Photo gallery of on-going activities.
Chandrasekaran is an Assistant Professor with the Dept. of CIS, Affiliated with the Center for Bioinformatics and Computational Biology (CBCB) and holds an Adjunct position with the Department of Computer Science at the University of Houston. Prior to joinging UDEL, she was a postdoctoral researcher at the Dept. of Computer Science at the University of Houston, Texas, advised by Prof. Barbara Chapman. Her Ph.D. is on Tools and Algorithms for High-Level Algorithm Mapping to FPGAs, School of Computer Science and Engineering, Nanyang Technological University, 2012. For more, see Curriculum Vitae.
Go to Computational Research and Programming Laboratory (CRPL). Thank you to our collaborators: National Science Foundation (NSF), DOE ECP SOLLVE, National Center for Atmospheric Research (NCAR), NVIDIA, Nemours Alfred duPont Hospital for Children
Chandrasekaran was a recipient of the 2016 IEEE-CS TCHPC Award for Excellence for Early Career Researchers in High Performance Computing and received her award at (SC16). She also received the SPEC HPG (Standard Performance Evaluation Corporation, High Performance Group) Technical Leadership Award in Jan 2016. SPEC also recognized her as one of the SPEC project leaders of the High Performance Group (HPG) benchmark suite in 2014.
Chandrasekaran and Guido Juckeland published an edited textbook on OpenACC for Programmers: Concepts and Strategies, November 2017.
Vertically Integarted Project (VIP) undergraduate students won the Research Poster prize for accelerating the prediction of chemical shift of protein structures using state-of-the-art NVIDIA V100 GPUs at the annual VIP mid-atlantic poster competition held at UD. The acceleration brought down the time taken from 10+ hours to 2 minutes on a dataset of approximately 11K atoms. Stay tuned for more details.
Sunita Chandrasekaran and her doctoral student Robert Searles have accelerated a nuclear reactor-based miniapp, Minisweep using OpenACC on GPUs. The paper is accepted to be published in PASC 2018. For more see UDaily and OLCF news.
Sunita Chandrasekaran and Guido Juckeland published an Edited book on OpenACC for Programmers: Concepts and Strategies, November 2017. The book provides a comprehensive and practical overview of OpenACC for massively parallel programming. Related articles: Eurekalert and insideHPC.
In this video from SC17, Sunita Chandrasekaran from OpenACC.org and Stan Posey from NVIDIA describe how OpenACC eases GPU programming for HPC. More
In Summer 2016, scientists from NASA, NCI, BNL and 3 UDEL teams gathered at the University of Delaware for a GPU Programming Hackathon. Watch the recap video shared by NVIDIA news center and photos. Similarly in summer 2017, a Brookathon was held at Brookhaven National Lab in collaboration with Meifeng Lin, a CSI computational scientist, Fernanda Foertter, a HPC user support specialist and programmer and several others. The hackathon stories and training experiences were captured in this paper presented at the 2017 EduHPC workshop co-located with SC17.
Accurate prediction of the chemical shift of a protein is essential in certain areas of molecular dyanamics research such as drug discovery. This is a compute-intensive problem. Currently, there is not an available application that can predict chemical shift of large protein structures in a realistic amount of time. We took a chemical shift prediction application called PPM_One, and accelerated it using OpenACC to reduce the time taken from 10+ hours on a single core to 2 minutes on NVIDIA V100 GPUs.
Denovo is a production code for nuclear reactor neutronics modeling and is in use by a current DOE INCITE project to model the ITER fusion reactor. Our project investigates the sweep kernel within Denovo that counts for approximately 80-99% of Denovo’s overall computational expenses. We use OpenACC, a high-level, directive-based programming model running on NVIDIA’s next-generation Volta GPU for this work and our preliminary shows promising speedup comparable to CUDA.
This project explores building a fast whole genome sequence alignment algorithm for both long and short reads. The tool is being evaluated with Saccharomyces Genome Database (SGD) (yeast) and human genome sequences. Stay tuned to learn more.
Sunita’s group builds validation and verification (V&V) testsuites for OpenMP directive-based parallel programming models and focusses on the offloading features. Work on OpenMP testsuite is part of the Exascale Computing Project (ECP) SOLLVE project. The testsuite project is funded by Oak Ridge National Laboratory (ORNL). The goal of this project is to validate and verify implementations of the programming model features in various compilers.
Sunita’s group builds validation and verification testsuite (V&V) for OpenACC directive-based paralell programming models. Work on OpenACC testsuite is supported by OpenACC/NVIDIA. The goal of this project is to validate and verify implementations of the programming model features in various compilers. This testsuite has been integrated into the harness infrastructure of the TITAN and Summitdev systems at Oak Ridge National Lab and is being used for production.