CGRA4ML: A Hardware/Software Framework to Implement Neural Networks for Scientific Edge Computing

1. 1Design and generate parameterized accelerators using CGRa4ML's modular framework
2. 2Implement neural networks on the generated accelerators for scientific edge computing
3. 3Integrate the accelerators into edge computing applications using software frameworks
4. 4Verify and validate the performance of the neural networks on the accelerators

ML engineers and researchers on a team can benefit from CGRa4ML as it provides a modular framework for generating parameterized accelerators, while software engineers can utilize it for integrating ML models into edge computing applications

💡 CGRa4ML provides a modular and open-source framework for generating parameterized accelerators for neural networks in edge computing

🚀 CGRa4ML: A framework for implementing neural networks in scientific edge computing