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Record W4241336885 · doi:10.1145/514001.514004

Retargetable binary utilities

2002· article· en· W4241336885 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.

Bibliographic record

VenueProceedings - ACM IEEE Design Automation Conference · 2002
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Search Problems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceBinary numberArithmeticMathematics

Abstract

fetched live from OpenAlex

Since software is playing an increasingly important role in system-on-chip, retargetable compilation has been an active research area in the last few years. However, the retargetting of equally important downstream system tools, such as assemblers, linkers and debuggers, has either been ignored, or falls short of meeting the requirements of modern programming languages and operating systems. In this paper, we present techniques that can automatically retarget the GNU binutils tool kit, which contains a large array of production-quality downstream tools. Other than having all the advantages enjoyed by open-source software by aligning to a de facto standard, our techniques are systematic, as a result of using a formal model of instruction set architecture (ISA) and application binary interface (ABI); and simple, as a result of leveraging free software to the largest extent.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.125
GPT teacher head0.267
Teacher spread0.142 · 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