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Ali TehraniJamsaz

3 accepted papers

2025

AutoParLLM: GNN-guided Context Generation for Zero-Shot Code Parallelization using LLMs

NAACL 2025long

In-Context Learning (ICL) has been shown to be a powerful technique to augment the capabilities of LLMs for a diverse range of tasks. This work proposes AutoParLLM, a novel way to generate context using guidance from graph neural networks (GNNs) to generate efficient parallel codes. We evaluate Auto…

2024

CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming

NeurIPS 2024poster

Automatic translation of programming languages has garnered renewed interest, driven by recent advancements in large language models (LLMs). Encoder-decoder transformer models, in particular, have shown promise in translating between different programming languages. However, translating between a la…

Cited by 1SourcePDFScholar
2023

PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis

NeurIPS 2023poster

The remarkable growth and significant success of machine learning have expanded its applications into programming languages and program analysis. However, a key challenge in adopting the latest machine learning methods is the representation of programming languages which has a direct impact on the a…

Cited by 9SourcePDFScholar