A multiword based high speed ECC scheme for low-voltage embedded SRAMS
Bibliographic record
Abstract
This paper presents a multiword based error correction code (MECC) scheme to mitigate SEUs in low-voltage SRAMs. MECC combines four 32 bit data words to form a composite 128 bit ECC word and uses optimized transmission-gate XOR logic, thus significantly reducing check-bit overhead and error correction time, respectively. Use of composite word warrants a unique write operation where MECC updates checkbits by simultaneously writing one data word and reading the other three data words. Two composite words are interleaved in a row to tackle multi-bit SEU. In addition, the supply voltage of the SRAM is reduced to save leakage and active power. A 64kb SRAM with MECC implemented in 90nm CMOS technology consumes 154 muW leakage power and 375 muW active power at 0.6 V and 100 MHz, showing improved area and speed-power efficiency than conventional single-word ECC and existing multiword ECC schemes.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".