On mixed abstraction, languages and simulation approach to refinement with SystemC AMS

Executable specifications and simulations arecornerstone to system design flows. Complex mixed signalembedded systems can be specified with SystemC AMSwhich supports abstraction and extensible models of computation. The language contains semantics for moduleconnections and synchronization required in analog anddigital interaction. Through the synchronization layer, user defined models of computation, solvers and simulators can be unified in the SystemC AMS simulator for achieving low level abstraction and model refinement. These improvements assist in amplifying model aspects and their contribution to the overall system behavior. This work presents cosimulating refined models with timed data flow paradigm of SystemC AMS. The methodology uses Cbased interaction between simulators. An RTL model ofdata encryption standard is demonstrated as an example.The methodology is flexible and can be applied in earlydesign decision trade off, architecture experimentation and particularly for model refinement and critical behavior analysis

A design methodology for soft-core platforms on FPGA with SMP Linux, OpenMP support, and distributed hardware profiling system

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Adaptive Knobs for Resource Efficient Computing

Performance demands of emerging domains such as artificial intelligence, machine learning and vision, Internet-of-things etc., continue to grow. Meeting such requirements on modern multi/many core systems with higher power densities, fixed power and energy budgets, and thermal constraints exacerbates the run-time management challenge. This leaves an open problem on extracting the required performance within the power and energy limits, while also ensuring thermal safety. Existing architectural solutions including asymmetric and heterogeneous cores and custom acceleration improve performance-per-watt in specific design time and static scenarios. However, satisfying applications’ performance requirements under dynamic and unknown workload scenarios subject to varying system dynamics of power, temperature and energy requires intelligent run-time management. Adaptive strategies are necessary for maximizing resource efficiency, considering i) diverse requirements and characteristics of concurrent applications, ii) dynamic workload variation, iii) core-level heterogeneity and iv) power, thermal and energy constraints. This dissertation proposes such adaptive techniques for efficient run-time resource management to maximize performance within fixed budgets under unknown and dynamic workload scenarios. Resource management strategies proposed in this dissertation comprehensively consider application and workload characteristics and variable effect of power actuation on performance for pro-active and appropriate allocation decisions. Specific contributions include i) run-time mapping approach to improve power budgets for higher throughput, ii) thermal aware performance boosting for efficient utilization of power budget and higher performance, iii) approximation as a run-time knob exploiting accuracy performance trade-offs for maximizing performance under power caps at minimal loss of accuracy and iv) co-ordinated approximation for heterogeneous systems through joint actuation of dynamic approximation and power knobs for performance guarantees with minimal power consumption. The approaches presented in this dissertation focus on adapting existing mapping techniques, performance boosting strategies, software and dynamic approximations to meet the performance requirements, simultaneously considering system constraints. The proposed strategies are compared against relevant state-of-the-art run-time management frameworks to qualitatively evaluate their efficacy

Actor-Oriented Programming for Resource Constrained Multiprocessor Networks on Chip

Multiprocessor Networks on Chip (MPNoCs) are an attractive architecture for integrated circuits as they can benefit from the improved performance of ever smaller transistors but are not severely constrained by the poor performance of global on-chip wires. As the number of processors increases it becomes ever more expensive to provide coherent shared memory but this is a foundational assumption of thread-level parallelism. Threaded models of concurrency cannot efficiently address architectures where shared memory is not coherent or does not exist. In this thesis an extended actor oriented programming model is proposed to enable the design of complex and general purpose software for highly parallel and decentralised multiprocessor architectures. This model requires the encapsulation of an execution context and state into isolated Machines which may only initiate communication with one another via explicitly named channels. An emphasis on message passing and strong isolation of computation encourages application structures that are congruent with the nature of non-shared memory multiprocessors, and the model also avoids creating dependences on specific hardware topologies. A realisation of the model called Machine Java is presented to demonstrate the applicability of the model to a general purpose programming language. Applications designed with this framework are shown to be capable of scaling to large numbers of processors and remain independent of the hardware targets. Through the use of an efficient compilation technique, Machine Java is demonstrated to be portable across several architectures and viable even in the highly constrained context of an FPGA hosted MPNoC

The Proceedings of the 23rd Annual International Conference on Digital Government Research (DGO2022) Intelligent Technologies, Governments and Citizens June 15-17, 2022

The 23rd Annual International Conference on Digital Government Research theme is “Intelligent Technologies, Governments and Citizens”. Data and computational algorithms make systems smarter, but should result in smarter government and citizens. Intelligence and smartness affect all kinds of public values - such as fairness, inclusion, equity, transparency, privacy, security, trust, etc., and is not well-understood. These technologies provide immense opportunities and should be used in the light of public values. Society and technology co-evolve and we are looking for new ways to balance between them. Specifically, the conference aims to advance research and practice in this field. The keynotes, presentations, posters and workshops show that the conference theme is very well-chosen and more actual than ever. The challenges posed by new technology have underscored the need to grasp the potential. Digital government brings into focus the realization of public values to improve our society at all levels of government. The conference again shows the importance of the digital government society, which brings together scholars in this field. Dg.o 2022 is fully online and enables to connect to scholars and practitioners around the globe and facilitate global conversations and exchanges via the use of digital technologies. This conference is primarily a live conference for full engagement, keynotes, presentations of research papers, workshops, panels and posters and provides engaging exchange throughout the entire duration of the conference

GSI Scientific Report 2016

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