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Record W4254204212 · doi:10.22215/etd/2016-11577

Automated Pipelining for Clocked CMOS Logic and FPGAs

2016· dissertation· en· W4254204212 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
Typedissertation
Languageen
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsCarleton University
Fundersnot available
KeywordsVerilogComputer scienceCMOSField-programmable gate arrayVirtexElectronic engineeringComputer hardwareLogic synthesisLogic gateEmbedded systemComputer architectureEngineering

Abstract

fetched live from OpenAlex

Achieving multi-Gbps clock speeds with static CMOS logic requires migrating designs to smaller geometries, which present a higher development and fabrication cost. Instead, this research investigates the use of clocked CMOS logic to create an inherently pipelined circuit that can be clocked up to 2.5x faster than the standard cells available in the IC design kit. An algorithm was developed and implemented in Perl to process Verilog RTL netlists for compatibility with the clocked logic. As an example application, a cascaded integrator comb (CIC) filter for RF DSP was designed with the clocked CMOS and fabricated in the IBM 130 nm process. Unfortunately, due to an oversight with designing the boundary scan chain, true functionality of the circuit could not be verified. In another demonstration of concept, the algorithm was successfully applied to a QAM modulator design on a Xilinx Virtex-5 FPGA, which achieved a clock speed of 548 MHz.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.760
Threshold uncertainty score0.550

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 head0.036
GPT teacher head0.328
Teacher spread0.292 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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