An initial performance review of software components for a heterogeneous computing platform

TL;DR

This paper evaluates the power consumption and execution time of software components on heterogeneous computing units like CPU, GPU, and FPGA, aiding energy-efficient embedded system design.

Contribution

It provides initial performance profiling data for software components on heterogeneous platforms, highlighting their physical footprint and aiding energy-aware design decisions.

Findings

Power consumption varies across CPU, GPU, FPGA

Execution time differs significantly among components

Profiles support energy-efficient software architecture

Abstract

The design of embedded systems is a complex activity that involves a lot of decisions. With high performance demands of present day usage scenarios and software, they often involve energy hungry state-of-the-art computing units. While focusing on power consumption of computing units, the physical properties of software are often ignored. Recently, there has been a growing interest to quantify and model the physical footprint of software (e.g. consumed power, generated heat, execution time, etc.), and a component based approach facilitates methods for describing such properties. Based on these, software architects can make energy-efficient software design solutions. This paper presents power consumption and execution time profiling of a component software that can be allocated on heterogeneous computing units (CPU, GPU, FPGA) of a tracked robot.