25th Anniversary International Conference on Supercomputing Anniversary Volume -
Bibliographic record
Abstract
The International Conference on Supercomputing (ICS) was born in 1987 in Athens, Greece. Some of us have been associated with this conference since its very beginning, and we take great joy and pride in seeing it become successful and now pass the quarter century mark. A decision was made to celebrate the silver jubilee by publishing a 25th Anniversary Volume consisting of some of the most important papers presented at the conference over the years, together with the authors' retrospectives. The ideal would have been to pick one paper from each of the 25 years that had the greatest impact, and making sure that no more than one paper was from the same author or set of authors. I am happy to report that we did not follow these rules too rigidly and did not rely blindly on citation counts of papers. The distinguished committee that made the final decisions was a group of former ICS program committee chairs: Eduard Ayguade, Kyle Gallivan, Avi Mendelson, Alex Nicolau, Constantine Polychronopoulos, Mateo Valero, Alex Veidenbaum, Harry Wijshoff and myself. The committee selected 35 papers after extensive discussion. These papers and their authors' retrospectives appear in this volume. Several selected papers are included without a retrospective; their authors chose not to write one or had a very tough work schedule and could not do it in time. Only 32 of the selected papers are reprinted in this volume however, because ACM does not hold the copyright to papers from ICS'87.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.293 | 0.266 |
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".