Overview

Prediction of new CeFeIn compounds with exa-AMD

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exa-AMD is a Python framework designed to accelerate the discovery and design of functional materials. The framework uses Parsl to build customizable and automated workflows that connect AI/ML tools, material databases, quantum mechanical calculations, and state-of-the-art computational methods for novel structure prediction. exa-AMD was designed to scale up on high-performance computing systems including supercomputers equipped with accelerators, such as the Nvidia and AMD GPUs.

Contents:

• Quickstart
  • Prerequisites
  • Installation
  • Run the tests
  • Using a JSON Configuration File
  • Command-line Usage
• Tutorial
  • 1. Clone the Repository
  • 2. Install Dependencies
  • 3. Prepare the Data and VASP Setup
  • 4. Prepare the JSON Configuration File
  • 5. Prepare the Parsl Configuration
  • 6. Run the Workflow
  • 7. Check the Results
• API Reference Guide
  • Parsl Tasks
  • Workflows
  • Parsl Configuration
  • Utils
• Contributors
  • Cai-Zhuang Wang
  • Ying Wai Li
  • Yongxin Yao
  • Feng Zhang
  • Weiyi Xia
  • Zhuo Ye
  • Maxim Moraru