2 citations · 5 across the 8 of their papers we have counts for
9 papers
OMPILOT: Harnessing Transformer Models for Auto Parallelization to Shared Memory Computing Paradigms
Arijit Bhattacharjee, Ali TehraniJamsaz, Le Chen +4
Recent advances in large language models (LLMs) have significantly accelerated progress in code translation, enabling more accurate and efficient transformation across programming…
CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming
Ali TehraniJamsaz, Arijit Bhattacharjee, Le Chen +3
Recent advancements in Large Language Models (LLMs) have renewed interest in automatic programming language translation. Encoder-decoder transformer models, in particular, have sho…
MPI Errors Detection using GNN Embedding and Vector Embedding over LLVM IR
Jad El Karchi, Hanze Chen, Ali TehraniJamsaz +3
Identifying errors in parallel MPI programs is a challenging task. Despite the growing number of verification tools, debugging parallel programs remains a significant challenge. Th…
AutoParLLM: GNN-guided Context Generation for Zero-Shot Code Parallelization using LLMs
Quazi Ishtiaque Mahmud, Ali TehraniJamsaz, Hung Phan +5
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 \ourtool, a novel way to ge…
PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis
Ali TehraniJamsaz, Quazi Ishtiaque Mahmud, Le Chen +2
The remarkable growth and significant success of machine learning have expanded its applications into programming languages and program analysis. However, a key challenge in adopti…
Performance Optimization using Multimodal Modeling and Heterogeneous GNN
Akash Dutta, Jordi Alcaraz, Ali TehraniJamsaz +3
Growing heterogeneity and configurability in HPC architectures has made auto-tuning applications and runtime parameters on these systems very complex. Users are presented with a mu…
GraphBinMatch: Graph-based Similarity Learning for Cross-Language Binary and Source Code Matching
Ali TehraniJamsaz, Hanze Chen, Ali Jannesari
Matching binary to source code and vice versa has various applications in different fields, such as computer security, software engineering, and reverse engineering. Even though th…
ParaGraph: Weighted Graph Representation for Performance Optimization of HPC Kernels
Ali TehraniJamsaz, Alok Mishra, Akash Dutta +3
GPU-based HPC clusters are attracting more scientific application developers due to their extensive parallelism and energy efficiency. In order to achieve portability among a varie…
Learning Intermediate Representations using Graph Neural Networks for NUMA and Prefetchers Optimization
Ali TehraniJamsaz, Mihail Popov, Akash Dutta +2
There is a large space of NUMA and hardware prefetcher configurations that can significantly impact the performance of an application. Previous studies have demonstrated how a mode…