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Record W2988233485 · doi:10.1587/elex.16.20190600

Novel bit-serial semi-systolic array structure for simultaneously computing field multiplication and squaring

2019· article· en· W2988233485 on OpenAlexaff
Atef Ibrahim

Bibliographic record

VenueIEICE Electronics Express · 2019
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsUniversity of Victoria
FundersDeanship of Scientific Research, Prince Sattam bin Abdulaziz UniversityPrince Sattam bin Abdulaziz University
KeywordsMultiplication (music)Systolic arrayComputer scienceBit (key)ArithmeticParallel computingField (mathematics)MathematicsEmbedded systemVery-large-scale integrationComputer networkCombinatorics

Abstract

fetched live from OpenAlex

This paper presents a novel bit-serial semi-systolic array structure to simultaneously execute modular multiplication and squaring operations in GF(2 m ). The architecture is explored by using a systematic methodology based on the proper choice of the scheduling and projection vectors applied to the algorithm dependency graph. The explored architecture has the advantage of sharing the data-path between the two operations, and hence it leads to saving more space compared to the case of using a separate data-path for each operation. Also, the simultaneous calculation of both operations significantly decreases the execution time required to perform modular exponentiation operation, as it mainly depends on these two core operations. Complexity analysis indicates that the developed bit-serial semi-systolic array structure outperforms the latest exiting competitor bit-serial systolic and non-systolic structures in terms of area-time (AT) by at least 24%. This makes the proposed structure more appropriate for use in resource-constrained cryptographic processors.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.611
Threshold uncertainty score0.767

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 science0.0010.000
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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2019
Admission routes1
Has abstractyes

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