His proposal was titled "Toward a locality-enhancing transformation framework for irregular programs".
Milind Kulkarni, Assistant Professor in ECE, has been awarded an NSF CAREER award for his proposal titled, "Toward a locality-enhancing transformation framework for irregular programs."
Many domains in computer science, from data-mining to simulation to computational biology, focus heavily on irregular applications, which deal with complex algorithms that manipulate complex data structures. For example, to analyze large data sets, point correlation - a data mining algorithm - organizes data in a tree-like structure that is then manipulated to extract trends and patterns. As such algorithms become more pervasive, and, more importantly, the data sets they are applied to become much larger, writing high performance irregular applications has become critically important. However, the complexity of irregular algorithms makes writing high-performance applications very difficult: simple expressions of the algorithms do not perform well, and high-performance implementations are difficult to express. Professor Kulkarni's project aims to develop a set of tools that will let programmers write simple algorithms to solve these problems, and then automatically transform them to provide efficient, high-performance implementations.
The award is for $418,786 over 5 years.