A serious challenge of nowadays Software Eco-System

Prof. Guang R. Gao

9:30am, Nov 11, room 3-404

Bio:

Professor Gao’s research has focused in high-performance computer system, specifically in compiler optimization techniques, instruction scheduling, software, and dataflow programming model.

He is the Endowed Distinguished Professor at the Department of Electrical & Computer Engineering in University of Delaware, ACM Fellow and IEEE Fellow. He won the CCF overseas outstanding contribution award in 2013.

Abstract:

Nowadays High-Performance Computing system and Big Data system are diverges from system architecture to software design, which leads to different eco-system. There needs a unified model to combine Big Data analytics and High-Performance Computing. This can provide a way to deal with big volume data while guarantee high computing performance.

My proposal to achieve it is the dataflow model. Dataflow paradigm “is the most suitable computing paradigm for Big Data”. It offers “superior speedup, power savings and size reduction”. Dataflow model has many advantages over other models: The argument –Fetching Dataflow Model encouraging a smooth integration of hybrid control-flow and dataflow, location consistency breaks the barrier on memory and spontaneous dataflow model permits a smooth handling on nondetermism introduced by external events. By using our new compute Engine—HAMR, requirements from both Big Data and High-Performance can be satisfied.