Distinguished CS Colloquium Talk by C. Mohan on Oct 18th
Title: Systems Design Dilemmas: Simplicity Versus Complexity
Speaker: Dr. C. Mohan
Distinguished Professor of Science (Hong Kong Baptist University, China)
Distinguished Visiting Professor (Tsinghua University, China)
Retired IBM Fellow (IBM Research, USA)
When: Wednesday, October 18, 2023 @ 11am
Where: Center for Computing and Data Sciences (CCDS), 17th floor
Abstract
Based on my 4 decades long involvement in and exposure to numerous database systems, in this talk I will discuss how various factors led multiple systems to be evolved in ways that made them become more complex in terms of their design as well as their usability aspects. While simplicity of design and architecture might be a highly desirable objective, there will invariably be conflicting requirements that lead to complexity creeping in, at least with respect to the internals of such systems. Examples of such requirements relate to the cloud environment, performance, availability, heterogeneity in terms of supported hardware, operating systems and programming language environments, accommodation of multiple workload types, extensibility, etc. It is also the case that aiming for simplicity in one aspect of system design might cause complexity to be introduced in other areas. A case in point is the desire for the near elimination of the need for DBAs and tuning knobs in the cloud environment which makes the internals of such systems become much more complex so that they could dynamically detect and react to different workload types that such systems might be used for. While KISS (Keep It Simple, Stupid) might be a desirable design principle, following it mindlessly might result in the kiss of death with respect to performance and reliability!
Bio
Dr. C. Mohan is currently a Distinguished Professor of Science at Hong Kong Baptist University, a Distinguished Visiting Professor at Tsinghua University in China, and a member of the inaugural Board of Governors of Digital University Kerala. He retired in June 2020 from being an IBM Fellow at the IBM Almaden Research Center in Silicon Valley. He was an IBM researcher for 38.5 years in the database, blockchain, AI and related areas, impacting numerous IBM and non-IBM products, the research and academic communities, and standards, especially with his invention of the well-known ARIES family of database locking and recovery algorithms, and the Presumed Abort distributed commit protocol. This IBM (1997-2020), ACM (2002-) and IEEE (2002-) Fellow has also served as the IBM India Chief Scientist (2006-2009). In addition to receiving the ACM SIGMOD Edgar F. Codd Innovations Award (1996), the VLDB 10 Year Best Paper Award (1999) and numerous IBM awards, Mohan was elected to the United States and Indian National Academies of Engineering (2009), and named an IBM Master Inventor (1997). This Distinguished Alumnus of IIT Madras (1977) received his PhD at the University of Texas at Austin (1981). He is an inventor of 50 patents. During the last many years, he focused on Blockchain, AI, Big Data and Cloud technologies (https://bit.ly/sigBcP, https://bit.ly/CMoTalks). Since 2017, he has been an evangelist of permissioned blockchains and the myth buster of permissionless blockchains. During 1H2021, Mohan was the Shaw Visiting Professor at the National University of Singapore. In 2019, he became an Honorary Advisor to the Tamil Nadu e-Governance Agency. In 2020, he joined the Advisory Board of the Kerala Blockchain Academy. Since 2016, Mohan has been a Distinguished Visiting Professor of China’s prestigious Tsinghua University. In 2023, he was named Distinguished Professor of Science of Hong Kong Baptist University. In 2021, he was inducted as a member of the inaugural Board of Governors of the new Indian university Digital University Kerala. Mohan has served on the advisory board of IEEE Spectrum, and on numerous conference and journal boards. During most of 2022, he was a consultant at Google with the title of Visiting Researcher. He has also been a Consultant to the Microsoft Data Team in 2020.