MétaCan
Menu
Back to cohort
Record W1982078374 · doi:10.1145/1189736.1189737

Specifying memory consistency of write buffer multiprocessors

2007· article· en· W1982078374 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

VenueACM Transactions on Computer Systems · 2007
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceConsistency modelCache coherenceSequential consistencyWrite bufferParallel computingMemory modelConsistency (knowledge bases)ScalabilityShared memoryOut-of-order executionMultiprocessingWeak consistencyEquivalence (formal languages)Causal consistencyAbstractionProgramming languageStrong consistencyCPU cacheCorrectnessOperating systemCache

Abstract

fetched live from OpenAlex

Write buffering is one of many successful mechanisms that improves the performance and scalability of multiprocessors. However, it leads to more complex memory system behavior, which cannot be described using intuitive consistency models, such as Sequential Consistency. It is crucial to provide programmers with a specification of the exact behavior of such complex memories. This article presents a uniform framework for describing systems at different levels of abstraction and proving their equivalence. The framework is used to derive and prove correct simple specifications in terms of program-level instructions of the sparc total store order and partial store order memories.The framework is also used to examine the sparc relaxed memory order. We show that it is not a memory consistency model that corresponds to any implementation on a multiprocessor that uses write-buffers, even though we suspect that the sparc version 9 specification of relaxed memory order was intended to capture a general write-buffer architecture. The same technique is used to show that Coherence does not correspond to a write-buffer architecture. A corollary, which follows from the relationship between Coherence and Alpha, is that any implementation of Alpha consistency using write-buffers cannot produce all possible Alpha computations. That is, there are some computations that satisfy the Alpha specification but cannot occur in the given write-buffer implementation.

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 score0.683
Threshold uncertainty score0.915

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 communication0.0000.000
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 head0.029
GPT teacher head0.267
Teacher spread0.238 · 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