Short bio
Postdoctoral Research
As of Jan 2017, I am a Postdoc Fellow @ University of Toronto where I conduct research on accelerating deep learning applications and automatic tuning.
PhD research
From January 2013, he was a Ph.D. student and researcher in DEIB, under the advisement of Cristina Silvano and Gianluca Palermo. He defended his thesis with the grade summa con laude in December 2016 and his Ph.D. thesis has been selected as the winner of the 2016 IEEE Computer Society Italy Section Chapter 2016 Ph.D. Thesis Award.
Short Summary of the PhD research titled Compiler Autotuning Using Machine Learning Techniques:
The diversity of today’s architectures have forced programmers to spend additional effort to port and tune their application code across different platforms. Compilers within this process need additional tuning which is a hard task itself. Recent compilers offer a vast number of multilayered optimizations, capable of targeting different code segments of an application. Choosing among these optimizations can significantly impact the performance of the code being optimized. The selection of the right set of compiler optimizations for a particular code segment is a very hard problem, but finding the best ordering of these optimizations adds further complexity. In fact, finding the best ordering is a long-standing problem in compilation research called the phase-ordering problem. The traditional approach of constructing compiler heuristics to solve this problem simply can not cope with the enormous complexity of choosing the right ordering of optimizations for every code segment in an application.
This thesis tackles the difficult problem of determining the best set of compiler optimizations for a range of platforms. It addresses both of the main problems, namely, the Selection and the Phase-ordering problem using innovative machine learning based solutions that exploit prior knowledge. This knowledge is used to build models that predict the right optimizations for unseen programs. I hope that it will be useful for a wide range of readers, including computer architects, compiler developers, researchers.
PhD defense session video: https://www.youtube.com/watch?v=KwxvldwKz5I
Research visits abroad
(September 2014- March 2015); he was awarded HiPEAC short-term Ph.D. visiting grant for his proposal and have been working under the supervision of John Cavazos at University of Delaware, applying machine learning to hard problems such as compiler auto-tuning and high-performance computing.