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Record W2041333130 · doi:10.1109/tcsii.2015.2407711

A Variation-Tolerant MRAM-Backed-SRAM Cell for a Nonvolatile Dynamically Reconfigurable FPGA

2015· article· en· W2041333130 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsMagnetoresistive random-access memoryField-programmable gate arrayStatic random-access memoryNon-volatile memoryComputer scienceSpin-transfer torqueRacetrack memoryUniversal memoryRandom accessEmbedded systemComputer hardwareRandom access memorySemiconductor memoryMemory managementPhysicsInterleaved memoryMagnetic fieldMagnetization

Abstract

fetched live from OpenAlex

Adding a spin-transfer-torque (STT) magnetoresistive random-access memory (MRAM) to a static random-access memory (SRAM) cell to produce an MRAM-backed SRAM cell for a nonvolatile field-programmable gate array (FPGA) is proposed. The proposed cell reduces the time to reconfigure the FPGA following a power-down and enables fast wake-ups and power gating. With the proposed restore operation, data are recalled with no error even in the presence of mismatch. Simulation results confirm that data can be stored in the proposed cell in 80 ns and restored in less than 1 ns.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.229
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it