ULEEN: A Novel Architecture for Ultra Low-Energy Edge Neural Networks

The deployment of AI models on low-power, real-time edge devices requires accelerators for which energy, latency, and area are all first-order concerns. There are many approaches to enabling deep neural networks (DNNs) in this domain, including pruning, quantization, compression, and binary neural networks (BNNs), but with the emergence of the "extreme edge", there is now a demand for even more efficient models. In order to meet the constraints of ultra-low-energy devices, we propose ULEEN, a model architecture based on weightless neural networks. Weightless neural networks (WNNs) are a class of neural model which use table lookups, not arithmetic, to perform computation. The elimination of energy-intensive arithmetic operations makes WNNs theoretically well suited for edge inference; however, they have historically suffered from poor accuracy and excessive memory usage. ULEEN incorporates algorithmic improvements and a novel training strategy inspired by BNNs to make significant strides in improving accuracy and reducing model size. We compare FPGA and ASIC implementations of an inference accelerator for ULEEN against edge-optimized DNN and BNN devices. On a Xilinx Zynq Z-7045 FPGA, we demonstrate classification on the MNIST dataset at 14.3 million inferences per second (13 million inferences/Joule) with 0.21 $\mu$s latency and 96.2% accuracy, while Xilinx FINN achieves 12.3 million inferences per second (1.69 million inferences/Joule) with 0.31 $\mu$s latency and 95.83% accuracy. In a 45nm ASIC, we achieve 5.1 million inferences/Joule and 38.5 million inferences/second at 98.46% accuracy, while a quantized Bit Fusion model achieves 9230 inferences/Joule and 19,100 inferences/second at 99.35% accuracy. In our search for ever more efficient edge devices, ULEEN shows that WNNs are deserving of consideration.Comment: 14 pages, 14 figures Portions of this article draw heavily from arXiv:2203.01479, most notably sections 5E and 5F.

AIM (Artery in microgravity): Design and development of an ice cubes mission

The Artery In Microgravity (AIM) project is the first experiment to be selected for the “Orbit Your Thesis!” programme of ESA Academy. It is a 2U experiment cube designed for the ICE Cubes facility on board of the International Space Station. The experiment is expected to be launched on SpaceX-20 in early 2020. The project is being developed by an international group of students from ISAE-SUPAERO and Politecnico di Torino, under the supervision of the ISAE-SUPAERO and Politecnico di Torino staff. The experiment is a test-bench for investigating haemodynamics in microgravity focusing on coronary heart disease, the most common form of cardiovascular disease and the cause of approximately 9 million deaths every year. Coronary heart disease is caused by stenosis of the coronary artery due to the build-up of plaque. While the development of atherosclerosis is not fully understood, the primary event seems to be subtle and repeated injury to the artery walls through various mechanisms including physical stresses from flow disturbances as well as from systemic and biological risk factors. In the presence of severe stenosis, patients are treated with the implantation of one or more coronary stents, which are tubular scaffolds devoted to restore and maintain myocardial perfusion. The coronary stenting procedure is largely applied (e.g., 1.8 million stents per year implanted in USA) In view of the impact that coronary artery disease has on humans, as well as of the increasing number of people that will be involved in space flights in the future, the way astronauts in space coronary hemodynamics is affected by the absence of gravity in the presence of stenosis or of stenting needs to be investigated in depth. In addition, as most stents are metallic objects, the radiation exposure in space might interact with their surface, altering blood flow, inducing particles release and ultimately leading to stent failure. Therefore, the aim of AIM is to start studying the vascular haemodynamics in a stented and a stenosed coronary artery on Earth and in microgravity and the stent-radiation coupling. This will allow to learn about the effect gravity plays on coronary artery haemodynamics, the effects of microgravity and radiation on the performance of implantable devices and ultimately the risks of myocardial infarction to astronauts on long-distance spaceflight. The experimental setup consists of a closed hydraulic loop containing two models of a coronary artery in series. An electric pump and reservoir will control the flow of a blood-mimicking fluid through the system. One model of the coronary artery will contain a coronary stent. The pressure of the fluid will be studied along its path using a series of pressure sensors and a camera will visualise the flow. The same experiments will be repeated on the ground with the same conditions as the in-flight model for comparison. The paper will outline in detail the design and development of the AIM experiment cube and the results of testing. The full data and results will be available after the completion of the mission which is expected to be between March and June 2020

Effect of Dietary Proteins on Growth, Food Conversion and Digestive Enzyme Activity of Juvenile Macrobrachium Rosenbergii

School of Industrial Fisheries, Cochin University of Science and Technolog