, a large number of circuits based on STT-MRAM have been proposed. However, they have limitations related to reliability and high write energy. In this article, we propose a differential spin Hall MRAM (DSH-MRAM)-based hybrid CMOS/MTJ magnetic 4-2 compressor. A write voltage of 0.4 V and 300 ps current pulse are used to switch the magnetization state of the MTJs. When compared with previous STT-MRAM-based designs, the proposed compressor shows 97% improvement in power-delay product (PDP) characteristics. The write circuit in DSH-MRAM consumes merely 5 nW in comparison to 2 μW by conventional STT-MRAM designs. Moreover, the narrow write pulse promotes the proposed design for input frequencies up to 1 GHz.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".