With the increasing popularity of accelerator technologies (e.g., GPUs and TPUs) and the emergence of domain-specific computing via ASICs and FPGA, the matter of heterogeneity and understanding its ramifications on the performance has become more critical than ever before. However, it is challenging to effectively educate students about the potential impacts of heterogeneity on the performance of distributed systems; and on the logic of resource allocation methods to efficiently utilize the resources. Making use of the real infrastructure for benchmarking the performance of heterogeneous machines, for different applications, with respect to different objectives, and under various workload intensities is cost- and time-prohibitive. 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 to study any type of heterogeneous (or homogeneous) computing system and measure its performance under various configurations. E2C is equipped with an intuitive graphical user interface (GUI) that enables its users to easily examine system-level solutions (scheduling, load balancing, scalability, etc.) in a controlled environment within a short time. 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 aspects to ease the learning curve for students. We used E2C as an assignment in the Distributed and Cloud Computing course. Our anonymous survey study indicates that students rated E2C with the score of 8.7 out of 10 for its usefulness in understanding the concepts of scheduling in heterogeneous computing.

翻译：随着加速器技术（如GPU和TPU）的日益普及，以及基于ASIC和FPGA的领域专用计算的出现，异构性及其对性能影响的理解变得比以往任何时候都更加关键。然而，有效教授学生异构性对分布式系统性能的潜在影响，以及如何通过资源分配逻辑高效利用资源，仍面临巨大挑战。使用真实基础设施对不同应用、不同目标及不同工作负载强度下的异构机器进行性能基准测试，成本高昂且耗时。为提升异构性多维度学习质量，并弥合日益扩大的教育差距，我们开发了一款名为E2C的开源仿真工具，可帮助学生和研究人员研究任意类型异构（或同构）计算系统，并测量其在多种配置下的性能。E2C配备直观的图形用户界面（GUI），使用户能够在受控环境中快速检验系统级解决方案（如调度、负载均衡、可扩展性等）。作为离散事件仿真器，E2C具备以下功能：（i）仿真异构计算系统；（ii）实现新开发的调度方法并将其接入系统；（iii）测量能耗及其他输出相关指标；（iv）通过强大的可视化功能降低学生学习曲线。我们将E2C作为分布式与云计算课程的作业工具。匿名调查表明，学生对E2C在理解异构计算调度概念方面的实用性评分为8.7分（满分10分）。