Scalable Programming Models for Massively Multicore Processors
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
Including multiple cores on a single chip has become the dominant mechanism for scaling processor performance. Exponential growth in the number of cores on a single processor is expected to lead in a short time to mainstream computers with hundreds of cores. Scalable implementations of parallel algorithms will be necessary in order to achieve improved single-application performance on such processors. In addition, memory access will continue to be an important limiting factor on achieving performance, and heterogeneous systems may make use of cores with varying capabilities and performance characteristics. An appropriate programming model can address scalability and can expose data locality while making it possible to migrate application code between processors with different parallel architectures and variable numbers and kinds of cores. We survey and evaluate a range of multicore processor architectures and programming models with a focus on GPUs and the Cell BE processor. These processors have a large number of cores and are available to consumers today, but the scalable programming models developed for them are also applicable to current and future multicore CPUs.
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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 | 0.001 | 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