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Space Computing using COTS Heterogeneous Platforms

Fulltext:


Publication Type:

Doctoral Thesis

Publisher:

Mälardalen University


Abstract

Space computing is growing due to the technological advances of high performance commercial off-the-shelf (COTS) computing platforms. Space offers a complex and challenging environment, with size, weight, power, and timing constraints, communication limitations, and radiation effects.The research presented in this thesis aims at investigating and supporting intelligent on-board data processing using COTS heterogeneous computing platforms in space systems. We investigate platforms with at least one Central Processing Unit (CPU) and one Graphics Processing Unit (GPU) on the same chip. The main goal of the research presented in this thesis is twofold. First, investigate the heterogeneous computing platforms to propose a solution to tackle the above-mentioned challenges in space systems. Second, to complement the proposed solution with novel scheduling techniques for real-time applications that run on COTS heterogeneous platforms in harsh environments like space.The proposed solutions are based on the system model that considers the use of alternative executions of parallel segments of tasks. Although offloading a parallel segment to a parallel computation unit (such as GPU) improves the best-case execution times of most applications, it can increase the response times of tasks in some applications due to the overuse of GPU. Hence, using the proposed task model can be a key to decreasing the response times of tasks and improving schedulability of the system. The server-based scheduling techniques support the proposed task model by guaranteeing the execution slot for parallel segments on CPU(s). Our experimental evaluation shows that the proposed allocation can increase the number of schedulable task sets of the real-time systems up to 90% compared to the static allocation of applications.We also present a dynamic allocation method using server-based scheduling with the proposed task model that can improve the schedulability up to 16%. Finally, the thesis presents a simulation tool that supports designers in choosing heterogeneous processing units using the proposed task model while considering the different levels of radiation tolerance to the processing units.

Bibtex

@phdthesis{Tsog6325,
author = {Nandinbaatar Tsog},
title = {Space Computing using COTS Heterogeneous Platforms},
isbn = {978-91-7485-528-9},
month = {November},
year = {2021},
school = {M{\"a}lardalen University},
url = {http://www.es.mdu.se/publications/6325-}
}