AI4Dev-2025 2025 : AI4Dev - The Workshop on AI Assisted Software Development for HPC in conjunction with the 54th International Conference on Parallel Processing, ICPP 2025
The goal of the AI Assisted Software Development for High-performance Computing (HPC) workshop (AI4Dev) is to create a forum composed of researchers, scientists, application developers, computing centers, and industry staff to discuss ideas on how artificial intelligence can help in the whole process of HPC software development. The workshop will feature contributed papers and invited talks in the area.
The workshop invites submissions of original research papers. Papers should be no longer than 8 pages (including references) and must be formatted according to the IEEE 2-column conference style.
Papers should be submitted in PDF format via the ICPP Linklings submission system (on the website).
We expect papers in the following areas (but not limited to):
- AI and/or Machine Learning (AI/ML) techniques to improve programming productivity
- Performance analysis driven by AI and ML
- Debugging and testing driven by AI/ML
- AI/ML-assisted compiler optimizations and code generation
- Auto-tuning and performance portability using AI/ML
- Code synthesis and generation using automated AI/ML techniques
- AI-assisted code recommendations for code maintainability, performance and correctness
- IDE extensions using ML for improved programming productivity
- AI-assisted software building and deployment
- Mining best programming practices using ML
- Addressing security, privacy, and licensing concerns using AI/ML for software development
The workshop invites submissions of original research papers. Papers should be no longer than 8 pages (including references) and must be formatted according to the IEEE 2-column conference style.
Papers should be submitted in PDF format via the ICPP Linklings submission system (on the website).
We expect papers in the following areas (but not limited to):
- AI and/or Machine Learning (AI/ML) techniques to improve programming productivity
- Performance analysis driven by AI and ML
- Debugging and testing driven by AI/ML
- AI/ML-assisted compiler optimizations and code generation
- Auto-tuning and performance portability using AI/ML
- Code synthesis and generation using automated AI/ML techniques
- AI-assisted code recommendations for code maintainability, performance and correctness
- IDE extensions using ML for improved programming productivity
- AI-assisted software building and deployment
- Mining best programming practices using ML
- Addressing security, privacy, and licensing concerns using AI/ML for software development