Partial Reconfiguration in the Field of Logic Controllers Design

The paper presents method for logic controllers multi context implementation by means of partial reconfiguration. The UML state machine diagram specifies the behaviour of the logic controller. Multi context functionality is specified at the specification level as variants of the composite state. Each composite state, both orthogonal or compositional, describes specific functional requirement of the control process. The functional decomposition provided by composite states is required by the dynamic partial reconfiguration flow. The state machines specified by UML state machine diagrams are transformed into hierarchical configurable Petri nets (HCfgPN). HCfgPN are a Petri nets variant with the direct support of the exceptions handling mechanism. The paper presents placesoriented method for HCfgPN description in Verilog language. In the paper proposed methodology was illustrated by means of simple industrial control process

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

Models for Co-Design of Heterogeneous Dynamically Reconfigurable SoCs

International audienceThe design of Systems-on-Chip is becoming an increasing difficult challenge due to the continuous exponential evolution of the targeted complex architectures and applications. Thus, seamless methodologies and tools are required to resolve the SoC design issues. This chapter presents a high level component based approach for expressing system reconfigurability in SoC co-design. A generic model of reactive control is presented for Gaspard2, a SoC co-design framework. Control integration in different levels of the framework is explored along with a comparison of their advantages and disadvantages. Afterwards, control integration at another high abstraction level is investigated which proves to be more beneficial then the other alternatives. This integration allows to integrate reconfigurability features in modern SoCs. Finally a case study is presented for validation purposes. The presented works are based on Model-Driven Engineering (MDE) and UML MARTE profile for modeling and analysis of real-time embedded systems

Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

Structured Mapping of Petri Net States and Events for FPGA Implementations

The paper presents a new method of structured encoding of global internal states and events in Reconfigurable Logic Controllers, which are directly mapped into Field Programmable Gate Arrays (FPGA). Modular, concurrently decomposed, colored state machine is chosen as a intermediate model, before the mapping of Petri net into an array structure of dedicated but very flexible and reliable digital system. The initial textual specification in formal Gentzen logic serves both as a design description for a rapid prototyping, as well as formal model, suitable for detailed computer-based reasoning about optimized and synthesized logic controller, implemented in configurable hardware. Only the selected linear subset from general, universal propositional Gentzen Logic is necessary to deduce several properties of the net, such as relations of nonconcurrency among structurally ordered macroplaces. The goal of this paper is to present the design methodology for modeling and synthesis of discrete controllers using related Petri net theory, rule-based theory (mathematical logic), and VHDL

TANGO: Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation

The paper is concerned with the issue of how software systems actually use Heterogeneous Parallel Architectures (HPAs), with the goal of optimizing power consumption on these resources. It argues the need for novel methods and tools to support software developers aiming to optimise power consumption resulting from designing, developing, deploying and running software on HPAs, while maintaining other quality aspects of software to adequate and agreed levels. To do so, a reference architecture to support energy efficiency at application construction, deployment, and operation is discussed, as well as its implementation and evaluation plans.Comment: Part of the Program Transformation for Programmability in Heterogeneous Architectures (PROHA) workshop, Barcelona, Spain, 12th March 2016, 7 pages, LaTeX, 3 PNG figure

Hardware synthesis from high-level scenario specifications

PhD ThesisThe behaviour of many systems can be partitioned into scenarios. These facilitate engineers’ understanding of the specifications, and can be composed into efficient implementations via a form of high-level synthesis. In this work, we focus on highly concurrent systems, whose scenarios are typically described using concurrency models such as partial orders, Petri nets and data-flow structures. In this thesis, we study different aspects of hardware synthesis from high-level scenario specifications. We propose new formal models to simplify the specification of concurrent systems, and algorithms for hardware synthesis and verification of the scenario-based models of such systems. We also propose solutions for mapping scenariobased systems on silicon and evaluate their efficiency. Our experiments show that the proposed approaches improve the design of concurrent systems. The new formalisms can break down complex specifications into significantly simpler scenarios automatically, and can be used to fully model the dataflow of operations of reconfigurable event-driven systems. The proposed heuristics for mapping the scenarios of a system to a digital circuit supports encoding constraints, unlike existing methods, and can cope with specifications comprising hundreds of scenarios at the cost of only 5% of area overhead compared to exact algorithms. These experiments are driven by three case studies: (1) hardware synthesis of control architectures, e.g. microprocessor control units; (2) acceleration of the ordinal pattern encoding, i.e. an algorithm for detecting repetitive patterns within data streams; (3) and acceleration of computational drug discovery, i.e. computation of shortest paths in large protein-interaction networks. Our findings are employed to design two prototypes, which have a practical value for the considered case studies. The ordinal pattern encoding accelerator is asynchronous, highly resilient to unstable voltage supply, and designed to perform a range of computations via runtime reconfiguration. The drug discovery accelerator is synchronous, and up to three orders of magnitude faster than conventional software implementations