Memory Hierarchy Hardware-Software Co-design in Embedded Systems

The memory hierarchy is the main bottleneck in modern computer systems as the gap between the speed of the processor and the memory continues to grow larger. The situation in embedded systems is even worse. The memory hierarchy consumes a large amount of chip area and energy, which are precious resources in embedded systems. Moreover, embedded systems have multiple design objectives such as performance, energy consumption, and area, etc. Customizing the memory hierarchy for specific applications is a very important way to take full advantage of limited resources to maximize the performance. However, the traditional custom memory hierarchy design methodologies are phase-ordered. They separate the application optimization from the memory hierarchy architecture design, which tend to result in local-optimal solutions. In traditional Hardware-Software co-design methodologies, much of the work has focused on utilizing reconfigurable logic to partition the computation. However, utilizing reconfigurable logic to perform the memory hierarchy design is seldom addressed. In this paper, we propose a new framework for designing memory hierarchy for embedded systems. The framework will take advantage of the flexible reconfigurable logic to customize the memory hierarchy for specific applications. It combines the application optimization and memory hierarchy design together to obtain a global-optimal solution. Using the framework, we performed a case study to design a new software-controlled instruction memory that showed promising potential.

Disentangling multi-level systems: averaging, correlations and memory

We consider two weakly coupled systems and adopt a perturbative approach based on the Ruelle response theory to study their interaction. We propose a systematic way of parameterizing the effect of the coupling as a function of only the variables of a system of interest. Our focus is on describing the impacts of the coupling on the long term statistics rather than on the finite-time behavior. By direct calculation, we find that, at first order, the coupling can be surrogated by adding a deterministic perturbation to the autonomous dynamics of the system of interest. At second order, there are additionally two separate and very different contributions. One is a term taking into account the second-order contributions of the fluctuations in the coupling, which can be parameterized as a stochastic forcing with given spectral properties. The other one is a memory term, coupling the system of interest to its previous history, through the correlations of the second system. If these correlations are known, this effect can be implemented as a perturbation with memory on the single system. In order to treat this case, we present an extension to Ruelle's response theory able to deal with integral operators. We discuss our results in the context of other methods previously proposed for disentangling the dynamics of two coupled systems. We emphasize that our results do not rely on assuming a time scale separation, and, if such a separation exists, can be used equally well to study the statistics of the slow variables and that of the fast variables. By recursively applying the technique proposed here, we can treat the general case of multi-level systems.

Analysis of slow- and fast-alpha band asymmetry during performance of a saccadic eye movement task: Dissociation between memory- and attention-driven systems

This study aimed at analyzing the relationship between slow- and fast-alpha asymmetry within frontal cortex and the planning, execution and voluntary control of saccadic eye movements (SEM), and quantitative electroencephalography (qEEG) was recorded using a 20-channel EEG system in 12 healthy participants performing a fixed (i.e., memory-driven) and a random SEM (i.e., stimulus-driven) condition. We find main effects for SEM condition in slow- and fast-alpha asymmetry at electrodes F3-F4, which are located over premotor cortex, specifically a negative asymmetry between conditions. When analyzing electrodes F7-F8, which are located over prefrontal cortex, we found a main effect for condition in slow-alpha asymmetry, particularly a positive asymmetry between conditions. In conclusion, the present approach supports the association of slow- and fast-alpha bands with the planning and preparation of SEM, and the specific role of these sub-bands for both, the attention network and the coordination and integration of sensory information with a (oculo)-motor response. (C) 2011 Elsevier B.V. All rights reserved.

Memory isolation in many-core embedded systems

The current approach to developing mixed-criticality sys- tems is by partitioning the hardware resources (processors, memory and I/O devices) among the different applications. Partitions are isolated from each other both in the temporal and the spatial domain, so that low-criticality applications cannot compromise other applications with a higher level of criticality in case of misbehaviour. New architectures based on many-core processors open the way to highly parallel systems in which each partition can be allocated to a set of dedicated proces- sor cores, thus simplifying partition scheduling and temporal separation. Moreover, spatial isolation can also benefit from many-core architectures, by using simpler hardware mechanisms to protect the address spaces of different applications. This paper describes an architecture for many- core embedded partitioned systems, together with some implementation advice for spatial isolation.

Involvement of the amygdala in memory storage: Interaction with other brain systems

There is extensive evidence that the amygdala is involved in affectively influenced memory. The central hypothesis guiding the research reviewed in this paper is that emotional arousal activates the amygdala and that such activation results in the modulation of memory storage occurring in other brain regions. Several lines of evidence support this view. First, the effects of stress-related hormones (epinephrine and glucocorticoids) are mediated by influences involving the amygdala. In rats, lesions of the amygdala and the stria terminalis block the effects of posttraining administration of epinephrine and glucocorticoids on memory. Furthermore, memory is enhanced by posttraining intra-amygdala infusions of drugs that activate β-adrenergic and glucocorticoid receptors. Additionally, infusion of β-adrenergic blockers into the amygdala blocks the memory-modulating effects of epinephrine and glucocorticoids, as well as those of drugs affecting opiate and GABAergic systems. Second, an intact amygdala is not required for expression of retention. Inactivation of the amygdala prior to retention testing (by posttraining lesions or drug infusions) does not block retention performance. Third, findings of studies using human subjects are consistent with those of animal experiments. β-Blockers and amygdala lesions attenuate the effects of emotional arousal on memory. Additionally, 3-week recall of emotional material is highly correlated with positron-emission tomography activation (cerebral glucose metabolism) of the right amygdala during encoding. These findings provide strong evidence supporting the hypothesis that the amygdala is involved in modulating long-term memory storage.

Evaluation and measurement of multiprocessor systems with shared memory

This study is concerned with several proposals concerning multiprocessor systems and with the various possible methods of evaluating such proposals. After a discussion of the advantages and disadvantages of several performance evaluation tools, the author decides that simulation is the only tool powerful enough to develop a model which would be of practical use, in the design, comparison and extension of systems. The main aims of the simulation package developed as part of this study are cost effectiveness, ease of use and generality. The methodology on which the simulation package is based is described in detail. The fundamental principles are that model design should reflect actual systems design, that measuring procedures should be carried out alongside design that models should be well documented and easily adaptable and that models should be dynamic. The simulation package itself is modular, and in this way reflects current design trends. This approach also aids documentation and ensures that the model is easily adaptable. It contains a skeleton structure and a library of segments which can be added to or directly swapped with segments of the skeleton structure, to form a model which fits a user's requirements. The study also contains the results of some experimental work carried out using the model, the first part of which tests• the model's capabilities by simulating a large operating system, the ICL George 3 system; the second part deals with general questions and some of the many proposals concerning multiprocessor systems.

Intelligent Systems Memory Structuring

The requirements for the memory structuring of intelligent systems are discussed. Simultaneously with the introduction of information into memory there should take place the processes of association links (bonds) formation, hierarchy systematizing, classification and concept formation. The growing pyramidal networks (GPN) meet these requirements. Many years of experience of GPN application for data analyses in chemistry and material studies proves their sufficiently high potential.

Memory effects and geometrical considerations in open quantum systems

This thesis discusses memory effects in open quantum systems with an emphasis on the Breuer, Laine, Piilo (BLP) measure of non-Markovianity. It is shown how the calculation of the measure can be simplifed and how quantum information protocols can bene t from memory e ects. The superdense coding protocol is used as an example of this. The quantum Zeno effect will also be studied from the point of view of memory e ects. Finally the geometric ideas used in simplifying the calculation of the BLP measure are applied in studying the amount of resources needed for detecting bipartite quantum correlations. It is shown that to decide without prior information if an unknown quantum state is entangled or not, an informationally complete measurement is required. The first part of the thesis contains an introduction to the theoretical ideas such as quantum states, closed and open quantum systems and necessary mathematical tools. The theory is then applied in the second part of the thesis as the results obtained in the original publications I-VI are presented and discussed.

Mesh partitioning and load balancing for distributed memory parallel systems

A method is outlined for optimising graph partitions which arise in mapping unstructured mesh calculations to parallel computers. The method employs a relative gain iterative technique to both evenly balance the workload and minimise the number and volume of interprocessor communications. A parallel graph reduction technique is also briefly described and can be used to give a global perspective to the optimisation. The algorithms work efficiently in parallel as well as sequentially and when combined with a fast direct partitioning technique (such as the Greedy algorithm) to give an initial partition, the resulting two-stage process proves itself to be both a powerful and flexible solution to the static graph-partitioning problem. Experiments indicate that the resulting parallel code can provide high quality partitions, independent of the initial partition, within a few seconds. The algorithms can also be used for dynamic load-balancing, reusing existing partitions and in this case the procedures are much faster than static techniques, provide partitions of similar or higher quality and, in comparison, involve the migration of a fraction of the data.

Crossover between the extended and localized regimes in stochastic partially self-avoiding walks in one-dimensional disordered systems

Consider N sites randomly and uniformly distributed in a d-dimensional hypercube. A walker explores this disordered medium going to the nearest site, which has not been visited in the last mu (memory) steps. The walker trajectory is composed of a transient part and a periodic part (cycle). For one-dimensional systems, travelers can or cannot explore all available space, giving rise to a crossover between localized and extended regimes at the critical memory mu(1) = log(2) N. The deterministic rule can be softened to consider more realistic situations with the inclusion of a stochastic parameter T (temperature). In this case, the walker movement is driven by a probability density function parameterized by T and a cost function. The cost function increases as the distance between two sites and favors hops to closer sites. As the temperature increases, the walker can escape from cycles that are reminiscent of the deterministic nature and extend the exploration. Here, we report an analytical model and numerical studies of the influence of the temperature and the critical memory in the exploration of one-dimensional disordered systems.

Modeling, control and experimental validation of a novel actuator based on shape memory alloys

The paper presents the development of a mechanical actuator using a shape memory alloy with a cooling system based on the thermoelectric effect (Seebeck-Peltier effect). Such a method has the advantage of reduced weight and requires a simpler control strategy as compared to other forced cooling systems. A complete mathematical model of the actuator was derived, and an experimental prototype was implemented. Several experiments are used to validate the model and to identify all parameters. A robust and nonlinear controller, based on sliding-mode theory, was derived and implemented. Experiments were used to evaluate the actuator closed-loop performance, stability, and robustness properties. The results showed that the proposed cooling system and controller are able to improve the dynamic response of the actuator. (C) 2009 Elsevier Ltd. All rights reserved.

On Building a Memory Evolutive System for Application to Learning and Cognition Modeling

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.