Selim Kalayci

Florida International University School of Computing and Information Sciences

Lecture Information:
  • April 24, 2024
  • 12:57 PM
  • ECS: 349

Speaker Bio

Selim Kalayci is a Ph.D. candidate in Computer Science at Florida International University advised by Dr. S. Masoud Sadjadi. Selim received his Bachelor’s degree in Computer Engineering in 2002 from Fatih University, Istanbul, Turkey. He received his Master of Science in Computer Science degree in 2006 from FIU. His research interests are in High-Performance Computing, Distributed Systems, and Big Data Analysis. Selim was awarded National Science Foundation’s Partnerships for International Research and Education (PIRE) grant and spent 10 weeks at IBM India Research Lab at New Delhi, India. He was also awarded NSF Extreme Science and Engineering Discovery Environment(XSEDE) educational resource allocation for 3 consecutive years, and several travel awards. Selim held the dual position of Instructor in Computing and Director of High-Performance Computing Center at East Tennessee State University (ETSU) between 2010 and 2014.


Scientific exploration demands heavy usage of computational resources for large-scale and deep analysis in many different fields. The complexity or the sheer scale of the computational studies can sometimes be encapsulated in the form of a workflow that is made up of numerous dependent components. Due to its decomposable and parallelizable nature, different components of a scientific workflow may be mapped over a distributed resource infrastructure to reduce time to results. However, the resource infrastructure may be heterogeneous, dynamic, and under diverse administrative control.
Workflow management tools are utilized to help manage and deal with various aspects in the lifecycle of such complex applications. One particular and fundamental aspect that has to be dealt with as smooth and efficient as possible is the run-time coordination of workflow activities (i.e. workflow orchestration). Our efforts in this study are focused on improving the workflow orchestration process in such dynamic and distributed resource environments. We tackle three main aspects of this process and provide contributions in each of them.
Our first contribution involves increasing the scalability and site autonomy in situations where the mapped components of a workflow span across several heterogeneous administrative domains. We devise and implement a generic decentralization framework for orchestration of workflows under such conditions. Our second contribution is involved with addressing the issues that arise due to the dynamic nature of such environments. We provide generic adaptation mechanisms that are highly transparent and also substantially less intrusive with respect to the rest of the workflow in execution. Our third contribution is to improve the efficiency of orchestration of large-scale parameter-sweep workflows. By exploiting their specific characteristics, we provide generic optimization patterns that are applicable to most instances of such workflows. We also discuss implementation issues and details that arise as we provide our contributions in each situation.