MétaCan
Menu
Back to cohort
Record W3013676662 · doi:10.1145/3372491

Feel Free to Interrupt

2020· article· en· W3013676662 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

VenueACM Transactions on Reconfigurable Technology and Systems · 2020
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceInterruptTask (project management)Context switchDebuggingField-programmable gate arrayContext (archaeology)Embedded systemOverhead (engineering)DeadlockInterface (matter)Distributed computingVariety (cybernetics)Operating systemMicrocontroller

Abstract

fetched live from OpenAlex

Saving and restoring an FPGA task state in an orderly manner is essential to enable hardware checkpointing, which is highly desirable to improve the ability to debug cloud-scale hardware services, and context switching, which allows multiple users to share FPGA resources. However, these features require task interruption, and stopping a task at an arbitrary time can cause several hazards including deadlock and data loss. In this article, we build a context saving and restoring simulator to simulate and identify these hazards. In addition, we derive design rules that should be followed to achieve safe task interruption. Finally, we propose task wrappers that can be placed around an FPGA task to implement these rules. The timing and area overheads added by these wrappers are very small; they add 1.8% area and no timing overhead to a full Memcached system. Taken together, these design rules and wrappers enable safe checkpointing and context switching in a wide variety of FPGA tasks, including those with multiple clocks, multi-cycle I/O transactions, and interface dependencies.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.026
GPT teacher head0.241
Teacher spread0.215 · 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