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 －

High-performance CMOS variability in the 65-nm regime and beyond. IBM J Res And Dev

ion is the selection and (possibly) coarsening (i.e. quantisation) of certain system characteristics (attributes, performance indicators, parameters) from the total set of system characteristics. The abstraction process comprises: • A simplification (Example: The colour Red is an abstraction, which neglects the different possible shades of Red, the wavelengths, the intensity etc.), • an aggregation (Example: ‘Temperature’ condenses the myriad of individual molecule movements in a gas volume into a single number.), • and consequently: loss of information. The opposite of abstraction is concretisation. It comprises: • gain of information, • detailing, • refinement, • disaggregation, • in engineering: the design process. 3.2.2 System Boundary Systems are defined by their system boundary, which makes a distinction between inside and outside possible (i.e. between self and non-self, see Sect. 4.1). When 3.2 What is a System? 87 Fig. 3.3 Trade-off between initial development cost and later adaptation cost systems are designed, we must choose where to place the boundary. This involves a consideration of cost (Fig. 3.3): A narrow boundary will reduce the cost for planning and development in the first place but bears the risk of a high effort in case a subsequent adaptation and extension of the system should be necessary. A wide system boundary reverses the cost curves. Apparently, the total cost minimum lies somewhere in the middle. 3.2.3 Some System Types and Properties Most systems are transient, i.e. they change over time. They are developed, assembled, modified, destroyed. Reactive systems react on inputs (events, signals, sensor data) by applying outputs (events, control signals, commands) to the environment. All open systems are reactive! In a more focused definition: Only systems reacting in real time (within a predefined time) are reactive systems. Such real-time systems are characterised by (1) time restrictions (deadlines), and (2) time determinism (i.e. guarantees). Planned vs. Unplanned systems: During the development process of technical systems, only predictable events are taken into account in the designed core. But there will always be an unpredictable rest. Therefore, the ‘spontaneous closure’ (Fig. 3.4) has to cover these events. In technical systems, the exception handler or the diagnosis system play the role of a simple spontaneous closure. Living systems are characterised by a powerful spontaneous closure. Recurring reactions of the spontaneous closure become part of the designed core. This amounts to learning.

Organic Computing – Technical Systems for Survival in the Real World

The convergence and divergence are two common phenomena in swarm intelligence. To obtain good search results, the algorithm should have a balance on convergence and divergence. The premature convergence happens partially due to the solutions getting clustered together, and not diverging again. The brain storm optimization (BSO), which is a young and promising algorithm in swarm intelligence, is based on the collective behavior of human being, that is, the brainstorming process. The convergence strategy is utilized in BSO algorithm to exploit search areas may contain good solutions. The new solutions are generated by divergence strategy to explore new search areas. Premature convergence also happens in the BSO algorithm. The solutions get clustered after a few iterations, which indicate that the population diversity decreases quickly during the search. A definition of population diversity in BSO algorithm is introduced in this paper to measure the change of solutions’ distribution. The algorithm’s exploration and exploitation ability can be measured based on the change of population diversity. Different kinds of partial reinitialization strategies are utilized to improve the population diversity in BSO algorithm. The experimental results show that the performance of the BSO is improved by part of solutions re-initialization strategies.

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Population Diversity Maintenance In Brain Storm Optimization Algorithm

Organic computing systems are systems which have the capability to autonomously (re-)organize and adapt themselves. The benefit of such systems with self-x properties is that they are more dependable, as they can compensate for some failures. They are easier to maintain, because they can automatically configure themselves and are more convenient to use because of automatic adaptation to new situations. While organic computing systems have a lot of desired properties, there still exists only little knowledge on how they can be designed and built.In this paper an approach for specification and construction of a class of organic computing systems is presented, called the (RIA). The core idea is that the behaviour of an organic computing system can be split into productive phases and self-x phases. This allows for a generic description of how ``organic'' aspects can be specified and implemented. The approach will be illustrated by applying it to a design methodology for organic computing systems and further refining it to an explicit case study in the domain of production automation.

A Specification and Construction Paradigm for Organic Computing Systems

The ongoing scaling of CMOS technology facilitates the design of systems with continuously increasing functionality but also raises the susceptibility of these systems to reliability issues. These can for example be caused by high power densities and temperatures. At the moment it is still possible to cope with the posed challenges in an affordable manner. But in the future, a combination of design and run-time measures will become necessary in order to guarantee that reliability guidelines are met. Because of complexity reasons, the Electronic System Level (ESL) is gaining importance as starting point of design. Design alternatives are evaluated at ESL with respect to several design objectives, lately also including reliability. In this paper, the most important phenomena threatening the reliability are introduced and the current status of related research work and tools is presented. After that, a high level design space exploration considering performance, energy and reliability trade-offs in multi-core systems is introduced. Finally, it is shown how reliability can be further improved during run-time by the application of a machine learning system.

Design and Run-time Reliability at the Electronic System Level (IPSJ Transactions on System LSI Design Methodology Vol.3)

With the increasing power density of deep submicron technology, temperature becomes one of the dominating factors for the reliability of integrated circuits. Coarse-grained reconfigurable devices typically exhibit spatially nonuniform activity, which results in areas of localized heating, so called hot spots. In this work we investigate the effects of continuous activity migration in order to prevent hot spots. By applying activity migration we are able to reduce temporal and spatial variations of temperature by up to 87%.

Prevention of Hot Spot Development on Coarse-Grained Dynamically Reconfigurable Architectures

In this article we present a novel two-stage method to realise a lightweight but very capable hardware implementation of a Learning Classifier System for on-chip learning. Learning Classifier Systems (LCS) allow taking good run-time decisions, but current hardware implementations are either large or have limited learning capabilities.

Combining Software and Hardware LCS for Lightweight On-chip Learning.

This work-in-progress paper surveys error detection techniques for transient, timing, permanent and logical errors in system-on-chip (SoC) design and discusses their applicability in the design of monitors for our Autonomic SoC architecture framework. These monitors will be needed to deliver necessary signals to achieve fault-tolerance, self-healing and self-calibration in our Autonomic SoC architecture. The framework combines the monitors with a well-tailored design methodology that explores how the Autonomic SoC (ASoC) can cope with malfunctioning subcomponents.

Andreas Bernauer

Papers

Design and Run-time Reliability at the Electronic System Level (IPSJ Transactions on System LSI Design Methodology Vol.3)

Prevention of Hot Spot Development on Coarse-Grained Dynamically Reconfigurable Architectures

Combining Software and Hardware LCS for Lightweight On-chip Learning.

Error Detection Techniques Applicable in an Architecture Framework and Design Methodology for Autonomic SoC