Use of "virtual" (simulated) hardware devices in microprocessor laboratories and tutorials
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
It is a common problem in industry that the development of software does not go hand-in-hand with the development of the hardware that the software is intended to control. A similar situation can occur in the undergraduate laboratory. Here a student, having designed the software component of a project, can't gain access to the necessary hardware to prepare for or complete a laboratory because of schedule/security difficulties. Over the past year we have overcome this problem by using "virtual" hardware, where device operation is simulated in software. We have generalized the approach so that the virtual devices can be used in conjunction with microprocessor simulator software and with actual evaluation boards for both RISC and CISC systems. We are in the preliminary development stages of a new HTML Web page approach where we control, rather than just launch, these commercial simulation packages. Such an approach would provide a controlled, interactive, tutorial environment for students taking microprocessor courses. There are further industrial and academic advantages of such an approach which can help to overcome the initial learning curve for the tools. We discuss the basics of developing "virtual" devices for use with the Windows based development environment provided with Software Development Systems 68 K and PowerPC free sample kits. These devices can then be ported to the Motorola M68332EVK and Advanced Micro Devices' SA29200 microprocessor evaluation boards to provide actual hardware experience.
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 | 0.000 | 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 it