A Parallel Processing Library for User-friendly Applications
Bibliographic record
Abstract
Clusters of commodity, "off the shelf" workstations have given developers and users access to scalable and affordable computing resources. However, unlike large, symmetric multi-processing machines, these clusters have an up front cost in complexity, both for the developer and the user. Existing software frameworks have attempted to mitigate this complexity with varied success. In most frameworks, the user is forgotten and left to deal with an unwieldy application. This thesis presents the design, development and testing of a new C++ computer programming library, Scopira Agents Library (SAL). SAL is a message passing interface and implementation suitable for building parallel applications, with a focus on developer ease of use and user application deployment specification. The target developers and users of such a solution would be those who prefer an easy to develop library, with simpler deployment and application integration options with acceptable sacrifices to performance and scalability. The novelty of this parallel programming library is that it is more user-friendly than other existing libraries. This novelty has two major facets: (i) programmer-usability and productivity and (ii) application integration. Together, they permit a wider range of programmers to utilize parallel programming in a wider range of new and existing applications. This goal, user-friendliness, is rare among current parallel programming libraries. The result of the novelty is that parallel programming can be embedded into more applications, especially desktop applications. The user base and use cases for parallel applications can be increased, resulting in more efficient use of resources in a variety of applications. With increased efficiency, work can be performed in less time and larger problems can be tackled.
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How this classification was reachedexpand
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 | 0.001 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".