Emergent Mind

Abstract

Non-uniform performance and power consumption across the processing elements (PEs) of heterogeneous SoCs increase the computation complexity of the task scheduling problem compared to homogeneous architectures. Latency of a software-based scheduler with the increased heterogeneity level in terms of number and types of PEs creates the necessity of deploying a scheduler as an overlay processor in hardware to be able to make scheduling decisions rapidly and enable deployment of real-life applications on heterogeneous SoCs. In this study we present the design trade-offs involved for implementing and deploying the runtime variant of the heterogeneous earliest finish time algorithm (HEFTRT) on the FPGA. We conduct performance evaluations on a SoC configuration emulated over the Xilinx Zynq ZCU102 platform. In a runtime environment we demonstrate hardware-based HEFTRT's ability to make scheduling decisions with 9.144 ns latency on average, process 26.7% more tasks per second compared to its software counterpart, and reduce the scheduling latency by up to a factor of 183x based on workloads composed of mixture of dynamically arriving real-life signal processing applications.

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