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Record W2951713654 · doi:10.1109/fpt.2018.00040

Synthesizable Heterogeneous FPGA Fabrics

2018· article· en· W2951713654 on OpenAlex
Brett Grady, Jason H. Anderson

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
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStratixField-programmable gate arrayVerilogComputer scienceEmbedded systemApplication-specific integrated circuitReuseComputer architectureParallel computingComputer hardwareEngineering

Abstract

fetched live from OpenAlex

We present an automated framework for the generation of synthesizable FPGAs with heterogeneous functional blocks and carry chains, as modelled with the open-source Verilog-to-Routing (VTR) FPGA architecture evaluation framework. VTR's modelling of hardened blocks, such as DSPs and BRAMs, is leveraged to generate synthesizeable FPGAs mappable via VTR's Verilog frontend. The generated Verilog source for the FPGA can be synthesized to target any conventional semiconductor process via an industry-standard ASIC toolflows with minimal implementation effort. We model a Stratix IV-style FPGA architecture, complete with carry chains, DSPs and BRAMs, and compare area/performance with the commercial Stratix IV FPGA. The area and performance gap between the fully synthesizable and commercial fabrics for a set of benchmarks using the heterogeneous blocks is 3.2× and 2.3×, respectively. Optimizations to reduce the gap are discussed.

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: Empirical · Consensus signal: none
Teacher disagreement score0.957
Threshold uncertainty score0.664

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)0.0010.000

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 head0.010
GPT teacher head0.201
Teacher spread0.191 · 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

Citations20
Published2018
Admission routes1
Has abstractyes

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