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Record W2133537407 · doi:10.1109/csicc.2009.5349361

Multi parametric optimized architectural synthesis of an application specific processor

2009· article· en· W2133537407 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

Venue2009 14th International CSI Computer Conference · 2009
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsToronto Metropolitan University
FundersCMC MicrosystemsOntario Innovation Trust
KeywordsComputer scienceEmbedded systemApplication-specific integrated circuitField-programmable gate arrayThroughputOverhead (engineering)SoftwareSystem on a chipComputer architectureComputer hardwareProcess (computing)WirelessOperating system

Abstract

fetched live from OpenAlex

Recent advancements in the field of multimedia and wireless communications have led to a wide array of application and services requiring high data processing rate at minimal power consumption. This new generation of data hungry portable devices requires power efficient hardware solutions where the operational specifications are as important as objective functionality. Conventional processing solutions like MIPS fall short on real time computational intensive operations due to large software overhead. This class of applications demands dedicated hardware units like Application Specific Processors (ASP) working as hardware accelerators for intensive data processing operations. In this paper we describe a novel Register Transfer Level (RTL) synthesis process of a power and throughput optimized ASP for a sample application. The ASP implemented on an FPGA, can serve as a hardware accelerator for system on chip (SOC) or as a standalone Application Specific Integrated Circuit (ASIC) at silicon level.

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 categoriesMeta-epidemiology (narrow)
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 score0.954
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.031
GPT teacher head0.286
Teacher spread0.255 · 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