Distributed Systems - The Next Level
Prof. Schahram Dustdar, TU Wien, Austria
As humans, things, software and AI continue to become the entangled fabric of distributed systems, systems engineers and researchers are facing novel challenges. In this talk, we analyze the role of Edge, Cloud, and Human-based Computing
as well as AI in the co-evolution of distributed systems for the new decade. We identify challenges and discuss a roadmap that these new distributed systems have to address. We take a closer look at how a cyber-physical fabric will
be complemented by AI operationalization to enable seamless end-to-end distributed systems.
Schahram Dustdar is Full Professor of Computer Science heading the Research Division of Distributed Systems at the TU Wien, Austria. He holds several honorary positions: University of California (USC) Los Angeles; Monash University in
Melbourne, Shanghai University, Macquarie University in Sydney, and University of Groningen (RuG), The Netherlands (2004-2010). From Dec 2016 until Jan 2017 he was a Visiting Professor at the University of Sevilla, Spain and from January
until June 2017 he was a Visiting Professor at UC Berkeley, USA.
From 1999 - 2007 he worked as the co-founder and chief scientist of Caramba Labs Software AG in Vienna (acquired by Engineering NetWorld AG), a venture capital
co-funded software company focused on software for collaborative processes in teams. Caramba Labs was nominated for several (international and national) awards: World Technology Award in the category of Software (2001); Top-Startup
companies in Austria (Cap Gemini Ernst & Young) (2002); MERCUR Innovation award of the Austrian Chamber of Commerece (2002).
He is founding co-Editor-in-Chief of the new ACM Transactions on Internet of Things (ACM TIoT)
as well as Editor-in-Chief of Computing (Springer). He is an Associate Editor of IEEE Transactions on Services Computing, IEEE Transactions on Cloud Computing, ACM Transactions on the Web, and ACM Transactions on Internet Technology,
as well as on the editorial board of IEEE Internet Computing and IEEE Computer. Dustdar is recipient of the ACM Distinguished Scientist award (2009), the IBM Faculty Award (2012), an elected member of the Academia Europaea: The Academy
of Europe, where he is chairman of the Informatics Section, as well as an IEEE Fellow (2016).
Challenges and Opportunities for Composable AI-Integrated Applications at the Digital Continuum
Dr. İLKAY ALTINTAŞ, San Diego Supercomputer Center, USA
Cyberinfrastructure is everywhere in diverse forms. From IoT to extreme scale computing, data and computing has never been as distributed with potential for real-time integration via fast networking and container management. The
of new processors over the last decade including GPUs, FPGAs, and edge accelerators opened the way to a diverse set of applications using machine learning on top of distributed nontraditional hardware. The common theme to these
mostly composed of artificial intelligence (AI) workloads, is their need to run in specialized environments for reasons such as on demand or 24x7 nature of the tasks they are performing, and difficulties regarding their portability,
latency, privacy and performance optimization. Moreover, in many data-driven scientific applications including drug discovery, high-energy physics, material design and disaster simulations, there is a need for integration of these
AI-workloads with traditional high-throughput computing (HTC) or high-performance computing (HPC) tasks for AI-integrated science. Although some key middleware technologies enabled demonstration of standalone applications, these applications
require expertise from a large group of people in very specialized settings. There are still many challenges for streamlined, scalable, repeatable, responsible and explainable integration of AI in applications. Key opportunities for
further innovations include intelligent systems and automated workflow management software that can compose and steer dynamic applications that can adapt to changing conditions in a data-driven fashion while integrating many tools
to explore, analyze and utilize data. This talk will discuss example AI-integrated applications, describe some of the new systems that enabled these applications, and overview our recent research to enable composable applications including
an application development methodology, intelligent middleware and workflow composition.
Dr. Ilkay Altintas is the Chief Data Science Officer at the San Diego Supercomputer Center (SDSC), UC San Diego, where she is also the Founder and Director for the Workflows for Data Science Center of Excellence and a Fellow of the Halicioglu
Data Science Institute (HDSI). In her various roles and projects, she leads collaborative multi-disciplinary teams with a research objective to deliver impactful results through making computational data science work more reusable,
programmable, scalable and reproducible. Since joining SDSC in 2001, she has been a principal investigator and a technical leader in a wide range of cross-disciplinary projects. Her work has been applied to many scientific and societal
domains including bioinformatics, geoinformatics, high-energy physics, multi-scale biomedical science, smart cities, and smart manufacturing. She is a co-initiator of the popular open-source Kepler Scientific Workflow System, and the
co-author of publications related to computational data science at the intersection of workflows, provenance, distributed computing, big data, reproducibility, and software modeling in many different application areas. She is also
a popular MOOC instructor in the field of “big” data science, and reached out to hundreds of thousands of learners across any populated continent. Her Ph.D. degree is from the University of Amsterdam in the Netherlands with an emphasis
on provenance of workflow-driven collaborative science. She is an associate research scientist at UC San Diego. Among the awards she has received are the 2015 IEEE TCSC Award for Excellence in Scalable Computing for Early Career Researchers
and the 2017 ACM SIGHPC Emerging Woman Leader in Technical Computing Award.