Energy Efficient Semi-Partitioned Scheduling for Embedded Multiprocessor Streaming Systems

Computer Systems, Imagery and Medi

On the Hard-Real-Time Scheduling of Embedded Streaming Applications

Computer Systems, Imagery and Medi

Buffer sizes reduction for memory-efficient CNN inference on mobile and embedded devices

Computer Systems, Imagery and Medi

Modeling, Analysis, and Hard Real-time Scheduling of Adaptive Streaming Applications

In real-time systems, the application's behavior has to be predictable at compile-time to guarantee timing constraints. However, modern streaming applications which exhibit adaptive behavior due to mode switching at run-time, may degrade system predictability due to unknown behavior of the application during mode transitions. Therefore, proper temporal analysis during mode transitions is imperative to preserve system predictability. To this end, in this paper, we initially introduce mode-aware data flow (MADF) which is our new predictable model of computation to efficiently capture the behavior of adaptive streaming applications. Then, as an important part of the operational semantics of MADF, we propose the maximum-overlap offset which is our novel protocol for mode transitions. The main advantage of this transition protocol is that, in contrast to self-timed transition protocols, it avoids timing interference between modes upon mode transitions. As a result, any mode transition can be analyzed independently from the mode transitions that occurred in the past. Based on this transition protocol, we propose a hard real-time analysis as well to guarantee timing constraints by avoiding processor overloading during mode transitions. Therefore, using this protocol, we can derive a lower bound and an upper bound on the earliest starting time of the tasks in the new mode during mode transitions in such a way that hard real-time constraints are respected.Computer Systems, Imagery and Medi

Energy-efficient and high-throughput CNN inference on embedded CPUs-GPUs MPSoCs

Computer Systems, Imagery and Medi

Adaptivity Support for MPSoCs Based on Process Migration in Polyhedral Process Networks

987209Computer System

Fault-Tolerant Nanosatellite Computing on a Budget

Computer Systems, Imagery and Medi

Scheduling Analysis of Imprecise Mixed-Criticality Real-Time Tasks

In this paper, we study the scheduling problem of the imprecise mixed-criticality model (IMC) under earliest deadline first with virtual deadline (EDF-VD) scheduling upon uniprocessor systems. Two schedulability tests are presented. The first test is a concise utilization-based test which can be applied to the implicit deadline IMC task set. The suboptimality of the proposed utilization-based test is evaluated via a widely-used scheduling metric, speedup factors. The second test is a more effective test but with higher complexity which is based on the concept of demand bound function (DBF). The proposed DBF-based test is more generic and can apply to constrained deadline IMC task set. Moreover, in order to address the high time cost of the existing deadline tuning algorithm, we propose a novel algorithm which significantly improve the efficiency of the deadline tuning procedure. Experimental results show the effectiveness of our proposed schedulability tests, confirm the theoretical suboptimality results with respect to speedup factor, and demonstrate the efficiency of our proposed algorithm over the existing deadline tunning algorithm. In addition, issues related to the implementation of the IMC model under EDF-VD are discussed.Computer Systems, Imagery and Medi

Low-memory and high-performance CNN inference on distributed systems at the edge

Computer Systems, Imagery and Medi