Design of a Cluster-Coupled Hardware Accelerator for FFT Computation

This thesis is related to the design of a hardware accelerator computing the Fast Fourier Transform (FFT) to be integrated into a PULP cluster. The project has been realized partly at the University of Bologna and partly at ETH Zurich. PULP (Parallel Ultra Low Power) platform is a joint project between the Energy-efficient Embedded Systems (EEES) group of UNIBO and the Integrated Systems Laboratory (IIS) of ETH Zurich that started in 2013. The FFT not only is used in data analytics but also represents a front-end for machine learning and neural networks application. The goal of this accelerator is to speed up these kinds of algorithms and to compute them in an ultra-low-power manner. For the project described in this thesis, the radix-2 DIT (Decimation-in-Time) FFT has been implemented and the whole design has been realized in synthesizable SystemVerilog. Fixed-point arithmetic has been used within the computational part of the accelerator and the correct behavior of this unit has been evaluated making use of some MATLAB scripts. Since the accelerator has been conceived to be integrated into the PULP platform, it has been designed in compliance with the communication protocols implemented on such a board. The performance of the hardware accelerator has then been estimated in terms of area, timing, flexibility, and execution time. It has resulted to be seven times faster than a highly optimized software running FFT on 8 cores. In 22 nm technology, it occupies around 115000 µm² and it is characterized by a maximum clock frequency of 690MHz. To avoid frequent conflicts accessing the external memory, a buffer has been internalized into the accelerator. Such a choice has led to shorter execution times but has increased considerably the overall area. Finally, a way to remove the internal buffer has been studied and the features of this new possible design have been compared to the results obtained for the implemented version of the FFT hardware accelerator

FPGA Implementation of Fast Fourier Transform Core Using NEDA

Transforms like DFT are a major block in communication systems such as OFDM, etc. This thesis reports architecture of a DFT core using NEDA. The advantage of the proposed architecture is that the entire transform can be implemented using adder/subtractors and shifters only, thus minimising the hardware requirement compared to other architectures. The proposed design is implemented for 16-bit data path (12–bit for comparison) considering both integer representation as well as fixed point representation, thus increasing the scope of usage. The proposed design is mapped on to Xilinx XC2VP30 FPGA, which is fabricated using 130 nm process technology. The maximum on board frequency of operation of the proposed design is 122 MHz. NEDA is one of the techniques to implement many signal processing systems that require multiply and accumulate units. FFT is one of the most employed blocks in many communication and signal processing systems. The FPGA implementation of a 16 point radix-4 complex FFT is proposed. The proposed design has improvement in terms of hardware utilization compared to traditional methods. The design has been implemented on a range of FPGAs to compare the performance. The maximum frequency achieved is 114.27 MHz on XC5VLX330 FPGA and the maximum throughput, 1828.32 Mbit/s and minimum slice delay product, 9.18. The design is also implemented using synopsys DC synthesis in both 65 nm and 180 nm technology libraries. The advantages of multiplier-less architectures are reduced hardware and improved latency. The multiplier-less architectures for the implementation of radix-2^2 folded pipelined complex FFT core are based on NEDA. The number of points considered in the work is sixteen and the folding is done by a factor of four. The proposed designs are implemented on Xilinx XC5VSX240T FPGA. Proposed designs based on NEDA have reduced area over 83%. The observed slice-delay product for NEDA based designs are 2.196 and 5.735

New FFT/IFFT Factorizations with Regular Interconnection Pattern Stage-to-Stage Subblocks

Les factoritzacions de la FFT (Fast Fourier Transform) que presenten un patró d’interconnexió regular entre factors o etapes son conegudes com algorismes paral·lels, o algorismes de Pease, ja que foren originalment proposats per Pease. En aquesta contribució s’han desenvolupat noves factoritzacions amb blocs que presenten el patró d’interconnexió regular de Pease. S’ha mostrat com aquests blocs poden ser obtinguts a una escala prèviament seleccionada. Les noves factoritzacions per ambdues FFT i IFFT (Inverse FFT) tenen dues classes de factors: uns pocs factors del tipus Cooley-Tukey i els nous factors que proporcionen la mateix patró d’interconnexió de Pease en blocs. Per a una factorització donada, els blocs comparteixen dimensions, el patró d’interconnexió etapa a etapa i a més cada un d’ells pot ser calculat independentment dels altres.FFT (Fast Fourier Transform) factorizations presenting a regular interconnection pattern between factors or stages are known as parallel algorithms, or Pease algorithms since were first proposed by Pease. In this paper, new FFT/IFFT (Inverse FFT) factorizations with blocks that exhibit regular Pease interconnection pattern are derived. It is shown these blocks can be obtained at a previously selected scale. The new factorizations for both the FFT and IFFT have two kinds of factors: a few Cooley-Tukey type factors and new factors providing the same Pease interconnection pattern property in blocks. For a given factorization, these blocks share dimensions, the interconnection pattern stage-to-stage, and all of them can be calculated independently from one another.Las factoritzaciones de la FFT (Fast Fourier Transform) que presentan un patrón de interconexiones regular entre factores o etapas son conocidas como algoritmos paralelos, o algoritmos de Pease, puesto que fueron originalmente propuestos por Pease. En esta contribución se han desarrollado nuevas factoritzaciones en subbloques que presentan el patrón de interconexión regular de Pease. Se ha mostrado como estos bloques pueden ser obtenidos a una escalera previamente seleccionada. Las nuevas factoritzaciones para ambas FFT y IFFT (Inverse FFT) tienen dos clases de factores: unos pocos factores del tipo Cooley-Tukey y los nuevos factores que proporcionan el mismo patrón de interconexión de Pease en bloques. Para una factoritzación dada, los bloques comparten dimensiones, patrón d’interconexión etapa a etapa y además cada uno de ellos puede ser calculado independientemente de los otros

An equalization technique for high rate OFDM systems

In a typical orthogonal frequency division multiplexing (OFDM) broadband wireless communication system, a guard interval using cyclic prefix is inserted to avoid the inter-symbol interference and the inter-carrier interference. This guard interval is required to be at least equal to, or longer than the maximum channel delay spread. This method is very simple, but it reduces the transmission efficiency. This efficiency is very low in the communication systems, which inhibit a long channel delay spread with a small number of sub-carriers such as the IEEE 802.11a wireless LAN (WLAN). To increase the transmission efficiency, it is usual that a time domain equalizer (TEQ) is included in an OFDM system to shorten the effective channel impulse response within the guard interval. There are many TEQ algorithms developed for the low rate OFDM applications such as asymmetrical digital subscriber line (ADSL). The drawback of these algorithms is a high computational load. Most of the popular TEQ algorithms are not suitable for the IEEE 802.11a system, a high data rate wireless LAN based on the OFDM technique. In this thesis, a TEQ algorithm based on the minimum mean square error criterion is investigated for the high rate IEEE 802.11a system. This algorithm has a comparatively reduced computational complexity for practical use in the high data rate OFDM systems. In forming the model to design the TEQ, a reduced convolution matrix is exploited to lower the computational complexity. Mathematical analysis and simulation results are provided to show the validity and the advantages of the algorithm. In particular, it is shown that a high performance gain at a data rate of 54Mbps can be obtained with a moderate order of TEQ finite impulse response (FIR) filter. The algorithm is implemented in a field programmable gate array (FPGA). The characteristics and regularities between the elements in matrices are further exploited to reduce the hardware complexity in the matrix multiplication implementation. The optimum TEQ coefficients can be found in less than 4µs for the 7th order of the TEQ FIR filter. This time is the interval of an OFDM symbol in the IEEE 802.11a system. To compensate for the effective channel impulse response, a function block of 64-point radix-4 pipeline fast Fourier transform is implemented in FPGA to perform zero forcing equalization in frequency domain. The offsets between the hardware implementations and the mathematical calculations are provided and analyzed. The system performance loss introduced by the hardware implementation is also tested. Hardware implementation output and simulation results verify that the chips function properly and satisfy the requirements of the system running at a data rate of 54 Mbps

Design and Evaluation of a Scalable Engine for 3D-FFT Computation in an FPGA Cluster

The Three Dimensional Fast Fourier Transform (3D-FFT) is commonly used to solve the partial differential equations describing the system evolution in several physical phenomena, such as the motion of viscous fluids described by the Navier–Stokes equations. Simulation of such problems requires the use of a parallel High-Performance Computing architecture since the size of the problem grows with the cube of the FFT size, and the representation of the single point comprises several double precision floating- point complex numbers. Modern High-Performance Computing (HPC) systems are considering the inclusion of FPGAs as components of this computing architecture because they can combine effective hardware acceleration capabilities and dedicated communication facilities. Furthermore, the network topology can be optimized for the specific calculation that the cluster must perform, especially in the case of algorithms limited by the data exchange delay between the processors. In this paper, we explore an HPC design that uses FPGA accelerators to compute the 3DFFT. We devise a scalable FFT engine based on a custom radix-2 double-precision core that is used to implement the Decimation in Frequency version of the Cooley–Tukey FFT algorithm. The FFT engine can be adapted to different technology constraints and networking topologies by adjusting the number of cores and configuration parameters in order to minimize the overall calculation time. We compare the various possible configurations with the technological limits of available hardware. Finally, we evaluate the bandwidth required for continuous FFT execution in the APEnet toroidal mesh network.