Proceedings of the 1st international workshop on Multicore software engineering
Bibliographic record
Abstract
Welcome to the International Workshop on Multicore Software Engineering (IWMSE 2008), the first workshop to focus on the software engineering challenges of chip-multiprocessors, or multi/manycore computers. With the emergence of multi/manycore, parallelism has become affordable at all levels, and software engineers now face the challenge of parallelizing performance-critical applications of all sorts, not just numeric applications. The workshop is intended to bring together researchers and practitioners with diverse backgrounds to advance the state of the art in software engineering for multi/manycore parallel applications. It aims to establish a community interested in advancing tools and methods for the cost-effective development of a broad spectrum of parallel applications, to start and extend a significant research dialog, and to push the boundaries of multicore software. The call for papers attracted 14 submissions from Australia, Canada, China, France, Germany, India, Russia, Sweden, United Kingdom, and the United States. The program committee accepted eight papers that cover a variety of topics, including parallel libraries, programming models and fault detection, multicore applications, and experience reports. In addition, the program includes a tutorial on Intel® Threading Building Blocks -- an open source library that was designed to simplify programming for multi-core platforms -- and a tutorial on parallel computing with X10, a language that supports a variety of concurrent programming idioms. Capturing an initial state of research and practice, we hope that these proceedings serve as a valuable reference for researchers and developers.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.057 | 0.024 |
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".