Description: The early decades of research on computer system design and operation have been marked by an utmost emphasis on performance. More recently, we have been witnessing an increasing interest in sustainable computing research and practice, where power, energy, and thermal management are considered as first-class system design and operation objectives. This paradigm shift is rooted in multiple developments: with the proliferation of battery-operated devices such as smartphones, wearables, sensors, and Internet of Things (IoT), Power/Energy has been recognized as a precious system resource that must be managed dynamically and optimally. In addition, power and thermal management is now considered a must for high-end systems such as servers and Internet Data Centers directly connected to the power grid. Internet Data Centers, such as those operated by the industry giants Google, Facebook, and Amazon, are the backbone of our current IT infrastructure. Google alone is running more than 2.5 million servers consuming more than 500 million watts.
This seminar class is primarily about System-level Software techniques that help to improve power, energy, and heat efficiency; and the trade-offs between those techniques and various system performance metrics. We will review the existing sustainable resource management techniques for cloud computing, edge/fog computing, high-performance computing, wearable computing, Internet-of-Things (IoT), and cyber-physical systems. Application-, operating system- and network-level adaptations will be of particular interest. In addition, there is a growing interaction between machine learning and sustainable computing : On the one hand, we will discuss machine learning (ML) techniques that are increasingly employed to achieve sustainability in computing. On the other hand, regulating the energy consumption of widely used ML frameworks such as Convolutional Neural Networks and Federated Learning is attracting increasing interest. Finally, the interplay between sustainable computing and other features such as security, reliability, and usability will be considered.
Another discussion topic of the course will be the emerging Computational Sustainability, which is an interdisciplinary field that develops computational methods using results from various areas (Computer Science, Data Science, Machine Learning, Economics, Applied Math, Operations Research) for balancing environmental, economic, and societal needs for general sustainable development. Computational Sustainability typically involves conducting on and synthesizing research from several fields such as Internet of Things (IoT), optimization, remote sensing, machine learning and decision making under uncertainty, for sustainable development goals such as Fighting Climate Change, Environmental Protection, and Supporting Good Health and Well-Being. A concise introduction to the field can be found in the September 2019 Communication of the ACM article Computational Sustainability: Computing for a Better World and a Sustainable Future.
During the term, we will present, discuss and evaluate various papers in the areas of Sustainable Computing and Computational Sustainability. Through a comprehensive term project, the students will be able to focus on a well-defined subarea and perform a preliminary research. There will be no exams. The course is particularly suitable for PhD students and advanced MS students interested in hot research problems. The course will also satisfy the breadth requirement of the MS in CS program for the Systems and Networks area.
The course is open to both Ph.D. students and advanced MS Students. Students of a graduate program offered by a department other than the Computer Science department should get the approval of the instructor before enrolling.
Readings: There is no required textbook. Most of the course material will be provided by the instructor and through recent research articles.
Grading:
Course Format and Presentations: During the first part of the course, the instructor will present the fundamentals of sustainable computing and computational sustainability, as well as the main research problems of the area. In the second part, the students will present articles from recent conference/workshop proceedings and journals. A list of suggested papers will be provided, however, the student suggestions are welcome. The (in-class) presentation will include a critical evaluation and discussion of the paper. The students will be required to read, and submit a brief summary/evaluation of the papers presented in class.
Term Project: Each student is expected to complete a term project and submit a research paper/report by the end of the term. Again, a list of potential projects will be provided; but students may define their own project as long as the project has sufficient scope/complexity and the instructor's approval is obtained. A term project may be in any of the following forms:
All students must abide by the GMU Honor Code and CS Department's Honor Code and Academic Integrity Policies during the semester.
Class Home Page: Throughout the term, all course material (slides, handouts, readings, etc.) will be available on the GMU Blackboard system.
Disability Statement: If you have a learning or physical difference that may affect your academic work, you will need to furnish appropriate documentation to GMU Disability Resource Center. If you qualify for accommodation, the DRC staff will give you a form detailing appropriate accommodations for your instructor. If you have such a condition, you must talk to the instructor during the first week of the term about the issue.