Design and implementation of a multi-octave-band audio camera for realtime diagnosis

Noise pollution investigation takes advantage of two common methods of diagnosis: measurement using a Sound Level Meter and acoustical imaging. The former enables a detailed analysis of the surrounding noise spectrum whereas the latter is rather used for source localization. Both approaches complete each other, and merging them into a unique system, working in realtime, would offer new possibilities of dynamic diagnosis. This paper describes the design of a complete system for this purpose: imaging in realtime the acoustic field at different octave bands, with a convenient device. The acoustic field is sampled in time and space using an array of MEMS microphones. This recent technology enables a compact and fully digital design of the system. However, performing realtime imaging with resource-intensive algorithm on a large amount of measured data confronts with a technical challenge. This is overcome by executing the whole process on a Graphic Processing Unit, which has recently become an attractive device for parallel computing

Improving Mobile SOC\u27s Performance as an Energy Efficient DSP Platform with Heterogeneous Computing

Mobile system-on-chip (SOC) technology is improving at a staggering rate spurred primarily by the adoption of smartphones and tablets. This rapid innovation has allowed the mobile SOC to be considered in everything from high performance computing to embedded applications. In this work, modern SOC\u27s heterogeneous computing capabilities are evaluated with a focus toward digital signal processing (DSP). Evaluation is conducted on modern consumer devices running Android operating system and leveraging the relatively new RenderScript Compute to utilize CPU resources alongside other compute resources such as graphics processing units (GPUs) and digital signal processors. In order to benchmark these concepts, several implementations of both the discrete Fourier transform (DFT) and the fast Fourier transform (FFT) are tested across devices. The results show both improvement in performance and energy efficiency on many devices compared to traditional Java implementations and indicate that the mobile SOC is a relevant platform for DSP applications

Studio e realizzazione di un'architettura VLSI di un processore per l'implementazione dell'algoritmo FFT

Poiché lo standard di connessione 5G è utilizzato da un numero sempre crescente di dispositivi e si sta evolvendo per soddisfare nuove esigenze e requisiti, è diventato fondamentale studiare e progettare nuovi trasmettitori e ricevitori più veloci ed efficienti. Un ruolo fondamentale nella connessione 5G è svolto dal multiplexing a divisione di frequenza ortogonale (OFDM), una metodologia di modulazione. Poiché la demodulazione è basata sulla trasformata di Fourier, lo scopo di questa tesi è realizzare un processore in grado di implementare algoritmi FFT e DFT su sequenze di lunghezza variabile che rispetti i criteri dello standard 5G. Per fare ciò, è stata prima condotta un'analisi del rapporto dell'Unione internazionale delle telecomunicazioni ITU-R M.2410-0 per definire i requisiti minimi per il processore. Successivamente, uno studio dello stato dell'arte per dispositivi simili ha portato allo sviluppo di un'architettura VLSI adatta all'applicazione. Una versione RTL dell'architettura è stata implementata in VHDL e testata.Since the 5G connection standard is utilized by a rising number of devices and is evolving to meet new needs and requirements, it has become crucial to study and design new, faster, and more efficient transmitters and receivers. A fundamental role in the 5G connection is played by Orthogonal frequency-division multiplexing (OFDM), an encoding methodology. Since the demodulation is based on the Fourier Transform, the purpose of this thesis is to realize a processor capable of implementing FFT and DFT algorithms on variable length sequences that complies with the 5G standard criteria. In order to do so, first an analysis of the International Telecommunication Union report ITU-R M.2410-0 has been conducted to define the minimum requirements for the processor. Then, a study of the state of the art for similar devices led to the development of a VLSI architecture suitable for the application. An RTL version of the architecture has been implemented in VHDL and tested

H-SIMD machine : configurable parallel computing for data-intensive applications

This dissertation presents a hierarchical single-instruction multiple-data (H-SLMD) configurable computing architecture to facilitate the efficient execution of data-intensive applications on field-programmable gate arrays (FPGAs). H-SIMD targets data-intensive applications for FPGA-based system designs. The H-SIMD machine is associated with a hierarchical instruction set architecture (HISA) which is developed for each application. The main objectives of this work are to facilitate ease of program development and high performance through ease of scheduling operations and overlapping communications with computations. The H-SIMD machine is composed of the host, FPGA and nano-processor layers. They execute host SIMD instructions (HSIs), FPGA SIMD instructions (FSIs) and nano-processor instructions (NPLs), respectively. A distinction between communication and computation instructions is intended for all the HISA layers. The H-SIMD machine also employs a memory switching scheme to bridge the omnipresent large bandwidth gaps in configurable systems. To showcase the proposed high-performance approach, the conditions to fully overlap communications with computations are investigated for important applications. The building blocks in the H-SLMD machine, such as high-performance and area-efficient register files, are presented in detail. The H-SLMD machine hierarchy is implemented on a host Dell workstation and the Annapolis Wildstar II FPGA board. Significant speedups have been achieved for matrix multiplication (MM), 2-dimensional discrete cosine transform (2D DCT) and 2-dimensional fast Fourier transform (2D FFT) which are used widely in science and engineering. In another FPGA-based programming paradigm, a high-level language (here ANSI C) can be used to program the FPGAs in a mode similar to that of the H-SIMD machine in terms of trying to minimize the effect of overheads. More specifically, a multi-threaded overlapping scheme is proposed to reduce as much as possible, or even completely hide, runtime FPGA reconfiguration overheads. Nevertheless, although the HLL-enabled reconfigurable machine allows software developers to customize FPGA functions easily, special architecture techniques are needed to achieve high-performance without significant penalty on area and clock frequency. Two important high-performance applications, matrix multiplication and image edge detection, are tested on the SRC-6 reconfigurable machine. The implemented algorithms are able to exploit the available data parallelism with independent functional units and application-specific cache support. Relevant performance and design tradeoffs are analyzed

From FPGA to ASIC: A RISC-V processor experience

This work document a correct design flow using these tools in the Lagarto RISC- V Processor and the RTL design considerations that must be taken into account, to move from a design for FPGA to design for ASIC

Computation Enhancement using Reconfigurable Computing

In light of the industry’s constant need for better computer performance, this project aims to choose and evaluate an approach for facing this issue. The targeted category of computers is single board computers (e.g. Raspberry Pi). The approach utilized for enhancing performance is the use of reconfigurable computing as to execute computationally expensive calculations on a runtime custom-tailored hardware. The objective of this project is the test of the potential this approach has for increasing computers performance through comparing a software implementation of an algorithm with an FPGA assisted implementation of the same algorithm. The platforms chosen for this project are the Rapsberry Pi and the Parallella P1602 board with its Zynq SoC for the software implementation and the FPGA assisted implementation in that order. The chosen algorithm is Fourier Fast Transform due to its part in many DSP applications and its suitability for the project objective. While the software solution worked successfully resulting in an asymptotic cost of O(N log N); the reconfigurable computing solution couldn’t be completed due to time constraints and lack of experience of the student. Future work should complete the experiment and add a multicore implementation of the same algorithm to add yet another class to the comparison

A Modular Mixed Signal VLSI Design Approach for Digital Radar Applications

This study explores the idea of building a library of VHDL configurable components for use in digital radar applications. Configurable components allows a designer to choose which components he or she needs and configures those components for a specific application. By doing this, design time for ASICs and FPGAs is shortened because the components are already designed and tested. This idea is demonstrated with a configurable dynamic pipelinable fast fourier transform. Many FFT implementations exist, but this implementation is both configurable and dynamic. Pre-synthesis customization allows the FFT to be tailored to almost any DSP application, and the dynamic property allows the FFT to calculate different length FFTs run-time. Three objectives will be accomplished: design and characterization of the aforementioned FFT; analysis of the error involved in the FFT calculation using different twiddle factor bit widths; and finally an analysis of all the configurations for the synthesized design using a 90nm technology library. Speeds of up to 225 MHz have been simulated for a length-1024 FFT using the 90 nm technology