Proceedings of the 8th annual IEEE/ACM international symposium on Code generation and optimization
Bibliographic record
Abstract
On behalf of the entire Program Committee, it is our pleasure to present the final program of papers selected for CGO 2010. This year we received a total of 70 submissions. Program Committee members were provided the opportunity to bid on the papers to review. Each paper was assigned to 4 PC members, with an additional review assigned to an expert solicited by the Program Chairs. Each paper received on average 4.94 reviews. The entire review process was double-blind. Papers receiving reviews with large deviations were discussed by PC members through email prior to the Program Committee Meeting. The CGO 2010 Program Committee Meeting was held in Boston, MA on Saturday November 7th. 27 of the 31 PC members attended in-person, with one person attending electronically. We particularly want to acknowledge those PC members that traveled long distances and internationally to be present at the meeting. This year CGO received a high number of quality papers. 29 papers were selected for the final program. CGO continues to draw a high percentage of international submissions; 44.3% of the submissions had at least one author from outside of the US. CGO also maintained its tradition of drawing contributions from industry, with 14.3% of the submissions having at least one author from industry. We are also happy to present two stimulating keynote talks from industry leaders. Ben Zorn from Microsoft Research will talk to us about a new definition of performance for future applications. CJ Newburn from Intel will present his perspectives on heterogeneous computing systems, and specifically the role that Intel technology will play. We thank our keynotes for agreeing to spend their time sharing their thoughts with the CGO community.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.060 | 0.021 |
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".