Vancouver 2: Improving Programmability of Contemporary Heterogeneous Architectures, Final Report
Bibliographic record
Abstract
The University of Oregon (UO) was a partner in the Vancouver 2 project together with Oak Ridge National Laboratory (ORNL), the University of Illinois-Urbana/Champaign (UIUC), and the Geor- gia Institute of Technology (GT). UO’s objective in the project was to advance the performance technology for evolving heterogenous computing systems, especially for exascale platforms. During the project period, our efforts focused on the advances taking place in manycore and accelera- tor processors, specifically those found in GPU and MIC devices. In addition to the design and development of novel performance measurement and analysis techniques, UO demonstrated these capabilities on real HPC applications and current generation heterogeneous machines. The following final report summarizes our accomplishments during the Vancouver 2 project, highlighting research work in the recent year (Year 3).
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".