Hardware synergistic algorithms




The evolution of scientific calculations is contingent on the concerted advancement of the underlying algorithms and the computer systems that they use.


It is now a time of fundamental change in computing. The end of Dennard scaling and the inevitable slowdown of Moore's law are progressively leading to the end of the general-purpose processor's era, due to their power-inefficient use of transistors. In order to achieve higher performance than general-purpose systems, novel supercomputers adopt heterogeneous architectures where CPUs are dedicated mostly to flow control while special-purpose accelerators absorb the vast majority of the computational workload. 



The focus of this project is to design novel computational science algorithms that are more scalable and that can efficiently reap performance benefits from the increasingly complex and heterogeneous computer hardware, such as many-GPU architectures.



Two examples of hardware-synergistic algorithms that we developed for application in computational chemistry are the Fragmentation-Based Accelerated Hartree-Fock algorithm in libcchem (GAMESS), and the Q-MP2 algorithm in Q-Chem.


For more information on how to contact me to discuss the specifics of PhD/Honours projects, please refer to my web page https://www.gbarca.com/openings.






Heterogeneous computing, GPU computing, massively parallel, accelerators

Updated:  1 June 2019/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing