Trellis-SDP: A simple data-parallel programming interface
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
Some datasets and computing environments are inherently distributed. For example, image data may be gathered and stored at different locations. Although data parallelism is a well-known computational model, there are few programming systems that are both easy to program (for simple applications) and can work across administrative domains. We have designed and implemented a simple programming system, called Trellis-SDP, that facilitates the rapid development of data-intensive applications. Trellis-SDP is layered on top of the Trellis infrastructure, a software system for creating overlay metacomputers: user-level aggregations of computer systems. Trellis-SDP provides a master-worker programming framework where the worker components can run self-contained, new or existing binary applications. We describe two interface functions, namely trellis scan() and trellis gather(), and show how easy it is to get reasonable performance with simple data-parallel applications, such as Content Based Image Retrieval (CBIR) and Parallel Sorting by Regular Sampling (PSRS).
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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.008 | 0.002 |
| 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