Yogish Sabharwal

I completed my Ph.D. from the Indian Institute of Technology, Delhi in 2007. My supervisors were Prof. Sandeep Sen and Prof. Amit Kumar. My thesis is in approximation algorithms for proximity and clustering problems.

I currently manage the HPC Team at IBM Research India, with a primary focus on performance optimization and tuning of a wide variety of benchmarks and scientific applications such as the HPC Challenge benchmarks, numerical linear algebra methods, environmental science applications, cognitive computing frameworks, deep learning and financial applications on massively parallel multicore architectures such as Blue Gene Supercomputers, Cell processor and Power processor systems. The optimizations include designing new algorithms, data structures and other intricate techniques for distributed memory and multicore architectures. I am an adjunct faculty @IIT-Delhi.

Courses taught @IIT-Delhi

2013-14 CSV880: Special Topics in Parallel Computing

2014-15 CSV880: Special Topics in Parallel Computing

2016-17 COV880: Parallel Programming with OpenMP

2017-18 COV880: Parallel Programming in Deep Learning

2018-19 COV880: Distributed Memory Parallel Programming with MPI

2020-21 COL106: Data Structures and Algorithms (taught jointly with Rahul and Riju)

MOOCs @NPTEL

2017-18 Parallel Programming with OpenMP

2018-19 Parallel Programming with OpenMP

2019-20 Parallel Programming with OpenMP

Ph.D. Students

Sonika Arora