Retargeting and enhancing a compact multitasking kernel for the Altera Nios II processor
Bibliographic record
Abstract
This paper describes the retargeting and further enhancement of a compact multitasking kernel for the 32-bit Altera Nios II processor. The kernel, called QUERK for Queen's University Educational Real-time Kernel, was originally written in assembly language and then the C language for the Motorola (and then Freescale) 68HC11 processor. Consisting of less than 200 lines of assembly-language instructions, the kernel was intended for educational purposes on undergraduate laboratory equipment in use at the time it was created. The software also supported undergraduate capstone project activity. To migrate the software to the 32-bit Altera Nios II processor that subsequently replaced the 8-bit 68HC11 in undergraduate laboratory activity, and to investigate issues arising from differences between the two instruction sets, this paper describes the retargeting of the kernel at the level of assembly language. The results reveal that the number of assembly-language source instructions for the base kernel with relinquish, block, and unblock services increased by less than 9% for the Nios II in comparison to the 68HC11. Although many additional instructions are needed to save and restore the larger number of registers for the Nios II, reductions in the number of instructions needed in other parts of the kernel aid in offsetting that increase in instructions. Further enhancements of the kernel are also described with support for timer delay requests, dynamic memory management, and interprocess communication with message passing. Potential future enhancements are also described.
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.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".