Virtual Single-Core for Multicore Real-Time Computing
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.
Bibliographic record
Abstract
This paper introduces Virtual Single-Core (VSC) technology that allows engineers to use a group of cores in a multicore computer as if the group of cores were a larger single-core computer. \n \nMulticore technology has many benefits, such as increased CPU bandwidth per chip. However, when used as is, inter-core interferences can be severe. Because of the potential for large and random delay spikes, the U.S. Federal Aviation Administration (FAA), European Aviation Safety Agency (EASA), and Transport Canada specify that only one core can be used, unless inter-core interference is specifically defined and handled. In addition, DO-178C: Software Considerations in Airborne Systems and Equipment Certification is for single-core chips only. \nSingle-core Equivalence (SCE) technology partitions the resources shared by cores in such a way that each core can be used as if it were a single-core computer. SCE is an effective solution that address certification authorities' concerns of intercore interference. However, a core in a multicore chip is often slower than a fast single-core chip. Therefore, a large multi-thread (task) application may not be scheduled within a core. \nVirtual Single-Core (VSC) technology extends the SCE technology so that a group of cores can be used to schedule a large application as if the VSC were a larger single-core computer. VSC greatly facilities the migration of certified avionics software from single-core computers to multicore computers.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it