Graduate Exam Abstract

swetha varadarajan

M.S. Final
October 26, 2017, 3:00 pm - 5:00 pm
CSB 305

Abstract: Studying RNA-RNA interaction has led to major successes in the treatment of some cancers, including colon, breast and pancreatic cancer by suppressing the gene expression involved in the development of these diseases. The problem with such programs is that they are computationally and memory intensive: O(N4) space and O(N6) time complexity. Moreover, the entire application is complicated, and involves many mutually recursive data variables. We address the problem of speeding up a surrogate kernel (named OSPSQ) that captures the main dependence pattern found in two widely used RNA-RNA interaction applications - IRIS and piRNA. The structure of the OSPSQ kernel perfectly fits the constraints of the polyhedral model, a well-developed technology for optimizing codes that belong to many specialized domains. However, the current state-of-the-art automatic polyhedral tools do not significantly improve the performance of the baseline implementation of OSPSQ. With simple techniques like loop permutation and skewing, we achieve an average of 17x sequential and 31x parallel speedup on a standard modern multi-core platform (Intel Broadwell, E5-1650v4). This performance represents 75% and 88% of attainable single-core and multi-core L1 bandwidth. For further performance improvement, we describe how to tile all six dimensions and also formulate the associated memory trade-off. In the future, we plan to implement these tiling strategies, explore the performance of the code for various tile sizes and optimize the whole piRNA application.

Adviser: Sanjay Rajopadhye
Co-Adviser: N.A.
Non-ECE Member: Wim Bohm, Computer Science
Member 3: Jesse Wilson, Electrical & Computer Engineering
Addional Members: N.A.


Program of Study:
ECE 561
CS 475
ECE 554
CS 575
MATH 510
CS 545