Automated System for Heterogeneous Resource Management

Automated system designers that can adapt to the workload complexity and infrastructure heterogeneity of smart data centers are increasingly critical. We explore the use of artificial intelligence technologies for autonomous system management. We propose to implement two main levels of autonomous management. The first one is to use automated search methods to enable efficient mapping of neural network operations to heterogeneous platforms. The other is to implement automatic assembly and management of hardware.