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Found 6 papers, 1 papers with code
HPC-GPT: Integrating Large Language Model for High-Performance Computing
Large Language Models (LLMs), including the LLaMA model, have exhibited their efficacy across various general-domain natural language processing (NLP) tasks.
Data Race Detection Using Large Language Models
Large language models (LLMs) are demonstrating significant promise as an alternate strategy to facilitate analyses and optimizations of high-performance computing programs, circumventing the need for resource-intensive manual tool creation.
LM4HPC: Towards Effective Language Model Application in High-Performance Computing
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.
Structured Thoughts Automaton: First Formalized Execution Model for Auto-Regressive Language Models
We introduce a low-level language to write "cognitive program" for this execution model.
Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study
The FAIR Guiding Principles aim to improve the findability, accessibility, interoperability, and reusability of digital content by making them both human and machine actionable.
Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines
Programming Language Processing (PLP) using machine learning has made vast improvements in the past few years.
