Akila Gothandaraman

Learn More
— Recent technological advances have led to a number of emerging platforms such as multi-cores, reconfigurable computing, and graphics processing units. We present a comparative study of multi-cores, field-programmable gate arrays, and graphics processing units for a Quantum Monte Carlo chemistry application. The speedups of these implementations are(More)
Recent advances in FPGA technology make them an attractive platform for accelerating scientific computing applications. We present a novel hardware accelerator for Quantum Monte Carlo simulations in N-body systems. The design is deeply pipelined and exploits the inherent fine-grained parallelism available using an FPGA for all calculations. The design is(More)
We are currently exploring the use of reconfigurable computing using Field Programmable Gate Arrays (FPGAs) to accelerate kernels of scientific applications. Here, we present a hardware architecture targeted towards the acceleration of two scientific kernels in a Quantum Monte Carlo (QMC) application applied to N-body systems. Quantum Monte Carlo methods(More)
The discrete element method (DEM) is used to accurately predict the motion over time of a large number of particles such as molecules or particles of soil. The computational demands for DEM simulations are quite significant, so improved performance could address a spectrum of scientific and engineering applications. This paper proposes an accelerated(More)
  • 1