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Record W2167500722 · doi:10.1155/2010/159367

Mechanism of Resource Virtualization in RCS for Multitask Stream Applications

2010· article· en· W2167500722 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

VenueInternational Journal of Reconfigurable Computing · 2010
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyCMC MicrosystemsUBS
KeywordsComputer scienceEmbedded systemVirtualizationField-programmable gate arrayPipeline (software)Overhead (engineering)Reconfigurable computingComputer architectureCloud computingOperating system

Abstract

fetched live from OpenAlex

Virtualization of logic, routing, and communication resources in recent FPGA devices can provide a dramatic improvement in cost-efficiency for reconfigurable computing systems (RCSs). The presented work is “proof-of-concept” research for the virtualization of the above resources in partially reconfigurable FPGA devices with a tile-based architecture. The following aspects have been investigated, prototyped, tested, and analyzed: (i) platform architecture for hardware support of the dynamic allocation of Application Specific Virtual Processors (ASVPs), (ii) mechanisms for run-time on-chip ASVP assembling using virtual hardware Components (VHCs) as building blocks, and (iii) mechanisms for dynamic on-chip relocation of VHCs to predetermined slots in the target FPGA. All the above mechanisms and procedures have been implemented and tested on a prototype platform—MARS (multitask adaptive reconfigurable system) using a Xilinx Virtex-4 FPGA. The on-chip communication infrastructure has been developed and investigated in detail, and its timing and hardware overhead were analyzed. It was determined that component relocation can be done without affecting the ASVP pipeline cycle time and throughput. The hardware overhead was estimated as relatively small compared to the gain of other performance parameters. Finally, industrial applications associated with next generation space-borne platforms are discussed, where the proposed approach can be beneficial.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.270
Teacher spread0.258 · 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