1. Wang Chen, Dr. Miriam Leeser, Dr. Carey Rappaport wchen@ece.neu.edu mel@ece.neu.edu rappaport@ece.neu.edu Goal Speedup 3D Finite-Difference Time-Domain (FDTD) Algorithm through the use of Field Programmable Gate Arrays (FPGAs). We have implemented the 2D FDTD on the FIREBIRD™/PCI board before. Now the New WILDSTAR™-II PRO/PCI board from Annapolis Micro Systems, Inc. is the target for our 3D FDTD hardware implementation. Reconfigurable Hardware Performance Result FDTD Hardware Design Structure Current Work We quantize the double floating-point precision data to fix-point data for hardware implementation according to data analysis. The Forward Model simulates the whole electromagnetic space and wave propagation in the model space with Ground Penetrating Radar, dispersive soil and rough air-soil surface. We Compare the relative error between floating-point Fortran code and fixed-point C code. We Choose the suitable bit-width considering the trade-off between accuracy and area. Abstract Understanding and predicting electromagnetic behavior is needed more and more in modern technology. The Finite- Difference Time-Domain (FDTD) method is a powerful computational electromagnetic technique for modelling electromagnetic space. However, the computation of this method is complex and time consuming. Implementing this algorithm in hardware will greatly increase its computational speed and widen its usage. We present the first fixed-point 3D FDTD FPGA accelerator, which supports a wide range of materials including dispersive media. By analyzing the performance of fixed- point arithmetic in both soil-based media and human tissue media, we choose the right fixed-point representation to minimize the relative error between fixed-point and floating point results. The FPGA accelerator supports the UPML absorbing boundary conditions which have better performance in dispersive soil and human tissue media than PML boundary conditions. The 3D FDTD design is implemented on a WildStarII-Pro FPGA board and experimental results is provided. The speedup is due to pipelining, parallelism, use of fixed point arithmetic, and careful memory architecture design. Acceleration of the 3D FDTD Algorithm in Fixed- point Arithmetic using Reconfigurable Hardware WILDSTAR™-II PRO/PCI  Fixed-point components is faster in hardware design  Data range of the FDTD algorithm is good for the fixed-point representation Block Diagram Architecture Electric Field Updating Pipeline Features of the WILDSTAR™-II PRO/PCI boards: Uses two Xilinx® Virtex-II Pro™ FPGAs XC2V70 (33088 slices and 5904Kb BlockRAM) 12 ports of DDR II SRAM totally 48MBytes, 2 ports of DDR SDRAM totally 256 MBytes 11 GBytes/sec memory bandwidth FDTD Application Models The 3D FDTD Buried Object Detection Forward Model and Breast Cancer Detection Forward Model were developed by Panos Kosmas and Dr. Carey Rappaport of Northeastern University. 3D UPML FDTD Hardware Implementation Schneider et. al. implement the 1D FDTD on hardware, but the architecture is too simple. Durbano et. al. implement the 3D FDTD on hardware, but their design use floating-point representation which sacrifice the speed for the precision. Memory Interface This work was supported in part by CenSSIS, the Center for Subsurface Sensing and Imaging Systems, under the Engineering Research Centers Program of the National Science Foundation (Award Number EEC-9986821). This work is a part of CenSSIS Research Thrust R3A. As we know, forward modeling of large complex scattering geometries is too slow for real-time applications or iterative solution of inverse problems. Our goal is to develop hardware/software implementation of forward modeling processing to achieve real-time inversion. Research Level 1 Thrust R3A Our 3D FDTD implementation has 16 times speedup compared to 3.0G PC, using fixed-point representation and support dispervice media and UPML boundary conditions. State of the Art [1] Ryan N. Schneider et. al., ``Application of FPGA Technology to Accelerate the Finite-Difference Time-Domain (FDTD) Method'', Proceedings of the FPGA 2002, pp.97 - 105. [2] J. P. Durbano et. al., ``FPGA-Based Acceleration of the 3D Finite-Difference Time- Domain Method”, Proceeding of the FCCM 2004, pp. 156-163. Publications Acknowledging NSF Support [1] W. Chen, P. Kosmas, M. Leeser, C. Rappaport, "An FPGA Implementation of the Two-Dimensional Finite-Difference Time- Domain (FDTD) Algorithm", Proceedings of the 2004 ACM International Symposium on Field-Programmable Gate Arrays, February 2004, Monterey, CA, USA, pp.213-222. [2] Kosmas, P., Wang, Y., and Rappaport, C., ``Three-Dimensional FDTD Model for GPR Detection of Objects Buried in Realistic Dispersive Soil'', SPIE Aerosense Conference, Orlando, FL, April 2002, pp.330--338. R2 Fundamental Science Validating TestBEDs L1 L2 L3 R3 S1 S4 S5 S3S2 Bio-Med Enviro-Civil R1  Breast Cancer Detection Forward Model  Spiral Antenna Model  Buried Object Detection Forward Model Accurate computational modelling of microwaves in human tissue with the FDTD method is very helpful for breast cancer detection research. This model uses the modified 3D FDTD algorithm and the modified UPML ABC for better performance in dispersive human tissue Use the FDTD method to simulate the radiation of the Archimedean spiral antenna.  Optimize 3D FDTD Implementation  Two FPGA parallel computing on board  3D UPML FDTD accelerator for general FDTD problems.  More Generic Hardware Design  Support More Complex Sources  Better User Interface