Document Type

Conference Proceeding



Publication Date



Institute of Electrical and Electronics Engineers

Source Publication

2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

Source ISSN



Multicore processors have become the standard in modern computing platforms. Such complex hardware enables faster execution of the programs it runs, but this is only true if its programmer has the knowledge and ability to make it so. Thus, there is a great need to prepare computing students by establishing robust educational tools. Existing tools often include abstract learning environments such as a virtual machine. While such platforms are widely available and convenient, they are unable to expose students to concurrency on real hardware.This paper presents multicore Embedded Xinu, an educational operating system used to teach concurrency concepts at the university level. The latest port of Embedded Xinu to the four-core, ARM-based Raspberry Pi 3 B+ enabled an operating systems curriculum in which students build their own concurrency-oriented kernel and execute it on a real machine. Assignments that have been run in the course include concepts of synchronization, scheduling, and memory allocation on a multicore platform. Upon completing the course, students are capable of solving problems commonly found in the field of parallel computing.


Accepted version. Published as part of the proceedings of the conference, IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (May 18-22, 2020). DOI. © 2020 The Institute of Electrical and Electronics Engineers. Used with permission.

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