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Record W2889995311 · doi:10.1109/fccm.2018.00026

High-Level Synthesis of FPGA Circuits with Multiple Clock Domains

2018· article· en· W2889995311 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
TopicEmbedded Systems Design Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceClock domain crossingElectronic circuitDigital clock managerClock skewStatic timing analysisSynchronous circuitClock signalField-programmable gate arrayBenchmark (surveying)Clock gatingParallel computingComputer hardwareEmbedded systemEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

We consider the high-level synthesis of circuits with multiple clock domains in a bid to raise circuit performance. A profiling-based approach is used to select time-intensive sub-circuits within a larger circuit to operate on separate clock domains. This isolates the critical paths of the sub-circuits from the larger circuit, allowing the sub-circuits to be clocked at the highest-possible speed. The open-source LegUp high-level synthesis tool (HLS) is modified to automatically insert clock-domain-crossing circuitry for signals crossing between two domains. The scheduling and binding phases of HLS were changed to reflect the impact of multiple clock domains on memory. Namely, the block RAMs in FPGAs are dual-port, where each port can operate on a different domain, implying that sub-circuits on different domains can access shared memory provided the domains of the memory ports are consistent with the sub-circuit domains. In an experimental study, we apply multi-clock domain HLS to the CHStone benchmark suite and demonstrate average wall-clock time improvements of 33%.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.842
Threshold uncertainty score0.493

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 head0.028
GPT teacher head0.241
Teacher spread0.213 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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