A Multi-layer Fpga Framework Supporting Autonomous Runtime Partial Reconfiguration

Partial reconfiguration is a unique capability provided by several Field Programmable Gate Array (FPGA) vendors recently, which involves altering part of the programmed design within an SRAM-based FPGA at run-time. In this dissertation, a Multilayer Runtime Reconfiguration Architecture (MRRA) is developed, evaluated, and refined for Autonomous Runtime Partial Reconfiguration of FPGA devices. Under the proposed MRRA paradigm, FPGA configurations can be manipulated at runtime using on-chip resources. Operations are partitioned into Logic, Translation, and Reconfiguration layers along with a standardized set of Application Programming Interfaces (APIs). At each level, resource details are encapsulated and managed for efficiency and portability during operation. An MRRA mapping theory is developed to link the general logic function and area allocation information to the device related physical configuration level data by using mathematical data structure and physical constraints. In certain scenarios, configuration bit stream data can be read and modified directly for fast operations, relying on the use of similar logic functions and common interconnection resources for communication. A corresponding logic control flow is also developed to make the entire process autonomous. Several prototype MRRA systems are developed on a Xilinx Virtex II Pro platform. The Virtex II Pro on-chip PowerPC core and block RAM are employed to manage control operations while multiple physical interfaces establish and supplement autonomous reconfiguration capabilities. Area, speed and power optimization techniques are developed based on the developed Xilinx prototype. Evaluations and analysis of these prototype and techniques are performed on a number of benchmark and hashing algorithm case studies. The results indicate that based on a variety of test benches, up to 70% reduction in the resource utilization, up to 50% improvement in power consumption, and up to 10 times increase in run-time performance are achieved using the developed architecture and approaches compared with Xilinx baseline reconfiguration flow. Finally, a Genetic Algorithm (GA) for a FPGA fault tolerance case study is evaluated as a ultimate high-level application running on this architecture. It demonstrated that this is a hardware and software infrastructure that enables an FPGA to dynamically reconfigure itself efficiently under the control of a soft microprocessor core that is instantiated within the FPGA fabric. Such a system contributes to the observed benefits of intelligent control, fast reconfiguration, and low overhead

Design of Digital Advanced Systems Based on Programmable System on Chip

This chapter fills up an advanced analysis of the state-of-the-art design in programmable SoC systems, giving a critical overall vision for every designer to implement real time operating systems and concurrent processing. The content of the chapter is divided in the next four main sections. First the evolution timeline of FPGA based systems is covered from its beginning until the last AP SoC chips. They are complex devices and it is necessary to have a well-known understanding to utilise them in the more efficient form possible. The more important advance digital systems structures and architectures are described. The embedded AP SoCs are analysed and main design methodologies are covered, focusing in hardware and co-design strategies. In this section is described the development of a real open source application that covers the fundamental parts in the design of a SoC system, ranging from the hardware development until the software design involving the embedded operating system and the user interface application. Finally, the system described in the last section is tested in a real scientific experiment and the results are evaluated

Embedded electronic systems driven by run-time reconfigurable hardware

Abstract This doctoral thesis addresses the design of embedded electronic systems based on run-time reconfigurable hardware technology –available through SRAM-based FPGA/SoC devices– aimed at contributing to enhance the life quality of the human beings. This work does research on the conception of the system architecture and the reconfiguration engine that provides to the FPGA the capability of dynamic partial reconfiguration in order to synthesize, by means of hardware/software co-design, a given application partitioned in processing tasks which are multiplexed in time and space, optimizing thus its physical implementation –silicon area, processing time, complexity, flexibility, functional density, cost and power consumption– in comparison with other alternatives based on static hardware (MCU, DSP, GPU, ASSP, ASIC, etc.). The design flow of such technology is evaluated through the prototyping of several engineering applications (control systems, mathematical coprocessors, complex image processors, etc.), showing a high enough level of maturity for its exploitation in the industry.Resumen Esta tesis doctoral abarca el diseño de sistemas electrónicos embebidos basados en tecnología hardware dinámicamente reconfigurable –disponible a través de dispositivos lógicos programables SRAM FPGA/SoC– que contribuyan a la mejora de la calidad de vida de la sociedad. Se investiga la arquitectura del sistema y del motor de reconfiguración que proporcione a la FPGA la capacidad de reconfiguración dinámica parcial de sus recursos programables, con objeto de sintetizar, mediante codiseño hardware/software, una determinada aplicación particionada en tareas multiplexadas en tiempo y en espacio, optimizando así su implementación física –área de silicio, tiempo de procesado, complejidad, flexibilidad, densidad funcional, coste y potencia disipada– comparada con otras alternativas basadas en hardware estático (MCU, DSP, GPU, ASSP, ASIC, etc.). Se evalúa el flujo de diseño de dicha tecnología a través del prototipado de varias aplicaciones de ingeniería (sistemas de control, coprocesadores aritméticos, procesadores de imagen, etc.), evidenciando un nivel de madurez viable ya para su explotación en la industria.Resum Aquesta tesi doctoral està orientada al disseny de sistemes electrònics empotrats basats en tecnologia hardware dinàmicament reconfigurable –disponible mitjançant dispositius lògics programables SRAM FPGA/SoC– que contribueixin a la millora de la qualitat de vida de la societat. S’investiga l’arquitectura del sistema i del motor de reconfiguració que proporcioni a la FPGA la capacitat de reconfiguració dinàmica parcial dels seus recursos programables, amb l’objectiu de sintetitzar, mitjançant codisseny hardware/software, una determinada aplicació particionada en tasques multiplexades en temps i en espai, optimizant així la seva implementació física –àrea de silici, temps de processat, complexitat, flexibilitat, densitat funcional, cost i potència dissipada– comparada amb altres alternatives basades en hardware estàtic (MCU, DSP, GPU, ASSP, ASIC, etc.). S’evalúa el fluxe de disseny d’aquesta tecnologia a través del prototipat de varies aplicacions d’enginyeria (sistemes de control, coprocessadors aritmètics, processadors d’imatge, etc.), demostrant un nivell de maduresa viable ja per a la seva explotació a la indústria

Intrinsically Evolvable Artificial Neural Networks

Dedicated hardware implementations of neural networks promise to provide faster, lower power operation when compared to software implementations executing on processors. Unfortunately, most custom hardware implementations do not support intrinsic training of these networks on-chip. The training is typically done using offline software simulations and the obtained network is synthesized and targeted to the hardware offline. The FPGA design presented here facilitates on-chip intrinsic training of artificial neural networks. Block-based neural networks (BbNN), the type of artificial neural networks implemented here, are grid-based networks neuron blocks. These networks are trained using genetic algorithms to simultaneously optimize the network structure and the internal synaptic parameters. The design supports online structure and parameter updates, and is an intrinsically evolvable BbNN platform supporting functional-level hardware evolution. Functional-level evolvable hardware (EHW) uses evolutionary algorithms to evolve interconnections and internal parameters of functional modules in reconfigurable computing systems such as FPGAs. Functional modules can be any hardware modules such as multipliers, adders, and trigonometric functions. In the implementation presented, the functional module is a neuron block. The designed platform is suitable for applications in dynamic environments, and can be adapted and retrained online. The online training capability has been demonstrated using a case study. A performance characterization model for RC implementations of BbNNs has also been presented

High level modeling of Partially Dynamically Reconfigurable FPGAs based on MDE and MARTE

International audienceSystem-on-Chip (SoC) architectures are becoming the preferred solution for implementing modern embedded systems. However their design complexity continues to augment due to the increase in integrated hardware resources requiring new design methodologies and tools. In this paper we present a novel SoC co-design methodology based on aModel Driven Engineering framework while utilizing the MARTE (Modeling and Analysis of Real-time and Embedded Systems) standard. This methodology permits us to model fine grain reconfigurable architectures such as FPGAs and allows to extend the standard for integrating new features such as Partial Dynamic Reconfiguration supported by modern FPGAs. The overall objective is to carry out modeling at a high abstraction level expressed in a graphical language like UML (Unified Modeling Language) and afterwards transformations of these models, automatically generate the necessary specifications required for FPGA implementation

Microprocessor and FPGA interfaces for in-system co-debugging in field programmable hybrid systems

Modern trends in technology require efficient control and processing platforms based on connected software-hardware subsystems. Due to their complexity and size, algorithms implemented on these platforms are difficult to test and verify. When these types of solution are being designed, it is necessary to provide information of the internal values of registers and memories of both the software and hardware during the execution of the complete system. The final architecture of the targeted design and its debugging capabilities strongly depends on how the hybrid system is connected and clocked. This article discusses different architectural strategies that have been adopted for a hybrid hardware-software platform, built ready for debugging, and that uses components that can be easily found with a few special features. All the solutions have been implemented and evaluated using the UNSHADES-2 framework

MARTE based modeling approach for Partial Dynamic Reconfigurable FPGAs

International audienceAs System-on-Chip (SoC) architectures become pivotal for designing embedded systems, the SoC design complexity continues to increase exponentially necessitating the need to find new design methodologies. In this paper we present a novel SoC co-design methodology based on Model Driven Engineering using the MARTE (Modeling and Analysis of Real-time and Embedded Systems) standard. This methodology is utilized to model fine grain reconfigurable architectures such as FPGAs and extends the standard to integrate new features such as Partial Dynamic Reconfiguration supported by modern FPGAs. The goal is to carry out modeling at a high abstraction level expressed in UML (Unified Modeling Language) and following transformations of these models, automatically generate the code necessary for FPGA implementation