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Record W2151471392 · doi:10.1109/fccm.2011.48

FUSE: Front-End User Framework for O/S Abstraction of Hardware Accelerators

2011· article· en· W2151471392 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 institutionsSimon Fraser University
Fundersnot available
KeywordsComputer scienceEmbedded systemFuse (electrical)Field-programmable gate arrayOperating systemFront and back endsSoftwareAbstractionProcess (computing)Computer architectureHardware accelerationComputer hardwareEngineering

Abstract

fetched live from OpenAlex

SoCs can be implemented on a single FPGA, offering designers a unique opportunity for Embedded Systems. Instead of defining a fixed architecture early in the design process, the reconfigurable platform allows architectural redesign to meet the system's specific needs. However, the ability to instantiate new modules in the reconfigurable hardware provides a unique set of challenges for integration, particularly to the software (SW) designer. Specifically, the Operating System (OS) cannot automatically abstract these platform changes without redesign. In this paper, we present FUSE, a framework for HW accelerator abstraction that provides: 1) transparency to the SW designer at the application level, and 2) OS support for easy HW accelerator integration. We illustrate FUSE as an API for an embedded Linux OS with POSIX threads on Xilinx's Micro Blaze on a Virtex5. For three different applications and HW accelerators, we achieve performance speedups ranging from 6.4-37×.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.839
Threshold uncertainty score0.447

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 science0.0010.000
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 head0.072
GPT teacher head0.295
Teacher spread0.223 · 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

Citations76
Published2011
Admission routes1
Has abstractyes

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