No abstract

Computing platforms are evolving towards heterogeneous architectures including processors of different types and field programmable gate arrays (FPGAs), used as hardware accelerators for speeding up specific functions. The increasing capacity and performance of modern FPGAs, with their partial reconfiguration capabilities, have made them attractive in several application domains, including space applications.This paper proposes a framework for supporting the development of safety-critical real-time systems that exploit hardware accelerators developed through FPGAs with dynamic partial reconfiguration capabilities.A model is first presented and then used to derive a response-time analysis to verify the schedulability of a real-time task set under given constraints and assumptions. Although the analysis is based on a generic model, the proposed framework has been conceived to account for several real-world constraints present on today's platforms and has been practically validated on the Zynq platform, showing that it can actually be supported by state-of-the-art technologies. Finally, a number of experiments are reported to evaluate the worst-case performance of the proposed approach on synthetic workload

The Fast TracKer (FTK) is an extremely powerful and very compact processing unit, essential for efficient Level 2 trigger selection in future high-energy physics experiments at the LHC. FTK employs Associative Memories (AM) to perform pattern recognition; input and output data are transmitted over serial links at 2 Gbit/s to reduce routing congestion at the board level. Prototypes of the AM chip and of the AM board have been manufactured and tested, in preparation of the imminent design of the final version.

As COVID-19 began to grip healthcare systems worldwide, worst-case models predicted huge demands for ventilators. The global community sprang to action, producing a large number of emergency "makeshift" ventilator designs. This brought about another problem: a gap between the quantity of new mechanical ventilators and the number of skilled physicians to operate them. New physicians could not complete training at the pace of ventilator production, which threatened to leave patients sitting untreated, next to unusable ventilators. To address this challenge, we developed a universal remote control system for makeshift ventilators that uses low-cost hardware addon modules to connect to different ventilators, and a three-tier control architecture to interface the ventilators with telemedicine software. We demonstrate system integration with two representative ventilator designs, adding a remote control option that allows caregivers to quickly and easily monitor and control these ventilators remotely.

The extended use of tracking information at the trigger level in the LHC is crucial for the trigger and data acquisition (TDAQ) system to fulfill its task. Precise and fast tracking is important to identify specific decay products of the Higgs boson or new phenomena, as well as to distinguish the contributions coming from the many collisions that occur at every bunch crossing. However, track reconstruction is among the most demanding tasks performed by the TDAQ computing farm; in fact, complete reconstruction at full Level-1 trigger accept rate (100 kHz) is not possible. In order to overcome this limitation, the ATLAS experiment is planning the installation of a dedicated processor, the Fast Tracker (FTK), which is aimed at achieving this goal. The FTK is a pipeline of high performance electronics, based on custom and commercial devices, which is expected to reconstruct, with high resolution, the trajectories of charged-particle tracks with a transverse momentum above 1 GeV, using the ATLAS inner tracker information. Pattern recognition and the track parameter extraction are expected to be performed in roughly 100 µs, allowing all the high level trigger selections to use the tracks provided by FTK in order to build high quality and robust triggering.