E2C: A Visual Simulator to Reinforce Education of Heterogeneous Computing Systems


연구 분야: Networking



학회: 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)


초록

Heterogeneity has been an indispensable aspect of distributed computing throughout the history of these systems. ln particular, with the increasing popularity of accelerator technologies (eg., GPUs and TPUs) and the emergence of domain-specific computing via ASlCs and FPGA, the matter of heterogeneity and understanding its ramifications on the system performance has become more critical than ever before. However, it is challenging to effectively educate students about the potential impacts of heterogeneity on: (a) the performance of distributed systems; and (b) the logic of resource allocation methods to efficiently utilize the resources. Making use of the real infrastructure (such as those offered by the public cloud providers) for benchmarking the performance of heterogeneous machines, for different applications, with respect to different obiectives, and under various workload intensities is cost- and time-prohibitive. Moreover, not all students (globally and nationally) have access or can afford such real infrastructure. To reinforce the quality of learning about various dimensions of heterogeneity, and to decrease the widening gap in education, we develop an open-source simulation tool, called E2C, that can help students researchers and practitioners to study any type of heterogeneous (or homogeneous) computing system and measure its performance under various system configurations. To make the learning curve shallow, E2C is equipped with an intuitive graphical user interface (GU1) that enables its users to easily examine system-level solutions (scheduling, load balancing, scalability, etc.) in a controlled environment within a short time and at no cost. In particular, E2C is a discrete event simulator that offers the following features: (i) simulating a heterogeneous computing system; (ii) implementing a newly developed scheduling method and plugging it into the system, (iii) measuring energy consumption and other output-related metrics; and (iv) powerful visual... Show More


Author Profile
Ali Mokhtari

High Performance Cloud Computing (HPCC) Laboratory School of Computing and Informatics University of Louisiana at Lafayette LA USA

Andorra
Author Profile
Drake Rawls

High Performance Cloud Computing (HPCC) Laboratory School of Computing and Informatics University of Louisiana at Lafayette LA USA

Andorra
Author Profile
Tony Huynh

High Performance Cloud Computing (HPCC) Laboratory School of Computing and Informatics University of Louisiana at Lafayette LA USA

Andorra

📄 논문 정보

발행 연도 2023년
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출판 국가 Andorra
사이트 IEEE
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