Novel Front-end Electronics for Time Projection Chamber Detectors

Este trabajo ha sido realizado en la Organización Europea para la Investigación Nuclear (CERN) y forma parte del proyecto de investigación Europeo para futuros aceleradores lineales (EUDET). En física de partículas existen diferentes categorías de detectores de partículas. El diseño presentado esta centrado en un tipo particular de detector de trayectoria de partículas denominado TPC (Time Projection Chamber) que proporciona una imagen en tres dimensiones de las partículas eléctricamente cargadas que atraviesan su volumen gaseoso. La tesis incluye un estudio de los objetivos para futuros detectores, resumiendo los parámetros que un sistema de adquisición de datos debe cumplir en esos casos. Además, estos requisitos son comparados con los actuales sistemas de lectura utilizados en diferentes detectores TPC. Se concluye que ninguno de los sistemas cumple las restrictivas condiciones. Algunos de los principales objetivos para futuros detectores TPC son un altísimo nivel de integración, incremento del número de canales, electrónica más rápida y muy baja potencia. El principal inconveniente del estado del arte de los sistemas anteriores es la utilización de varios circuitos integrados en la cadena de adquisición. Este hecho hace imposible alcanzar el altísimo nivel de integración requerido para futuros detectores. Además, un aumento del número de canales y frecuencia de muestreo haría incrementar hasta valores no permitidos la potencia utilizada. Y en consecuencia, incrementar la refrigeración necesaria (en caso de ser posible). Una de las novedades presentadas es la integración de toda la cadena de adquisición (filtros analógicos de entrada, conversor analógico-digital (ADC) y procesado de señal digital) en un único circuito integrado en tecnología de 130nm. Este chip es el primero que realiza esta altísima integración para detectores TPC. Por otro lado, se presenta un análisis detallado de los filtros de procesado de señal. Los objetivos más importantes es la reduccióGarcía García, EJ. (2012). Novel Front-end Electronics for Time Projection Chamber Detectors [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16980Palanci

Approximate and timing-speculative hardware design for high-performance and energy-efficient video processing

Since the end of transistor scaling in 2-D appeared on the horizon, innovative circuit design paradigms have been on the rise to go beyond the well-established and ultraconservative exact computing. Many compute-intensive applications – such as video processing – exhibit an intrinsic error resilience and do not necessarily require perfect accuracy in their numerical operations. Approximate computing (AxC) is emerging as a design alternative to improve the performance and energy-efficiency requirements for many applications by trading its intrinsic error tolerance with algorithm and circuit efficiency. Exact computing also imposes a worst-case timing to the conventional design of hardware accelerators to ensure reliability, leading to an efficiency loss. Conversely, the timing-speculative (TS) hardware design paradigm allows increasing the frequency or decreasing the voltage beyond the limits determined by static timing analysis (STA), thereby narrowing pessimistic safety margins that conventional design methods implement to prevent hardware timing errors. Timing errors should be evaluated by an accurate gate-level simulation, but a significant gap remains: How these timing errors propagate from the underlying hardware all the way up to the entire algorithm behavior, where they just may degrade the performance and quality of service of the application at stake? This thesis tackles this issue by developing and demonstrating a cross-layer framework capable of performing investigations of both AxC (i.e., from approximate arithmetic operators, approximate synthesis, gate-level pruning) and TS hardware design (i.e., from voltage over-scaling, frequency over-clocking, temperature rising, and device aging). The cross-layer framework can simulate both timing errors and logic errors at the gate-level by crossing them dynamically, linking the hardware result with the algorithm-level, and vice versa during the evolution of the application’s runtime. Existing frameworks perform investigations of AxC and TS techniques at circuit-level (i.e., at the output of the accelerator) agnostic to the ultimate impact at the application level (i.e., where the impact is truly manifested), leading to less optimization. Unlike state of the art, the framework proposed offers a holistic approach to assessing the tradeoff of AxC and TS techniques at the application-level. This framework maximizes energy efficiency and performance by identifying the maximum approximation levels at the application level to fulfill the required good enough quality. This thesis evaluates the framework with an 8-way SAD (Sum of Absolute Differences) hardware accelerator operating into an HEVC encoder as a case study. Application-level results showed that the SAD based on the approximate adders achieve savings of up to 45% of energy/operation with an increase of only 1.9% in BD-BR. On the other hand, VOS (Voltage Over-Scaling) applied to the SAD generates savings of up to 16.5% in energy/operation with around 6% of increase in BD-BR. The framework also reveals that the boost of about 6.96% (at 50°) to 17.41% (at 75° with 10- Y aging) in the maximum clock frequency achieved with TS hardware design is totally lost by the processing overhead from 8.06% to 46.96% when choosing an unreliable algorithm to the blocking match algorithm (BMA). We also show that the overhead can be avoided by adopting a reliable BMA. This thesis also shows approximate DTT (Discrete Tchebichef Transform) hardware proposals by exploring a transform matrix approximation, truncation and pruning. The results show that the approximate DTT hardware proposal increases the maximum frequency up to 64%, minimizes the circuit area in up to 43.6%, and saves up to 65.4% in power dissipation. The DTT proposal mapped for FPGA shows an increase of up to 58.9% on the maximum frequency and savings of about 28.7% and 32.2% on slices and dynamic power, respectively compared with stat

Algorithm-Architecture Co-Design for Digital Front-Ends in Mobile Receivers

The methodology behind this work has been to use the concept of algorithm-hardware co-design to achieve efficient solutions related to the digital front-end in mobile receivers. It has been shown that, by looking at algorithms and hardware architectures together, more efficient solutions can be found; i.e., efficient with respect to some design measure. In this thesis the main focus have been placed on two such parameters; first reduced complexity algorithms to lower energy consumptions at limited performance degradation, secondly to handle the increasing number of wireless standards that preferably should run on the same hardware platform. To be able to perform this task it is crucial to understand both sides of the table, i.e., both algorithms and concepts for wireless communication as well as the implications arising on the hardware architecture. It is easier to handle the high complexity by separating those disciplines in a way of layered abstraction. However, this representation is imperfect, since many interconnected "details" belonging to different layers are lost in the attempt of handling the complexity. This results in poor implementations and the design of mobile terminals is no exception. Wireless communication standards are often designed based on mathematical algorithms with theoretical boundaries, with few considerations to actual implementation constraints such as, energy consumption, silicon area, etc. This thesis does not try to remove the layer abstraction model, given its undeniable advantages, but rather uses those cross-layer "details" that went missing during the abstraction. This is done in three manners: In the first part, the cross-layer optimization is carried out from the algorithm perspective. Important circuit design parameters, such as quantization are taken into consideration when designing the algorithm for OFDM symbol timing, CFO, and SNR estimation with a single bit, namely, the Sign-Bit. Proof-of-concept circuits were fabricated and showed high potential for low-end receivers. In the second part, the cross-layer optimization is accomplished from the opposite side, i.e., the hardware-architectural side. A SDR architecture is known for its flexibility and scalability over many applications. In this work a filtering application is mapped into software instructions in the SDR architecture in order to make filtering-specific modules redundant, and thus, save silicon area. In the third and last part, the optimization is done from an intermediate point within the algorithm-architecture spectrum. Here, a heterogeneous architecture with a combination of highly efficient and highly flexible modules is used to accomplish initial synchronization in at least two concurrent OFDM standards. A demonstrator was build capable of performing synchronization in any two standards, including LTE, WiFi, and DVB-H

Enhancing Real-time Embedded Image Processing Robustness on Reconfigurable Devices for Critical Applications

Nowadays, image processing is increasingly used in several application fields, such as biomedical, aerospace, or automotive. Within these fields, image processing is used to serve both non-critical and critical tasks. As example, in automotive, cameras are becoming key sensors in increasing car safety, driving assistance and driving comfort. They have been employed for infotainment (non-critical), as well as for some driver assistance tasks (critical), such as Forward Collision Avoidance, Intelligent Speed Control, or Pedestrian Detection. The complexity of these algorithms brings a challenge in real-time image processing systems, requiring high computing capacity, usually not available in processors for embedded systems. Hardware acceleration is therefore crucial, and devices such as Field Programmable Gate Arrays (FPGAs) best fit the growing demand of computational capabilities. These devices can assist embedded processors by significantly speeding-up computationally intensive software algorithms. Moreover, critical applications introduce strict requirements not only from the real-time constraints, but also from the device reliability and algorithm robustness points of view. Technology scaling is highlighting reliability problems related to aging phenomena, and to the increasing sensitivity of digital devices to external radiation events that can cause transient or even permanent faults. These faults can lead to wrong information processed or, in the worst case, to a dangerous system failure. In this context, the reconfigurable nature of FPGA devices can be exploited to increase the system reliability and robustness by leveraging Dynamic Partial Reconfiguration features. The research work presented in this thesis focuses on the development of techniques for implementing efficient and robust real-time embedded image processing hardware accelerators and systems for mission-critical applications. Three main challenges have been faced and will be discussed, along with proposed solutions, throughout the thesis: (i) achieving real-time performances, (ii) enhancing algorithm robustness, and (iii) increasing overall system's dependability. In order to ensure real-time performances, efficient FPGA-based hardware accelerators implementing selected image processing algorithms have been developed. Functionalities offered by the target technology, and algorithm's characteristics have been constantly taken into account while designing such accelerators, in order to efficiently tailor algorithm's operations to available hardware resources. On the other hand, the key idea for increasing image processing algorithms' robustness is to introduce self-adaptivity features at algorithm level, in order to maintain constant, or improve, the quality of results for a wide range of input conditions, that are not always fully predictable at design-time (e.g., noise level variations). This has been accomplished by measuring at run-time some characteristics of the input images, and then tuning the algorithm parameters based on such estimations. Dynamic reconfiguration features of modern reconfigurable FPGA have been extensively exploited in order to integrate run-time adaptivity into the designed hardware accelerators. Tools and methodologies have been also developed in order to increase the overall system dependability during reconfiguration processes, thus providing safe run-time adaptation mechanisms. In addition, taking into account the target technology and the environments in which the developed hardware accelerators and systems may be employed, dependability issues have been analyzed, leading to the development of a platform for quickly assessing the reliability and characterizing the behavior of hardware accelerators implemented on reconfigurable FPGAs when they are affected by such faults

SdrLift: A Domain-Specific Intermediate Hardware Synthesis Framework for Prototyping Software-Defined Radios

Modern design of Software-Defined Radio (SDR) applications is based on Field Programmable Gate Arrays (FPGA) due to their ability to be configured into solution architectures that are well suited to domain-specific problems while achieving the best trade-off between performance, power, area, and flexibility. FPGAs are well known for rich computational resources, which traditionally include logic, register, and routing resources. The increased technological advances have seen FPGAs incorporating more complex components that comprise sophisticated memory blocks, Digital Signal Processing (DSP) blocks, and high-speed interfacing to Gigabit Ethernet (GbE) and Peripheral Component Interconnect Express (PCIe) bus. Gateware for programming FPGAs is described at a lowlevel of design abstraction using Register Transfer Language (RTL), typically using either VHSIC-HDL (VHDL) or Verilog code. In practice, the low-level description languages have a very steep learning curve, provide low productivity for hardware designers and lack readily available open-source library support for fundamental designs, and consequently limit the design to only hardware experts. These limitations have led to the adoption of High-Level Synthesis (HLS) tools that raise design abstraction using syntax, semantics, and software development notations that are well-known to most software developers. However, while HLS has made programming of FPGAs more accessible and can increase the productivity of design, they are still not widely adopted in the design community due to the low-level skills that are still required to produce efficient designs. Additionally, the resultant RTL code from HLS tools is often difficult to decipher, modify and optimize due to the functionality and micro-architecture that are coupled together in a single High-Level Language (HLL). In order to alleviate these problems, Domain-Specific Languages (DSL) have been introduced to capture algorithms at a high level of abstraction with more expressive power and providing domain-specific optimizations that factor in new transformations and the trade-off between resource utilization and system performance. The problem of existing DSLs is that they are designed around imperative languages with an instruction sequence that does not match the hardware structure and intrinsics, leading to hardware designs with system properties that are unconformable to the high-level specifications and constraints. The aim of this thesis is, therefore, to design and implement an intermediatelevel framework namely SdrLift for use in high-level rapid prototyping of SDR applications that are based on an FPGA. The SdrLift input is a HLL developed using functional language constructs and design patterns that specify the structural behavior of the application design. The functionality of the SdrLift language is two-fold, first, it can be used directly by a designer to develop the SDR applications, secondly, it can be used as the Intermediate Representation (IR) step that is generated by a higher-level language or a DSL. The SdrLift compiler uses the dataflow graph as an IR to structurally represent the accelerator micro-architecture in which the components correspond to the fine-level and coarse-level Hardware blocks (HW Block) which are either auto-synthesized or integrated from existing reusable Intellectual Property (IP) core libraries. Another IR is in the form of a dataflow model and it is used for composition and global interconnection of the HW Blocks while making efficient interfacing decisions in an attempt to satisfy speed and resource usage objectives. Moreover, the dataflow model provides rules and properties that will be used to provide a theoretical framework that formally analyzes the characteristics of SDR applications (i.e. the throughput, sample rate, latency, and buffer size among other factors). Using both the directed graph flow (DFG) and the dataflow model in the SdrLift compiler provides two benefits: an abstraction of the microarchitecture from the high-level algorithm specifications and also decoupling of the microarchitecture from the low-level RTL implementation. Following the IR creation and model analyses is the VHDL code generation which employs the low-level optimizations that ensure optimal hardware design results. The code generation process per forms analysis to ensure the resultant hardware system conforms to the high-level design specifications and constraints. SdrLift is evaluated by developing representative SDR case studies, in which the VHDL code for eight different SDR applications is generated. The experimental results show that SdrLift achieves the desired performance and flexibility, while also conserving the hardware resources utilized

Image Processing Using FPGAs

This book presents a selection of papers representing current research on using field programmable gate arrays (FPGAs) for realising image processing algorithms. These papers are reprints of papers selected for a Special Issue of the Journal of Imaging on image processing using FPGAs. A diverse range of topics is covered, including parallel soft processors, memory management, image filters, segmentation, clustering, image analysis, and image compression. Applications include traffic sign recognition for autonomous driving, cell detection for histopathology, and video compression. Collectively, they represent the current state-of-the-art on image processing using FPGAs

Fast algorithm for real-time rings reconstruction

The GAP project is dedicated to study the application of GPU in several contexts in which real-time response is important to take decisions. The definition of real-time depends on the application under study, ranging from answer time of μs up to several hours in case of very computing intensive task. During this conference we presented our work in low level triggers [1] [2] and high level triggers [3] in high energy physics experiments, and specific application for nuclear magnetic resonance (NMR) [4] [5] and cone-beam CT [6]. Apart from the study of dedicated solution to decrease the latency due to data transport and preparation, the computing algorithms play an essential role in any GPU application. In this contribution, we show an original algorithm developed for triggers application, to accelerate the ring reconstruction in RICH detector when it is not possible to have seeds for reconstruction from external trackers