SEDec 31, 2016

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

arXiv:1701.00117v12 citations
Originality Synthesis-oriented
AI Analysis

This work addresses energy-efficient software design for embedded systems architects, but it is incremental as it builds on existing component-based approaches.

The paper tackled the problem of ignoring physical properties like power consumption and execution time in software design for embedded systems, by profiling a component software on heterogeneous computing units (CPU, GPU, FPGA) of a tracked robot, resulting in quantified data for power consumption and execution time.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes