Proceedings of the 2003 international workshop on System-level interconnect prediction
Bibliographic record
Abstract
SLIP exists to bring together researchers working in many areas related to interconnections who would otherwise not have a chance to interact. Specifically, interconnect is studied at a range of levels from technology to its impact on computer architecture or packaging issues. As an example, interconnect technologists tend to be isolated from researchers working on physical design, wire planning, IC microarchitecture, and other fields. However, it is exactly these groups of people that must interact to develop a cohesive and systematic approach to addressing the woes that interconnect is lately responsible for - these issues include signal integrity (coupling, both capacitively and inductively), delay, power consumption, yield, and chip density. SLIP has evolved over the past five years to include more and more of these topics while maintaining a distinct prediction personality. For instance, in this year's proceedings there are several FPGA-oriented papers as well as efforts at post-Rentian analysis of wirelength distributions. We have also brought in three invited speakers from highly distinguished research labs (IBM, Intel, and Philips) to provide their perspective on issues ranging from the practical (how do current wirelength distribution models actually fit to real commercial chips?) to the more visionary (how can routability be captured and/or predicted at the logic synthesis stage of design?).We are happy to see that the international flavor of the workshop is continued again this year as there are a number of groups from Europe presenting their work alongside US and Canadian researchers. Furthermore, SLIP 2004 will be held in Paris, co-located with Design, Automation and Test Europe (DATE), which will expose the workshop to a whole new audience.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.027 | 0.009 |
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 source (direct Gemma or distilled Codex), 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".