Influence of parasitic capacitance variations on 65 nm and 32 nm predictive technology model SRAM core-cells

The continuous improving of CMOS technology allows the realization of digital circuits and in particular static random access memories that, compared with previous technologies, contain an impressive number of transistors. The use of new production processes introduces a set of parasitic effects that gain more and more importance with the scaling down of the technology. In particular, even small variations of parasitic capacitances in CMOS devices are expected to become an additional source of faulty behaviors in future technologies. This paper analyzes and compares the effect of parasitic capacitance variations in a SRAM memory circuit realized with 65 nm and 32 nm predictive technology model

Pose consensus based on dual quaternion algebra with application to decentralized formation control of mobile manipulators

This paper presents a solution based on dual quaternion algebra to the general problem of pose (i.e., position and orientation) consensus for systems composed of multiple rigid-bodies. The dual quaternion algebra is used to model the agents' poses and also in the distributed control laws, making the proposed technique easily applicable to time-varying formation control of general robotic systems. The proposed pose consensus protocol has guaranteed convergence when the interaction among the agents is represented by directed graphs with directed spanning trees, which is a more general result when compared to the literature on formation control. In order to illustrate the proposed pose consensus protocol and its extension to the problem of formation control, we present a numerical simulation with a large number of free-flying agents and also an application of cooperative manipulation by using real mobile manipulators

Using ER Models for Microprocessor Functional Test Coverage Evaluation

Test coverage evaluation is one of the most critical issues in microprocessor software-based testing. Whenever the test is developed in the absence of a structural model of the microprocessor, the evaluation of the final test coverage may become a major issue. In this paper, we present a microprocessor modeling technique based on entity-relationship diagrams allowing the definition and the computation of custom coverage functions. The proposed model is very flexible and particularly effective when a structural model of the microprocessor is not availabl

GPU cards as a low cost solution for efficient and fast classification of high dimensional gene expression datasets

The days when bioinformatics tools will be so reliable to become a standard aid in routine clinical diagnostics are getting very close. However, it is important to remember that the more complex and advanced bioinformatics tools become, the more performances are required by the computing platforms. Unfortunately, the cost of High Performance Computing (HPC) platforms is still prohibitive for both public and private medical practices. Therefore, to promote and facilitate the use of bioinformatics tools it is important to identify low-cost parallel computing solutions. This paper presents a successful experience in using the parallel processing capabilities of Graphical Processing Units (GPU) to speed up classification of gene expression profiles. Results show that using open source CUDA programming libraries allows to obtain a significant increase in performances and therefore to shorten the gap between advanced bioinformatics tools and real medical practic