Dynamic-CoMPI: dynamic optimization techniques for MPI parallel applications

This work presents an optimization of MPI communications, called Dynamic-CoMPI, which uses two techniques in order to reduce the impact of communications and non-contiguous I/O requests in parallel applications. These techniques are independent of the application and complementaries to each other. The first technique is an optimization of the Two-Phase collective I/O technique from ROMIO, called Locality aware strategy for Two-Phase I/O (LA-Two-Phase I/O). In order to increase the locality of the file accesses, LA-Two-Phase I/O employs the Linear Assignment Problem (LAP) for finding an optimal I/O data communication schedule. The main purpose of this technique is the reduction of the number of communications involved in the I/O collective operation. The second technique, called Adaptive-CoMPI, is based on run-time compression of MPI messages exchanged by applications. Both techniques can be applied on every application, because both of them are transparent for the users. Dynamic-CoMPI has been validated by using several MPI benchmarks and real HPC applications. The results show that, for many of the considered scenarios, important reductions in the execution time are achieved by reducing the size and the number of the messages. Additional benefits of our approach are the reduction of the total communication time and the network contention, thus enhancing, not only performance, but also scalability.     

Robust design of nonlinear internal models without adaptation

We propose a solution to the problem of semiglobal output regulation for nonlinear minimum-phase systems driven by uncertain exosystems that does not rely upon conventional adaptation schemes to estimate the frequency of the exogenous signals. Rather, the proposed approach relies upon regression-like arguments used to derive a nonlinear internal model able to offset the presence of an unknown number of harmonic exogenous inputs of uncertain amplitude, phase and frequency. The design methodology guarantees asymptotic regulation if the dimension of the regulator exceeds a lower bound determined by the actual number of harmonic components of the exogenous input. If this is not the case, a bounded steady-state regulation error is ensured whose amplitude, though, can be arbitrarily decreased by acting on a design parameter of the regulator.     

Petri net-based engine for adaptive learning

In this paper, an IMS LD engine based on a Petri net model that represents the operational semantics of units of learning based on this specification is presented. The Petri nets of this engine, which is called OPENET4LD, verify the structural properties that are desirable for a learning flow and also facilitate the adaptation of the engine if potential changes in the IMS LD specification were proposed. Furthermore, OPENET4LD has an open and flexible architecture based on a set of ontologies that describe both the semantics of the Petri nets execution and the semantics of each learning flow component of IMS LD. Furthermore, the implementation of this architecture has been exhaustively validated with a number of UoLs that are compliant with the levels A and B of IMS LD.     

Cracks and re-entrant corners in functionally graded materials

Functionally graded materials (FGMs) are special composites in which the volume fractions of constituent materials vary gradually, giving continuously graded mechanical properties. The aim of this paper is the evaluation of the strength of structures composed by FGMs incorporating re-entrant corners - tending to the more common crack for vanishing corner angle. The end result is useful in engineering applications predicting the strength of the element corresponding to the unstable brittle crack propagation in such innovative materials. To show the general validity of the method, heterogeneous plates under tension and beam under bending containing re-entrant corners and by varying corner angle, depth and grading of the FGM are considered. Ad hoc performed numerical finite element simulations, by using the FRANC2D code, agree with the theoretical predictions.     

Model of Precipitation Kinetics Induced by Strain for Microalloyed Steels

In microalloyed steels, static recrystallisation is temporarily inhibited by precipitation which is occurring at the same time. A high number of microalloyed steels containing various combinations of carbon, nitrogen and precipitate forming elements like V, Nb and Ti were recrystallised at different temperatures and strain rates. From these results recrystallisation‐precipitation–time‐temperature (RPTT) diagrams were established. The influence of grain size and strain rate on the RPTT diagrams was studied. The precipitation kinetics were mathematically described for isothermal conditions and converted to cooling conditions, which enables an application to hot rolling. Under cooling conditions, completion of recrystallisation is prevented, especially for Nb alloyed steels.     

Design and Calibration of an Opto-mechanical Appliance for 3D Non-contact Orthopedic Measurements Part II: Calibration Methodology and Experimental Results

A multistep iterative calibration methodology for the opto-mechanical system introduced in Part I is proposed. The methodology makes use of a monoview coplanar set of control points, whose number has been determined on the basis of both geometrical considerations and the results of a statistical analysis aiming at assessing the procedure stability in the case of noisy image data. The calibration procedure is carried out comparing the theoretical and observed images of the calibration pattern. Both synthetic and real data have been employed to test the calibration procedure, which proved to be accurate and efficient. The experimental results achieved by the calibrated system are satisfactory in terms of measurement precision.     

A random set approach to the optimization of uncertain structures

The single-objective optimization of structures, whose parameters are assigned as fuzzy numbers or fuzzy relations, is presented in this paper as a particular case of the random set theory and evidence theory approach to uncertainty. Some basic concepts concerning these theories are reviewed and the relationships among interval analysis, convex modeling, possibility theory and probability theory are pointed out. In this context a frequentistic view of fuzzy sets makes sense and it is possible to calculate bounds on the probability that the solution satisfies the constraints. Some special but useful cases illustrate in detail the meaning of the approach proposed and its links with a recent formulation conceived within the context of convex modeling. Some theorems allow a very efficient computational procedure to be set up in many real design situations. Two numerical examples illustrate the model presented.     

Merging Results for Distributed Content Based Image Retrieval

Searching information through the Internet often requires users to separately contact several digital libraries, use each library interface to author the query, analyze retrieval results and merge them with results returned by other libraries. Such a solution could be simplified by using a centralized server that acts as a gateway between the user and several distributed repositories: The centralized server receives the user query, forwards the user query to federated repositories—possibly translating the query in the specific format required by each repository—and fuses retrieved documents for presentation to the user. To accomplish these tasks efficiently, the centralized server should perform some major operations such as: resource selection, query transformation and data fusion. In this paper we report on some aspects of MIND, a system for managing distributed, heterogeneous multimedia libraries (MIND, 2001, http://www.mind-project.org). In particular, this paper focusses on the issue of fusing results returned by different image repositories. The proposed approach is based on normalization of matching scores assigned to retrieved images by individual libraries. Experimental results on a prototype system show the potential of the proposed approach with respect to traditional solutions.