◆ I earned my B.Tech from the Indian Institute of Technology (I.I.T), Madras (1997) and my PhD in Computer Science (high-performance heterogeneous computing) at UCD (2005). My research centres on heterogeneous parallel computing and energy-efficient computing.
I develop models, algorithms, and tools to optimise applications for performance and energy on extreme-scale heterogeneous platforms — cloud, grid, and supercomputers.
◆ I am co‑author of functional performance & energy models, a theoretical framework for energy predictive models, and analyses of energy proportionality in modern server processors. I have also built accurate linear energy predictive models, model‑based methods, and data‑partitioning algorithms for bi‑objective optimisation of performance and energy on heterogeneous platforms.
◆ I am the author of Heterogeneous MPI (an extension of MPI for heterogeneous clusters) and Heterogeneous ScaLAPACK (a linear algebra package for heterogeneous clusters). My work appears in top journals and conferences on parallel & distributed computing and energy science.
◆ I direct the M.Sc. in Computer Science through Negotiated Learning (ucdmscnl.com) and serve as Postdoctoral Coordinator in the School of Computer Science. I am also a member of the School’s Equality, Diversity, and Inclusion (EDI) committee, contributing to the ATHENA SWAN action plans.
◆ With 11+ years of industrial experience at IONA Technologies, Ansys, and Siemens Research, I have worked on distributed middleware, high‑performance web services, parallel CFD, and IBM mainframe processing.