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Record W2146486934 · doi:10.1145/2024724.2024787

Temporal isolation on multiprocessing architectures

2011· article· en· W2146486934 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsUniversity of Waterloo
FundersArmy Research OfficeAir Force Office of Scientific ResearchNational Science Foundation
KeywordsComputer scienceIsolation (microbiology)MultithreadingMultiprocessingAbstractionComputer architectureParallel computingSimultaneous multithreadingSoftwareSet (abstract data type)Memory hierarchyInstruction setEmbedded systemDistributed computingProgramming languageThread (computing)Cache

Abstract

fetched live from OpenAlex

Multiprocessing architectures provide hardware for executing multiple tasks simultaneously via techniques such as simultaneous multithreading and symmetric multiprocessing. The problem addressed by this paper is that even when tasks that are executing concurrently do not communicate, they may interfere by affecting each others' timing. For cyber-physical system applications, such interference can nullify many of the advantages offered by parallel hardware and can enormously complicate synthesis of software from models. This paper examines what changes need to be made at lower levels of abstraction to support temporal isolation for effective software synthesis. We discuss techniques at the microarchitecture level, in the memory hierarchy, in on-chip communication, and in the instruction-set architecture that can facilitate temporal isolation.

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 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 score0.939
Threshold uncertainty score0.222

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 head0.037
GPT teacher head0.263
Teacher spread0.226 · 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