Research on Acceleration Technology for FDTD Based on Vivado HLS

时域有限差分法(Finitedifferencetimedomainmethod，FDTD)是一种电磁学计算的基本方法，通过空间内电场和磁场的交替计算，得到整个研究空间的电磁分布情况。对于很多电磁学问题，不论从概念上还是可实现性上来讲，时域有限差分方法都是最简单的计算方法。时域有限差分法可以解决复杂的电磁计算问题，但同时要消耗大量的计算机资源，并且花费较长的计算时间。为了更快速高效地得到计算结果，可以利用硬件技术进行加速，这也是近年来FDTD方法研究领域比较受关注的部分。Xilinx公司新推出的高级综合工具VivadoHLS(HighLevelSynthesis)，直接通过C/C++语言开发硬...In the field of computational electromagnetics, finite difference time domain method (FDTD) has been widely used. Using FDTD, the electromagnetic distribution of the whole field is obtained by alternating calculation of the electric and magnetic field. For many electromagnetical computational problems, FDTD is the simplest method, in consideration of conception and achievability. Although FDTD can...学位：工程硕士院系专业：物理科学与技术学院_工程硕士(电子与通信工程)学号：3432014115280

Viability of Numerical Full-Wave Techniques in Telecommunication Channel Modelling

In telecommunication channel modelling the wavelength is small compared to the physical features of interest, therefore deterministic ray tracing techniques provide solutions that are more efficient, faster and still within time constraints than current numerical full-wave techniques. Solving fundamental Maxwell's equations is at the core of computational electrodynamics and best suited for modelling electrical field interactions with physical objects where characteristic dimensions of a computing domain is on the order of a few wavelengths in size. However, extreme communication speeds, wireless access points closer to the user and smaller pico and femto cells will require increased accuracy in predicting and planning wireless signals, testing the accuracy limits of the ray tracing methods. The increased computing capabilities and the demand for better characterization of communication channels that span smaller geographical areas make numerical full-wave techniques attractive alternative even for larger problems. The paper surveys ways of overcoming excessive time requirements of numerical full-wave techniques while providing acceptable channel modelling accuracy for the smallest radio cells and possibly wider. We identify several research paths that could lead to improved channel modelling, including numerical algorithm adaptations for large-scale problems, alternative finite-difference approaches, such as meshless methods, and dedicated parallel hardware, possibly as a realization of a dataflow machine

Numerical solutions of differential equations on FPGA-enhanced computers

Conventionally, to speed up scientific or engineering (S&E) computation programs on general-purpose computers, one may elect to use faster CPUs, more memory, systems with more efficient (though complicated) architecture, better software compilers, or even coding with assembly languages. With the emergence of Field Programmable Gate Array (FPGA) based Reconfigurable Computing (RC) technology, numerical scientists and engineers now have another option using FPGA devices as core components to address their computational problems. The hardware-programmable, low-cost, but powerful “FPGA-enhanced computer” has now become an attractive approach for many S&E applications. A new computer architecture model for FPGA-enhanced computer systems and its detailed hardware implementation are proposed for accelerating the solutions of computationally demanding and data intensive numerical PDE problems. New FPGAoptimized algorithms/methods for rapid executions of representative numerical methods such as Finite Difference Methods (FDM) and Finite Element Methods (FEM) are designed, analyzed, and implemented on it. Linear wave equations based on seismic data processing applications are adopted as the targeting PDE problems to demonstrate the effectiveness of this new computer model. Their sustained computational performances are compared with pure software programs operating on commodity CPUbased general-purpose computers. Quantitative analysis is performed from a hierarchical set of aspects as customized/extraordinary computer arithmetic or function units, compact but flexible system architecture and memory hierarchy, and hardwareoptimized numerical algorithms or methods that may be inappropriate for conventional general-purpose computers. The preferable property of in-system hardware reconfigurability of the new system is emphasized aiming at effectively accelerating the execution of complex multi-stage numerical applications. Methodologies for accelerating the targeting PDE problems as well as other numerical PDE problems, such as heat equations and Laplace equations utilizing programmable hardware resources are concluded, which imply the broad usage of the proposed FPGA-enhanced computers

Improving finite-difference time-domain memory bandwidth by using block floating-point arithmetic

Докторска теза анализира предлог за уштеду меморијских ресурса у меморијски интензвином алгоритму. Предмет истраживања је проналажење решења које би услед ефикаснијег руковања меморијом имало и мању потрошњу исте што би резултовало ефикаснијим системом и решењем. Резултат истраживања је симулација која потрвђује хипотезу, као и физичка имплементација која проверава исправност концепта.Doktorska teza analizira predlog za uštedu memorijskih resursa u memorijski intenzvinom algoritmu. Predmet istraživanja je pronalaženje rešenja koje bi usled efikasnijeg rukovanja memorijom imalo i manju potrošnju iste što bi rezultovalo efikasnijim sistemom i rešenjem. Rezultat istraživanja je simulacija koja potrvđuje hipotezu, kao i fizička implementacija koja proverava ispravnost koncepta.PhD thesis analyzes a proposal for improving memory bandwidth in a memory intense algorithm. The purpose of the study is to find a more effective and efficient solution which would use less memory for the same algorithm and thus have better performance. The result of the study is a simulation model which proves the hypothesis as well as a hardware implementation on an FPGA development board which acts as a proof of concept