53 citations · 153 across the 24 of their papers we have counts for
10 papers · 1 filter
FlashVideo: A Framework for Swift Inference in Text-to-Video Generation
Bin Lei, le Chen, Caiwen Ding
In the evolving field of machine learning, video generation has witnessed significant advancements with autoregressive-based transformer models and diffusion models, known for synt…
CompCodeVet: A Compiler-guided Validation and Enhancement Approach for Code Dataset
Le Chen, Arijit Bhattacharjee, Nesreen K. Ahmed +4
Large language models (LLMs) have become increasingly prominent in academia and industry due to their remarkable performance in diverse applications. As these models evolve with in…
HPC-GPT: Integrating Large Language Model for High-Performance Computing
Xianzhong Ding, Le Chen, Murali Emani +6
Large Language Models (LLMs), including the LLaMA model, have exhibited their efficacy across various general-domain natural language processing (NLP) tasks. However, their perform…
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…
DataRaceBench V1.4.1 and DataRaceBench-ML V0.1: Benchmark Suites for Data Race Detection
Le Chen, Wenhao Wu, Stephen F. Siegel +2
Data races pose a significant threat in multi-threaded parallel applications due to their negative impact on program correctness. DataRaceBench, an open-source benchmark suite, is…
Data Race Detection Using Large Language Models
Le Chen, Xianzhong Ding, Murali Emani +3
Large language models (LLMs) are demonstrating significant promise as an alternate strategy to facilitate analyses and optimizations of high-performance computing programs, circumv…
Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C++
Bin Lei, Caiwen Ding, Le Chen +2
In this study, we present a novel dataset for training machine learning models translating between OpenMP Fortran and C++ code. To ensure reliability and applicability, the dataset…
LM4HPC: Towards Effective Language Model Application in High-Performance Computing
Le Chen, Pei-Hung Lin, Tristan Vanderbruggen +3
In recent years, language models (LMs), such as GPT-4, have been widely used in multiple domains, including natural language processing, visualization, and so on. However, applying…
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…
Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation
Le Chen, Quazi Ishtiaque Mahmud, Hung Phan +2
Detecting parallelizable code regions is a challenging task, even for experienced developers. Numerous recent studies have explored the use of machine learning for code analysis an…