Proceedings of the 18th ACM international symposium on High performance distributed computing
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 our great pleasure to welcome you to the 18th ACM International Symposium on High Performance Distributed Computing. This year's symposium continues its tradition of being the premier forum for presentation of research results and experience reports on latest research findings on the design and use of parallel and distributed systems for high end computing, collaboration, data analysis, and other innovative applications. This installment takes place in Garching near Munich, Germany, June 11-13, 2009. Topics of interest include HPDC architectures, high end communications, data management and transport, software environments, operating system technologies, grid middleware, applications and algorithms, as well as fault tolerance. Co-located with HPDC 09 are six workshops. We welcome the Workshop on Challenges for Large Applications in Distributed Environments (CLADE 09), the Second International Workshop on Data-Aware Distributed Computing (DADC 09), the Workshop on Large-Scale System and Application Performance (LSAP 09), the Workshop on Monitoring, Logging and Accounting in Production Grids (MLA 09), the Workshop on Resiliency in High-Performance Computing (Resilience 09), and the 4th UPGRADE-CN Workshop on Content Management and Delivery in Large-Scale Networks (UPGRADE-CN 09). The call for papers attracted 68 submissions from Asia, Canada, Europe, Africa, and the United States. The program committee accepted 20 papers that cover a variety of topics, including Grid middleware and distributed algorithms, resource management and scheduling, data management, parallel algorithms and applications, workflow and dataflow applications, I/O and parallel computing. We hope that these proceedings will 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.
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 | 0.003 | 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