Hardware-based accelerators for real-time machine learning. This project will tackle the challenge of applying real-time machine learning to massive high-frequency data. This project will leverage advancements in machine learning and hardware synthesis to implement computationally complex machine-learning algorithms on hardware-accelerated platforms, avoiding overhead delays incurred by software running on a processor.
High-performance real-time OS framework for low-power applications. Wireless network adapters, as they are being developed by Cisco, will find widespread use in the near future, as they are the basis of all mobile or otherwise disconnected intelligent devices. These devices must process data very rapidly, yet operate with minimal power consumption. We will develop operating system kernels that will support the secure, efficient and protected execution of the core processing firmware, and provide ....High-performance real-time OS framework for low-power applications. Wireless network adapters, as they are being developed by Cisco, will find widespread use in the near future, as they are the basis of all mobile or otherwise disconnected intelligent devices. These devices must process data very rapidly, yet operate with minimal power consumption. We will develop operating system kernels that will support the secure, efficient and protected execution of the core processing firmware, and provide application frameworks for the controlling higher software layers. We will also investigate and design hardware mechanisms that support the software while keeping power consumption minimal.Read moreRead less