Cross-Paradigm Compilation across Programming Models: from Imperative to Asynchronous Graph
Bibliographic record
Abstract
Recent years have seen a rapid evolution in multi-core processor architectures.However, programming multi-core processors efficiently is a challenging endeavor [1], [2].Either programmers empirically or ad hoc identify parallelization opportunities in their sequential code, then manually parallelize the implementation, or parallel programming paradigms (with appropriate tooling and support) must be employed to automate parallelization efforts.Despite encouraging efforts such as OpenMP [3] and OpenCL[4], we are far from automated parallelization.Asynchronous Graph Programming (AGP) is a novel parallel paradigm that is amenable to automated parallelization for multi-core processors.However, its semantics are both foreign to most programmers, and too low-level to support software development at scale.Thus, this thesis explores the development of a cross-paradigm compiler, that can translate code in an imperative language (C) to AGP, allowing existing code-bases to be re-deployed and automatically parallelized, despite the semantics of their original language being sequential.Towards this, we define semantic transformations from (a sub-set of) C to AGP, and demonstrate the implementation of a compiler that implements those transformations.Our results show that it is indeed possible to transform C code into AGP code, and that transformed parallel implementations running on a multi-core system, for a suite of testing benchmarks, i outperform sequential code substantially.First and foremost, I am grateful to Almighty God for leading me down the path of knowledge.I would like to express my deep and sincere gratitude to my research supervisor, Dr. Paulo Garcia for giving me the opportunity to do research and providing invaluable guidance throughout this research.I can't say thank you enough for his tremendous support and help.In every meeting we had together, I have been inspired by his continuance support, patience, and guidance which was vital for the completion of this project.I appreciate his help throughout the whole thesis at times when he was trying to put me in the right path.Special thanks to students of our research group for their valuable comments and suggestions especially to Sebastien with whom I have worked for a period of time before our thesis begins.I would like to express my heartfelt gratitude to my
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".