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Cloud-based Instruction Model for Electrical Engineering Courses: A Rapid Response to Enable Fully Online Course Delivery

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2021 ASEE Virtual Annual Conference Content Access


Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Electrical and Computer Division Technical Session 2

Tagged Division

Electrical and Computer

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Paper Authors


Praveen Meduri California State University, Sacramento

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Dr. Praveen Meduri is an Assistant Professor of Electrical and Electronic Engineering at Sacramento State University. He is also a Technical Liaison to Cadence Design Systems. He received his PhD from Old Dominion University, VA, M.S. from Southern Illinois University at Carbondale and bachelors from JNT University, India.

His research interests include Embedded Systems, Smart Cities and VLSI Design and has multiple peer reviewed publications in these fields.

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Lawrence David Landis Intel Programmable Solutions Group

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Senior Manager University Academic Outreach, Intel Programmable Solutions Group

Lawrence has 35 years’ experience in a wide variety of functions in the electronics industry including marketing, sales and project management for numerous ASIC and FPGA products. Larry teaches part time digital electronics and ASIC design at Santa Clara University and UC Berkeley.

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Perry L. Heedley California State University, Sacramento

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PERRY L. HEEDLEY earned his Ph.D. and M.S. degrees from Auburn University and his B.E.E. from the Georgia Institute of Technology. He has over 20 years of industrial experience designing analog and mixed-signal integrated circuits for companies including Intel, Sacramento (formerly Level One Communications), Crystal Semiconductor, and Harris Semiconductor. In 2003 he joined the Department of Electrical and Electronic Engineering at California State University, Sacramento, while continuing to consult with industry on a part-time basis. In 2005 he co-founded the Mixed-Signal Design Laboratory (MSDL) at Sacramento State with Professor Thomas W Matthews. His interests include high-speed data converters, low-jitter clock generation and distribution, high-speed serial data communications, switched-capacitor circuits for analog signal-processing, low-voltage analog design in deep sub-micron CMOS processes, and mixed-signal circuits for biomedical applications.

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Tyler Sheaves Intel Corporation

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Tyler Sheaves is a Ph.D. student at University of California, Davis and a graduate technical intern in the academic outreach division of Intel's Programmable Solutions Group. In his position at Intel, he develops virtual FPGA-based learning applications and curriculum. In academia, his primary areas of research are hardware security, intellectual property protection, and digital integrated circuit design and verification.

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In this paper, we present four techniques that have been successfully adopted for delivering lab based electrical and computer engineering courses, in a fully-online format. This experiment is a rapid response to the exigent circumstances necessitating a sudden transition to online instruction format.

Firstly, we present the use of public cloud based servers for hosting custom IC design software. This software (for example, Cadence Virtuoso suite) is essential to impart important learning outcomes and to ensure curricular currency in electrical and computer engineering programs.

This approach has relevance that extends beyond the upper division class (Digital VLSI Design) in which it is implemented. This could be a model for enabling fully online course delivery in engineering; particularly in courses that have significant compute-intensive simulation needs.

We also discuss the specifications and compute resource optimizations of cloud server instances in relation to the class size. The long-term viability of this cloud-based model for online instruction is considered based on the user feedback, added value and cost metrics.

Secondly, we present a cloud-based computational platform (called DevCloud from Intel), for use in heterogeneous computing courses. Knowledge of heterogeneous computing systems has been identified by IEEE Computer Society and ACM as a core learning outcome in computer engineering curricula [1]. The paradigm of heterogeneous computing entails a judicious combination of CPUs and co-processor accelerators like FPGAs or GPUs. This significantly accelerates arithmetic intensive workloads (like Artificial Intelligence projects), by leveraging the power of data-level and task-level parallelism.

Thirdly, we also present a couple of tried and tested approaches for delivering hardware based electrical and computer engineering courses in online format. These FPGA lab related approaches have been successfully implemented in courses at different universities worldwide.

Even as different universities plan a phased return to in-person instruction, we feel confident in asserting that these approaches will have an enduring positive role in creating a robust educational system that can disseminate hands-on electrical engineering skills, without regard for geographical limitations.

Meduri, P., & Landis, L. D., & Heedley, P. L., & Sheaves, T. (2021, July), Cloud-based Instruction Model for Electrical Engineering Courses: A Rapid Response to Enable Fully Online Course Delivery Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36799

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