Investigation of the reliability and longevity of parallel systems with defects using Daniels’ sequences

The Reliability and longevity of parallel systems is studied using the example of a fibrous composite material using Daniels sequences’ and the Markov chain theory. The connection between the strength distribution function of the separate longitudinal elements forming the parallel system and the longevity distribution function of this system under cyclic loads is analyzed. The obtained models do not give direct coincidence with the experimental data but can be used for their nonlinear regressive analysis. Numerical experimental data processing examples are given.     

A parallel O(log n) algorithm for the drawing of algebraic curves in an n × n square

A parallel O(log n) algorithm for the drawing of algebraic curves in the digital plane is described. The algorithm contains a systolic subroutine and is implemented in a parallel computer structure called pyramid cellular automaton (PCA). The constructibility of conics and especially of circles (Sakoda's (1981) circle problem) in O(log n) time follows as a special case.     

Scalable parallel word search in multicore/multiprocessor systems

This paper presents a parallel algorithm for fast word search to determine the set of biological words of an input DNA sequence. The algorithm is designed to scale well on state-of-the-art multiprocessor/multicore systems for large inputs and large maximum word sizes. The pattern exhibited by many sequential solutions to this problem is a repetitive execution over a large input DNA sequence, and the generation of large amounts of output data to store and retrieve the words determined by the algorithm. As we show, this pattern does not lend itself to straightforward standard parallelization techniques. The proposed algorithm aims to achieve three major goals to overcome the drawbacks of embarrassingly parallel solution techniques: (i) to impose a high degree of cache locality on a problem that, by nature, tends to exhibit nonlocal access patterns, (ii) to be lock free or largely reduce the need for data access locking, and (iii) to enable an even distribution of the overall processing load among multiple threads. We present an implementation and performance evaluation of the proposed algorithm on DNA sequences of various sizes for different organisms on a dual processor quad-core system with a total of 8 cores. We compare the performance of the parallel word search implementation with a sequential implementation and with an embarrassingly parallel implementation. The results show that the proposed algorithm far outperforms the embarrassingly parallel strategy and achieves a speed-up’s of up to 6.9 on our 8-core test system.     

Cost–reliability optimum release policies for a software system under penalty cost

Optimum software release policies are considered, minimizing the expected software cost simultaneously with the reliability requirement. Cost here also includes the penalty cost which is incurred by the manufacturer for not delivering the software at scheduled delivery time. The underlying software reliability growth models (SRGMs) are based on the non-homogeneous Poisson process (NHPP). Numerical results are also presented.     

On the reliability of large-scale distributed systems – A topological view

In large-scale, self-organized distributed systems, such as peer-to-peer (P2P) overlays and wireless sensor networks (WSN), a small proportion of the nodes are likely to be more critical to the system’s reliability than others. This paper focuses on detecting cut vertices so that we can either neutralize or protect these critical nodes. Detection of cut vertices is trivial if the global knowledge of the whole system is known but it is very challenging when the global knowledge is not available. In this paper, we propose a completely distributed scheme where every single node can determine whether it is a cut vertex or not. In addition, our design can also confine the detection overhead to a constant instead of being proportional to the size of a network. The correctness of this algorithm is theoretically proved and the key performance gains are measured and verified through trace-driven simulations.     

EUCS test–retest reliability in representational model decision support systems

A test–retest reliability study of an end-user computing satisfaction instrument was conducted. The instrument was distributed to real-world representational decision support system users through a mail survey. One month later, follow-up surveys were mailed asking the original respondents to again evaluate the same system. The data sets were compared and suggest that the instrument is internally consistent and stable when applied to its users.     

Scalable mpNoC for massively parallel systems – Design and implementation on FPGA

The high chip-level integration enables the implementation of large-scale parallel processing architectures with 64 and more processing nodes on a single chip or on an FPGA device. These parallel systems require a cost-effective yet high-performance interconnection scheme to provide the needed communications between processors. The massively parallel Network on Chip (mpNoC) was proposed to address the demand for parallel irregular communications for massively parallel processing System on Chip (mppSoC). Targeting FPGA-based design, an efficient mpNoC low level RTL implementation is proposed taking into account design constraints. The proposed network is designed as an FPGA based Intellectual Property (IP) able to be configured in different communication modes. It can communicate between processors and also perform parallel I/O data transfer which is clearly a key issue in an SIMD system. The mpNoC RTL implementation presents good performances in terms of area, throughput and power consumption which are important metrics targeting an on chip implementation. mpNoC is a flexible architecture that is suitable for use in FPGA-based parallel systems. This paper introduces the basic mppSoC architecture. It mainly focuses on the mpNoC flexible IP based design and its implementation on FPGA. The integration of mpNoC in mppSoC is also described. Implementation results on a Stratix II FPGA device are given for three data-parallel applications ran on mppSoC. The obtained good performances justify the effectiveness of the proposed parallel network. It is shown that the mpNoC is a lightweight parallel network making it suitable for both small as well as large FPGA-based parallel systems.     

OpenMP based parallel normalized direct methods for sparse finite element linear systems

A new parallel normalized exact inverse algorithm is presented for solving sparse symmetric finite element linear systems on symmetric multiprocessor systems (SMP), based upon an antidiagonal motion approach (“wave”-like pattern) for overcoming the data dependencies. The proposed algorithm was implemented using OpenMP directives. Numerical results, such as speedups and efficiency, are presented illustrating the efficient performance on a symmetric multiprocessor computer system, where the proposed algorithmic solution method achieves good speedups.

PetRBF — A parallel O(N) algorithm for radial basis function interpolation with Gaussians

We have developed a parallel algorithm for radial basis function (rbf) interpolation that exhibits O(N) complexity, requires O(N) storage, and scales excellently up to a thousand processes. The algorithm uses a gmres iterative solver with a restricted additive Schwarz method (rasm) as a preconditioner and a fast matrix-vector algorithm. Previous fast rbf methods — achieving at most O(NlogN) complexity — were developed using multiquadric and polyharmonic basis functions. In contrast, the present method uses Gaussians with a small variance with respect to the domain, but with sufficient overlap. This is a common choice in particle methods for fluid simulation, our main target application. The fast decay of the Gaussian basis function allows rapid convergence of the iterative solver even when the subdomains in the rasm are very small. At the same time we show that the accuracy of the interpolation can achieve machine precision. The present method was implemented in parallel using the petsc library (developer version). Numerical experiments demonstrate its capability in problems of rbf interpolation with more than 50 million data points, timing at 106 s (19 iterations for an error tolerance of 10^? 15) on 1024 processors of a Blue Gene/L (700 MHz PowerPC processors). The parallel code is freely available in the open-source model.     

A parallel solving method for block-tridiagonal equations on CPU–GPU heterogeneous computing systems

Solving block-tridiagonal systems is one of the key issues in numerical simulations of many scientific and engineering problems. Non-zero elements are mainly concentrated in the blocks on the main diagonal for most block-tridiagonal matrices, and the blocks above and below the main diagonal have little non-zero elements. Therefore, we present a solving method which mixes direct and iterative methods. In our method, the submatrices on the main diagonal are solved by the direct methods in the iteration processes. Because the approximate solutions obtained by the direct methods are closer to the exact solutions, the convergence speed of solving the block-tridiagonal system of linear equations can be improved. Some direct methods have good performance in solving small-scale equations, and the sub-equations can be solved in parallel. We present an improved algorithm to solve the sub-equations by thread blocks on GPU, and the intermediate data are stored in shared memory, so as to significantly reduce the latency of memory access. Furthermore, we analyze cloud resources scheduling model and obtain ten block-tridiagonal matrices which are produced by the simulation of the cloud-computing system. The computing performance of solving these block-tridiagonal systems of linear equations can be improved using our method.     

System reliability for non-repairable multi-state series–parallel system using fuzzy Bayesian inference based on prior interval probabilities

In this article, the fuzzy concepts are applied in analysis of the system reliability problem. The fuzzy number is used to construct the fuzzy reliability of the non-repairable multi-state series–parallel system (NMSS). The fuzzy failure rate function is represented by an exponential fuzzy number. By using this innovative approach, the fuzzy system reliability of NMSS is created. In order to analyse this fuzzy system reliability, the fuzzy Bayesian point estimate of fuzzy system reliability is made by the conventional Bayesian formula. And, the posterior fuzzy system reliability of NMSS is developed by Bayesian inference with fuzzy probabilities. Finally, the performance of the method is measured by the mean square error of fuzzy Bayesian point estimate for the fuzzy system reliability of NMSS.     

A parallel computational framework to solve flow and transport in integrated surface–subsurface hydrologic systems

Hydrologic modeling requires the handling of a wide range of highly nonlinear processes from the scale of a hill slope to the continental scale, and thus the computational efficiency of the model becomes a critical issue for water resource management. This work is aimed at implementing and evaluating a flexible parallel computing framework for hydrologic simulations by applying OpenMP in the HydroGeoSphere (HGS) model. HGS is a 3D control-volume finite element model that solves the nonlinear coupled equations describing surface–subsurface water flow, solute migration and energy transport. The computing efficiency of HGS is improved by three parallel computing schemes: 1) parallelization of Jacobian matrix assembly, 2) multi-block node reordering for performing LU solve efficiently, and 3) parameter privatization for reducing memory access latency. Regarding to the accuracy and consistency of the simulation solutions obtained with parallel computing, differences in the solutions are entirely due to use of a finite linear solver iteration tolerance, which produces slightly different solutions which satisfy the convergence tolerance. The maximum difference in the head solution between the serial and parallel simulations is less than 10⁻³ m, using typical convergence tolerances. Using the parallel schemes developed in this work, three key achievements can be summarized: (1) parallelization of a physically-based hydrologic simulator can be performed in a manner that allows the same code to be executed on various shared memory platforms with minimal maintenance; (2) a general, flexible and robust parallel iterative sparse-matrix solver can be implemented in a wide range of numerical models employing either structured or unstructured mesh; and (3) the methodology is flexible, especially for the efficient construction of the coefficient and Jacobian matrices, compared to other parallelized hydrologic models which use parallel library packages.     

Optimal allocation and maintenance of multi-state elements in series–parallel systems with common bus performance sharing

This article considers the optimal allocation and maintenance of multi-state elements in series–parallel systems with common bus performance sharing. The surplus performance from a sub-system can be transmitted to any other sub-system which is experiencing performance deficiency. The amount that can be transmitted is subjected to a random transmission capacity. In order to increase the system availability, maintenance actions can be performed during the system lifetime and the system elements can be optimally allocated into the sub-systems. In this paper, we consider the element allocation and maintenance simultaneously in order to minimize the total maintenance cost subject to the pre-specified system availability requirement. An algorithm based on universal generating function is suggested to evaluate the system availability and the genetic algorithm is explored to solve the optimization problem. Numerical experiments are presented to illustrate the applications.     

Designing parallel loop self-scheduling schemes using the hybrid MPI and OpenMP programming model for?multi-core grid systems

Loop scheduling on parallel and distributed systems has been thoroughly investigated in the past. However, none of these studies considered the multi-core architecture feature for emerging grid systems. Although there have been many studies proposed to employ the hybrid MPI and OpenMP programming model to exploit different levels of parallelism for a distributed system with multi-core computers, none of them were aimed at parallel loop self-scheduling. Therefore, this paper investigates how to employ the hybrid MPI and OpenMP model to design a parallel loop self-scheduling scheme adapted to the multi-core architecture for emerging grid systems. Three different featured applications are implemented and evaluated to demonstrate the effectiveness of the proposed scheduling approach. The experimental results show that the proposed approach outperforms the previous work for the three applications and the speedups range from 1.13 to 1.75.