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- Navas, Byron, 1969-
(författare)
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Cognitive and Self-Adaptive SoCs with Self-Healing Run-Time-Reconfigurable RecoBlocks
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In contrast to classical Field-Programmable Gate Arrays (FPGAs), partial and run-time reconfigurable (RTR) FPGAs can selectively reconfigure partitions of its hardware almost immediately while it is still powered and operative. In this way, RTR FPGAs combine the flexibility of software with the high efficiency of hardware. However, their potential cannot be fully exploited due to the increased complexity of the design process, and the intricacy to generate partial reconfigurations. FPGAs are often seen as a single auxiliary area to accelerate algorithms for specific problems. However, when several RTR partitions are implemented and combined with a processor system, new opportunities and challenges appear due to the creation of a heterogeneous RTR embedded system-on-chip (SoC).The aim of this thesis is to investigate how the flexibility, reusability, and productivity in the design process of partial and RTR embedded SoCs can be improved to enable research and development of novel applications in areas such as hardware acceleration, dynamic fault-tolerance, self-healing, self-awareness, and self-adaptation. To address this question, this thesis proposes a solution based on modular reconfigurable IP-cores and design-and-reuse principles to reduce the design complexity and maximize the productivity of such FPGA-based SoCs. The research presented in this thesis found inspiration in several related topics and sciences such as reconfigurable computing, dependability and fault-tolerance, complex adaptive systems, bio-inspired hardware, organic and autonomic computing, psychology, and machine learning.The outcome of this thesis demonstrates that the proposed solution addressed the research question and enabled investigation in initially unexpected fields. The particular contributions of this thesis are: (1) the RecoBlock SoC concept and platform with its flexible and reusable array of RTR IP-cores, (2) a simplified method to transform complex algorithms modeled in Matlab into relocatable partial reconfigurations adapted to an improved RecoBlock IP-core architecture, (3) the self-healing RTR fault-tolerant (FT) schemes, especially the Upset-Fault-Observer (UFO) that reuse available RTR IP-cores to self-assemble hardware redundancy during runtime, (4) the concept of Cognitive Reconfigurable Hardware (CRH) that defines a development path to achieve self-adaptation and cognitive development, (5) an adaptive self-aware and fault-tolerant RTR SoC that learns to adapt the RTR FT schemes to performance goals under uncertainty using rule-based decision making, (6) a method based on online and model-free reinforcement learning that uses a Q-algorithm to self-optimize the activation of dynamic FT schemes in performance-aware RecoBlock SoCs.The vision of this thesis proposes a new class of self-adaptive and cognitive hardware systems consisting of arrays of modular RTR IP-cores. Such a system becomes self-aware of its internal performance and learns to self-optimize the decisions that trigger the adequate self-organization of these RTR cores, i.e., to create dynamic hardware redundancy and self-healing, particularly while working in uncertain environments.
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| 2. |
- Robino, Francesco, 1985-
(författare)
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A model-based design approach for heterogeneous NoC-based MPSoCs on FPGA
- 2014
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Network-on-chip (NoC) based multi-processor systems-on-chip (MPSoCs) are promising candidates for future multi-processor embedded platforms, which are expected to be composed of hundreds of heterogeneous processing elements (PEs) to potentially provide high performances. However, together with the performances, the systems complexity will increase, and new high level design techniques will be needed to efficiently model, simulate, debug and synthesize them. System-level design (SLD) is considered to be the next frontier in electronic design automation (EDA). It enables the description of embedded systems in terms of abstract functions and interconnected blocks. A promising complementary approach to SLD is the use of models of computation (MoCs) to formally describe the execution semantics of functions and blocks through a set of rules. However, also when this formalization is used, there is no clear way to synthesize system-level models into software (SW) and hardware (HW) towards a NoC-based MPSoC implementation, i.e., there is a lack of system design automation (SDA) techniques to rapidly synthesize and prototype system-level models onto heterogeneous NoC-based MPSoCs. In addition, many of the proposed solutions require large overhead in terms of SW components and memory requirements, resulting in complex and customized multi-processor platforms. In order to tackle the problem, a novel model-based SDA flow has been developed as part of the thesis. It starts from a system-level specification, where functions execute according to the synchronous MoC, and then it can rapidly prototype the system onto an FPGA configured as an heterogeneous NoC-based MPSoC. In the first part of the thesis the HeartBeat model is proposed as a model-based technique which fills the abstraction gap between the abstract system-level representation and its implementation on the multiprocessor prototype. Then details are provided to describe how this technique is automated to rapidly prototype the modeled system on a flexible platform, permitting to adjust the system specification until the designer is satisfied with the results. Finally, the proposed SDA technique is improved defining a methodology to automatically explore possible design alternatives for the modeled system to be implemented on a heterogeneous NoC-based MPSoC. The goal of the exploration is to find an implementation satisfying the designer's requirements, which can be integrated in the proposed SDA flow. Through the proposed SDA flow, the designer is relieved from implementation details and the design time of systems targeting heterogeneous NoC-based MPSoCs on FPGA is significantly reduced. In addition, it reduces possible design errors proposing a completely automated technique for fast prototyping. Compared to other SDA flows, the proposed technique targets a bare-metal solution, avoiding the use of an operating system (OS). This reduces the memory requirements on the FPGA platform comparing to related work targeting MPSoC on FPGA. At the same time, the performance (throughput) of the modeled applications can be increased when the number of processors of the target platform is increased. This is shown through a wide set of case studies implemented on FPGA.
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