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Record W2094966716 · doi:10.1145/2145694.2145733

FCache

2012· article· en· W2094966716 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceSemaphoreCacheField-programmable gate arraySynchronization (alternating current)Embedded systemOverhead (engineering)Shared memoryComputer architectureMultiprocessingParallel computingOperating systemComputer network

Abstract

fetched live from OpenAlex

Much like other computing platforms in the world today, FPGAs are becoming increasingly larger and contain large amounts of reconfigurable logic. This makes FPGAs an acceptable platform for multiprocessor systems. However in today's world of FPGA computing, very limited infrastructure is available to facilitate the creation of cache coherent shared memory systems for FPGAs. This paper introduces FCache, a system for shared memory cache coherent processing on FPGAs. The paper also describes the mapping of the conventional shared bus to FPGAs using two distinct network implemented in FCache. FCache also provides flushing and multithreaded synchronization functionalities, such as locking and unlocking of a mutex variable, which is embedded in its cache component. Despite these additional functionalities, results show that FCache has little resource overhead compared to a previous more simplistic cache coherent system that was targeted for FPGAs.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.921
Threshold uncertainty score0.565

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 communication0.0000.001
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 head0.027
GPT teacher head0.265
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

Quick stats

Citations13
Published2012
Admission routes2
Has abstractyes

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