CODAI’23: Workshop on Compilers, Deployment, and Tooling for Edge AI
Workshop Program
ROOM: H0.07
| Introduction & Keynote | |
|---|---|
| 10:00 – 10:30 | Welcome Coffee |
| 10:30 – 10:35 | Opening |
| 10:35 – 11:15 | Keynote: Next-generation Compilers for Emerging Systems |
| Session 1: Deployment and Optimization Techniques | |
| 11:15 – 11:40 | Scaling Up Quantization-Aware Neural Architecture Search for Efficient Deep Learning on the Edge |
| 11:40 – 12:05 | Tiny Machine Learning: Enabling Intelligence on Constrained Devices |
| 12:05 – 12:30 | Hardware-Aware Network Compression: From Data to Silicon |
| 12:30 – 13:30 | Lunch Break |
| Session 2: Compilation Frameworks and Techniques | |
| 13:30 – 13:55 | Accelerating Edge AI with Morpher: An Integrated Design, Compilation and Simulation Framework for CGRAs |
| 13:55 – 14:20 | Towards Rapid Exploration of Heterogeneous TinyML Systems using Virtual Platforms and TVM’s UMA |
| 14:20 – 14:45 | ART: An Actor transition systems RunTime for enabling efficient partitioning of neural network graphs |
| 14:45 – 15:10 | SYCL – A Modern C++ Programming Model for Accelerators |
| 15:10 – 15:40 | Coffee Break |
| Session 3: Applications | |
| 15:40 – 16:05 | Temporal Patience: Efficient Adaptive Deep Learning for Embedded Radar Data Processing |
| 16:05 – 16:30 | Pros and Cons of Executable Neural Networks for Deeply Embedded Systems |
| 16:30 – 16:55 | Software and Hardware for Sparse ML |
| 16:55 – 17:00 | Closing remarks |
