AbstractAbstract Currently, Mmolecular dynamics simulations are mostly carried outaccelerated by supercomputers that are made up of either by a clusters of microprocessors or by a custom ASIC systems. However, Tthe power dissipation of the microprocessors and the non-recurring engineering (NRE) cost of the custom ASICs could make this breedthese of simulation systems not very cost-efficient. With the increasing performance and density of the Field Programmable Gate Array (FPGA), an FPGA system is now capable of performing accelerating molecular dynamics simulations at in a cost-performance level that is surpassing that of the supercomputerseffective way.
This thesis describes the design, the implementation, and the verification effort of an FPGA compute engine, named the Reciprocal Sum Compute Engine (RSCE), that computes calculates the reciprocal space contribution of to the electrostatic energy and forces using the Smooth Particle Mesh Ewald (SPME) algorithm [1, 2]. Furthermore, this thesis also investigates the fixed pointed precision requirement, the speedup capability, and the parallelization strategy of the RSCE. Thise FPGA, named Reciprocal Sum Compute Engine (RSCE), is intended to be used with other compute engines in a multi-FPGA system to speedup molecular dynamics simulations. The design of the RSCE aims to provide maximum speedup against software implementations of the SPME algorithm while providing flexibility, in terms of degree of parallelization and scalability, for different system architectures.
The RSCE RTL design was done in Verilog and the self-checking testbench was built using SystemC. The SystemC RSCE behavioral model used in the testbench was also used as a fixed-point RSCE model to evaluate the precision requirement of the energy and forces computations. The final RSCE design was downloaded to the Xilinx XCV-2000 multimedia board  and integrated with NAMD2 MD program . Several demo molecular dynamics simulations were performed to prove the correctness of the FPGA implementation.
Aknowledgement Working on this thesis is certainly a memorable and enjoyable event in my life. I have learned a lot of interesting new things that have broadened my view of the engineering field. In here, I would like to offer my appreciation and thanks to several grateful and helpful individuals. Without them, the thesis could not have been completed and the experience would not be so enjoyable.
First of all, I would like to thank my supervisor Professor Paul Chow for his valuable guidance and creative suggestions that helped me to complete this thesis. Furthermore, I am also very thankful to have an opportunity to learn from him on the aspect of using the advancing FPGA technology to improve the performance for different computer applications. Hopefully, this experience will inspire me to come up with new and interesting research ideas in the future.
I also would like to thank Canadian Microelectronics Corporation for generously providing us with software tools and hardware equipment that were very useful during the implementation stage of this thesis.
Furthermore, I want to offer my thanks to Professor Régis Pomès and Chris Madill on providing me with valuable background knowledge on the molecular dynamics field. Their practical experiences have substantially helped me to ensure the practicality of this thesis work. I also want to thank Chris Comis, Lorne Applebaum, and especially, David Pang Chin Chui for all the fun in the lab and all the helpful and inspiring discussions that helped me to make important improvements on this thesis work.
Last but not least, I really would like to thank my family members, including my newly married wife, Emma Man Yuk Wong and my twin brother, Alan Tat Man Lee, in supporting me to pursue a Master degree in the University of Toronto. Their love and support strengthened and delighted me to complete this thesis with happiness.