Bit Steering In The Minimization Of Control Memory In Microprogrammed Digital-Computers

This correspondence presents an algorithm for microprogram control memory width minimization with the bit steering technique. The necessary and sufficient conditions to detect the steerability of two mutually exclusive sets of microcommands are established. The algorithm encodes the microcommands of the sets with a bit steering common part and also extends the theory to multiple (more than two) sets of microcommands.

Aerodynamic pressure variation over SMA wire integrated morphing aerofoil

An analysis of the pressure variation over an aerofoil with integrated Shape Memory Alloy (SMA) wire is reported. A computational model based on finite elements and potential flow computation is proposed to obtain the deflections of the upper and the lower skins of the aerofoil subjected to aerodynamic pressure and hysteretic deformation of the SMA wire. The computational model couples a one-dimensional phenomenological constitutive model of SMA wire with the laminar incompressible aerodynamic pressure induced deformation of the aerofoil skins. The SMA wires are actuated by thermoelectric control system with auxiliary compensator feeding the piezoelectric stack actuators to adjust the hysteretic dynamics of the SMA wire. At each step of this coupled deformation process, the deflected/morphed shape of the aerofoil is d while recalculating to get the pressure distribution. Panel method based on incompressible and inviscid flow is employed for this purpose. The aerodynamic lift is then obtained from the pressure distributions. Numerical results on the variation of coefficient of pressure are reported.

Scalable Context-Sensitive Points-To Analysis Using Multi-Dimensional Bloom Filters

Context-sensitive points-to analysis is critical for several program optimizations. However, as the number of contexts grows exponentially, storage requirements for the analysis increase tremendously for large programs, making the analysis non-scalable. We propose a scalable flow-insensitive context-sensitive inclusion-based points-to analysis that uses a specially designed multi-dimensional bloom filter to store the points-to information. Two key observations motivate our proposal: (i) points-to information (between pointer-object and between pointer-pointer) is sparse, and (ii) moving from an exact to an approximate representation of points-to information only leads to reduced precision without affecting correctness of the (may-points-to) analysis. By using an approximate representation a multi-dimensional bloom filter can significantly reduce the memory requirements with a probabilistic bound on loss in precision. Experimental evaluation on SPEC 2000 benchmarks and two large open source programs reveals that with an average storage requirement of 4MB, our approach achieves almost the same precision (98.6%) as the exact implementation. By increasing the average memory to 27MB, it achieves precision upto 99.7% for these benchmarks. Using Mod/Ref analysis as the client, we find that the client analysis is not affected that often even when there is some loss of precision in the points-to representation. We find that the NoModRef percentage is within 2% of the exact analysis while requiring 4MB (maximum 15MB) memory and less than 4 minutes on average for the points-to analysis. Another major advantage of our technique is that it allows to trade off precision for memory usage of the analysis.

Form, Content, and Magnetism in Iron Oxide Nanocrystals

Monodisperse iron oxide nanocrystals with spherical and cubic morphologies, of comparable dimensions, have been prepared by the thermal decomposition of FeOOH. The lattice spacings of both forms agree with that of magnetite, Fe(3)O(4). The two, however, exhibit very different blocking temperatures. Nanocrystals of cubic morphology are superparamagnetic above 190 K while the spherical nanocrystals at a lower temperature, 142 K. The higher blocking temperatures in particles of cubic morphology are shown to be a consequence of exchange bias fields. We show that in the present iron oxide nanocrystals the exchange bias fields originate from the presence of trace amounts of wustite, FeO. A Reitveld refinement analysis of the X-ray diffraction patterns shows that nanocrystals of cubic morphology have a higher FeO content. The higher FeO content is responsible for the larger exchange bias fields that in turn lead to a higher blocking temperature for nanocrystals with cubic morphology.

Fuzzy Clustering Based Ad Recommendation for TV Programs

Advertisements(Ads) are the main revenue earner for Television (TV) broadcasters. As TV reaches a large audience, it acts as the best media for advertisements of products and services. With the emergence of digital TV, it is important for the broadcasters to provide an intelligent service according to the various dimensions like program features, ad features, viewers’ interest and sponsors’ preference. We present an automatic ad recommendation algorithm that selects a set of ads by considering these dimensions and semantically match them with programs. Features of the ad video are captured interms of annotations and they are grouped into number of predefined semantic categories by using a categorization technique. Fuzzy categorical data clustering technique is applied on categorized data for selecting better suited ads for a particular program. Since the same ad can be recommended for more than one program depending upon multiple parameters, fuzzy clustering acts as the best suited method for ad recommendation. The relative fuzzy score called “degree of membership” calculated for each ad indicates the membership of a particular ad to different program clusters. Subjective evaluation of the algorithm is done by 10 different people and rated with a high success score.

MAX: A Multi Objective Memory Architecture eXploration Framework for Embedded Systems-on-Chip

Today's feature-rich multimedia products require embedded system solution with complex System-on-Chip (SoC) to meet market expectations of high performance at a low cost and lower energy consumption. The memory architecture of the embedded system strongly influences these parameters. Hence the embedded system designer performs a complete memory architecture exploration. This problem is a multi-objective optimization problem and can be tackled as a two-level optimization problem. The outer level explores various memory architecture while the inner level explores placement of data sections (data layout problem) to minimize memory stalls. Further, the designer would be interested in multiple optimal design points to address various market segments. However, tight time-to-market constraints enforces short design cycle time. In this paper we address the multi-level multi-objective memory architecture exploration problem through a combination of Multi-objective Genetic Algorithm (Memory Architecture exploration) and an efficient heuristic data placement algorithm. At the outer level the memory architecture exploration is done by picking memory modules directly from a ASIC memory Library. This helps in performing the memory architecture exploration in a integrated framework, where the memory allocation, memory exploration and data layout works in a tightly coupled way to yield optimal design points with respect to area, power and performance. We experimented our approach for 3 embedded applications and our approach explores several thousand memory architecture for each application, yielding a few hundred optimal design points in a few hours of computation time on a standard desktop.