The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

International Technology Roadmap for Semiconductors 2003の要求清浄度について － シリコンウエハ表面と雰囲気環境に要求される清浄度, 分析方法の現状について －

Hawaii International Conference on System Sciences

Is your memory hierarchy stopping your microprocessor from performing at the high level it should be? Memory Systems: Cache, DRAM, Disk shows you how to resolve this problem. The book tells you everything you need to know about the logical design and operation, physical design and operation, performance characteristics and resulting design trade-offs, and the energy consumption of modern memory hierarchies. You learn how to to tackle the challenging optimization problems that result from the side-effects that can appear at any point in the entire hierarchy.As a result you will be able to design and emulate the entire memory hierarchy. . Understand all levels of the system hierarchy -Xcache, DRAM, and disk. . Evaluate the system-level effects of all design choices. . Model performance and energy consumption for each component in the memory hierarchy.

Memory Systems: Cache, DRAM, Disk

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well as solve challenging machine learning problems The promise of the technology is to create a brain-like ability to learn and adapt, but the technical challenges are significant, starting with an accurate neuroscience model of how the brain works, to finding materials and engineering breakthroughs to build devices to support these models, to creating a programming framework so the systems can learn, to creating applications with brain-like capabilities In this work, we provide a comprehensive survey of the research and motivations for neuromorphic computing over its history We begin with a 35-year review of the motivations and drivers of neuromorphic computing, then look at the major research areas of the field, which we define as neuro-inspired models, algorithms and learning approaches, hardware and devices, supporting systems, and finally applications We conclude with a broad discussion on the major research topics that need to be addressed in the coming years to see the promise of neuromorphic computing fulfilled The goals of this work are to provide an exhaustive review of the research conducted in neuromorphic computing since the inception of the term, and to motivate further work by illuminating gaps in the field where new research is needed

A Survey of Neuromorphic Computing and Neural Networks in Hardware.

A DAG-based design approach for reconfigurable VLIW processors

The need for low-power embedded systems has become very significant within the microelectronics scenario in the most recent years. A power-driven methodology is mandatory during embedded systems design to meet system-level requirements while fulfilling time-to-market. The aim of this paper is to introduce accurate and efficient power metrics included in a hardware/software (HW/SW) codesign environment to guide the system-level partitioning. Power evaluation metrics have been defined to widely explore the architectural design space at high abstraction level. This is one of the first approaches that considers globally HW and SW contributions to power in a system-level design flow for control dominated embedded systems.

Power estimation of embedded systems: a hardware/software codesign approach

In this paper a comprehensive methodology for software execution time estimation is presented. The methodology is supported by rigorous mathematical models of C statements in terms of elementary operations. The deterministic contribution is combined with a statistical term accounting for all those aspects that cannot be quantified exactly. The methodology has been validated by realizing a complete prototype toolset, used to carry out the experiments.

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Source-level execution time estimation of C programs

The paper aims at defining a methodology for the optimization of the switching power related to the processor-to memory communication on system-level buses. First, a methodology to profile the switching activity related to system-level buses has been defined, based on the tracing of benchmark programs running on the Sun SPARC V8 architecture. The bus traces have been analyzed to identify temporal correlations between consecutive patterns. Second, a framework has been set up for the design of high-performance encoder/decoder architectures to reduce the transition activity of the system-level buses. Novel bus encoding schemes have been proposed, whose performance has been compared with the most widely adopted power-oriented encodings. The experimental results have shown that the proposed encoding techniques provide an average reduction in transition activity up to 74.11% over binary encoding for instruction address streams. The results indicate the suitability of the proposed techniques for high-capacitance wide buses, for which the power saving due to the transition activity reduction is not offset by the extra power dissipation introduced in the system by the encoding/decoding logic.

Power optimization of system-level address buses based on software profiling

This paper presents a parametric area estimation methodology at SystemC level for FPGA-based designs. The approach is conceived to reduce the effort to adapt the area estimators to the evolutions of the EDA design environments. It consists in identifying the subset of measures that can be derived form the system level description and that are also relevant at VHDL-RT level. Estimators' parameters are then automatically derived from a set of benchmarks.

William Fornaciari

Papers

A DAG-based design approach for reconfigurable VLIW processors

Power estimation of embedded systems: a hardware/software codesign approach

Source-level execution time estimation of C programs

Power optimization of system-level address buses based on software profiling

An area estimation methodology for FPGA based designs at systemc-level