Abstract

The reliance on Network-on-Chip (NoC)-based Multiprocessor Systems-on-Chips (MPSoCs) is proliferating in modern embedded systems to satisfy the higher performance requirement of multimedia streaming applications. Task level coarse grained software pipeling also called re-timing when combined with Dynamic Voltage and Frequency Scaling (DVFS) has shown to be an effective approach in significantly reducing energy consumption of the multiprocessor systems at the expense of additional delay. In this article we develop a novel energy-aware scheduler considering tasks with conditional constraints on Voltage Frequency Island (VFI)-based heterogeneous NoC-MPSoCs deploying re-timing integrated with DVFS for real-time streaming applications. We propose a novel task level re-timing approach called R-CTG and integrate it with non linear programming-based scheduling and voltage scaling approach referred to as ALI-EBAD. The R-CTG approach aims to minimize the latency caused by re-timing without compromising on energy-efficiency. Compared to R-DAG, the state-of-the-art approach designed for traditional Directed Acyclic Graph (DAG)-based task graphs, R-CTG significantly reduces the re-timing latency because it only re-times tasks that free up the wasted slack. To validate our claims we performed experiments on using 12 real benchmarks, the results demonstrate that ALI-EBAD out performs CA-TMES-Search and CA-TMES-Quick task schedulers in terms of energy-efficiency.

Highlights

  • H EALTHCARE is one of the fastest growing industries with an enormous potential for enhancement from the employment of technologies such as the Internet-of-Things (IoT), cloud computing, and mobile devices

  • To the best of our knowledge, no prior work has been done that focuses on energy-aware scheduling of tasks with conditional constraints represented by Conditional Task Graph (CTG) on Voltage Frequency Island (VFI)-NoC-HMPSoC deploying re-timing combined with Dynamic Voltage and Frequency Scaling (DVFS) technique

  • The computational complexity of real-time multimedia applications is rapidly proliferating, Voltage Frequency Islands (VFI) based Multiprocessor System-on-Chip (MPSoC) architectures are adopted for higher performance and effective energy management

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Summary

INTRODUCTION

H EALTHCARE is one of the fastest growing industries with an enormous potential for enhancement from the employment of technologies such as the Internet-of-Things (IoT), cloud computing, and mobile devices. In real-time streaming applications, tasks are dependent on each other the slack within the processors of the MPSoC architecture is not efficiently utilized. Xilinx Zynq R UltraScale+TM MPSoCs and Tilera TILE-Gx72TM are few of the well-known high performance computing architectures used in digital systems for healthcare Examples of the medical application of multiprocessor systems include a real-time video-streaming system [10] developed to remotely monitor the human ultrasound examinations. We investigate an energy-efficient static scheduling deploying VFI-NoC-HMPSoC for a set of periodic tasks with conditional precedence constraints representing a real-time periodic streaming application. Our contributions and innovations include as follows: 1) We develop a novel energy-aware static scheduler considering tasks with conditional constraints using VFINoC-HMPSoC computing architecture deploying a retiming technique integrated with DVFS for the IoT based real-time streaming applications in healthcare.

LITERATURE REVIEW
Application Model
System Model
Offline Schedule
SCHEDULE-AWARE PIPELINING
Experimental Setup
Results and Discussion
Findings
CONCLUSION
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