The Complexity of Sorting on Distributed Systems

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryJoint Services Electronics Program / N00014-79-C-0424National Science Foundation / MCS-821744

Implementation and Performance Evaluation of Algorithms Running on Distributed Systems

With the rapid development of technology, people are fully engrossed by the information age. A single computer does not have enough ability to process the huge information and communication that generated on the Internet every day. However, a distributed system offers quick and precise solutions for a variety of complex problems in different fields. There are several definitions on distributed systems, these definitions can be summarized as a system in which hardware or software components located at networked computers communicate and coordinate their actions only by message passing. In comparison to a personal computer (PC), a distributed system has more resources to increase performance. Because distributed system can separate the task when handling complexity problems or massive data. This thesis focuses on implementation and performance evaluation of algorithms running on distributed systems. Mainly measures the time complexity of algorithms (bubble sort, quick sort, and heap sort) executed on distributed system and a personal computer. Then takes the comparison between them. Distributed systems consist of two Raspberries Pi and a personal computer. Two raspberries Pi regarded as two clients and the personal computer is a server. Sockets are used for the communication between the clients and the server. The Graphical User Interface (GUI) has been implemented on the server. The server generates the random numbers, selects the sort algorithm, separates the task and sends it to two clients. On the client, the random numbers will be sorted then two clients return the result of the task to the server. The server receives the sorted numbers and displays it. Furthermore, the GUI shows the measured sorting time.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Parallel Performance of MPI Sorting Algorithms on Dual-Core Processor Windows-Based Systems

Message Passing Interface (MPI) is widely used to implement parallel programs. Although Windowsbased architectures provide the facilities of parallel execution and multi-threading, little attention has been focused on using MPI on these platforms. In this paper we use the dual core Window-based platform to study the effect of parallel processes number and also the number of cores on the performance of three MPI parallel implementations for some sorting algorithms

The Effect of Electronic Auditing In Reducing The Burden of Electronic Environment Complexity of Accounting Information System on The Auditor

This study aims to show the effect of Electronic Auditing in reducing the burden of Electronic Environment Complexity of Accounting Information System on the Auditor. So as to achieve the study objectives, a questionnaire has been prepared consisting of 17 paragraphs related to the capacity of Electronic Auditing System in reducing the complexity of Electronic Environment that external auditors face when they are asked to audit accounts of a company that uses Electronic Accounting Information System. The complexity of Electronic Environment has been determined through an interview made with a number of programmers of Accounting Information System and number of Auditors who use Electronic System in auditing, 100 questionnaires were distributed on external auditors working in Auditing offices in Amman that were chosen randomly. Out of the total   questionnaires 92 have been collected valid to be analyzed with 92% response. The study reached to a conclusion that  there is an effect to the Electronic Auditing System in reducing the burden of Electronic Environment Complexity of Accounting Information System on the Auditor regarding to the increasing Trust Factor and the dealing with multi–generation of Electronic Accounting Information System, and in following up mistakes and sorting them out directly…etc. The two researchers recommend that auditors increase their interest in Electronic Auditing Field, because of its impact in reducing the burden of Electronic Environment Complexity of Accounting Information System on the Auditor, and confirming the accuracy and authenticity of data from Accounting Information Systems. Keywords: Electronic Auditing, Accounting Information System, Complexity of Electronic Environment.

Randomized versus Deterministic Implementations of Concurrent Data Structures

One of the key trends in computing over the past two decades has been increased distribution, both at the processor level, where multi-core architectures are now the norm, and at the system level, where many key services are currently distributed overmultiple machines. Thus, understanding the power and limitations of computing in a concurrent, distributed setting is one of the major challenges in Computer Science. In this thesis, we analyze the complexity of implementing concurrent data structures in asynchronous shared memory systems. We focus on the complexity of a classic distributed coordination task called renaming, in which a set of processes need to pick distinct names from a small set of identifiers. We present the first tight bounds for the time complexity of this problem, both for deterministic and randomized implementations, solving a long-standing open problem in the field. For deterministic algorithms, we prove a tight linear lower bound; for randomized solutions, we provide logarithmic upper and lower bounds on time complexity. Together, these results show an exponential separation between deterministic and randomized renaming solutions. Importantly, the lower bounds extend to implementations of practical shared-memory data structures, such as queues, stacks, and counters. From a technical perspective, this thesis highlights new connections between the distributed renaming problem and other fundamental objects, such as sorting networks, mutual exclusion, and counters. In particular, we show that sorting networks can be used to obtain optimal randomized solutions to renaming, and that, in turn, the existence of these solutions implies a linear lower bound on the complexity of the problem. In sum, the results in this thesis suggest that deterministic implementations of shared-memory data structures do not scale well in terms of worst-case time complexity. On the positive side, we emphasize randomization as a natural alternative, which can circumvent the deterministic lower bounds with high probability. Thus, a promising direction for future work is to extend our randomized renaming techniques to obtain efficient implementations of concurrent data structures

A Parallel Monte Carlo Code for Simulating Collisional N-body Systems

We present a new parallel code for computing the dynamical evolution of collisional N-body systems with up to N~10^7 particles. Our code is based on the the Henon Monte Carlo method for solving the Fokker-Planck equation, and makes assumptions of spherical symmetry and dynamical equilibrium. The principal algorithmic developments involve optimizing data structures, and the introduction of a parallel random number generation scheme, as well as a parallel sorting algorithm, required to find nearest neighbors for interactions and to compute the gravitational potential. The new algorithms we introduce along with our choice of decomposition scheme minimize communication costs and ensure optimal distribution of data and workload among the processing units. The implementation uses the Message Passing Interface (MPI) library for communication, which makes it portable to many different supercomputing architectures. We validate the code by calculating the evolution of clusters with initial Plummer distribution functions up to core collapse with the number of stars, N, spanning three orders of magnitude, from 10^5 to 10^7. We find that our results are in good agreement with self-similar core-collapse solutions, and the core collapse times generally agree with expectations from the literature. Also, we observe good total energy conservation, within less than 0.04% throughout all simulations. We analyze the performance of the code, and demonstrate near-linear scaling of the runtime with the number of processors up to 64 processors for N=10^5, 128 for N=10^6 and 256 for N=10^7. The runtime reaches a saturation with the addition of more processors beyond these limits which is a characteristic of the parallel sorting algorithm. The resulting maximum speedups we achieve are approximately 60x, 100x, and 220x, respectively.Comment: 53 pages, 13 figures, accepted for publication in ApJ Supplement

A Parallel Distributed Strategy for Arraying a Scattered Robot Swarm

We consider the problem of organizing a scattered group of $n$ robots in two-dimensional space, with geometric maximum distance $D$ between robots. The communication graph of the swarm is connected, but there is no central authority for organizing it. We want to arrange them into a sorted and equally-spaced array between the robots with lowest and highest label, while maintaining a connected communication network. In this paper, we describe a distributed method to accomplish these goals, without using central control, while also keeping time, travel distance and communication cost at a minimum. We proceed in a number of stages (leader election, initial path construction, subtree contraction, geometric straightening, and distributed sorting), none of which requires a central authority, but still accomplishes best possible parallelization. The overall arraying is performed in $O(n)$ time, $O(n^2)$ individual messages, and $O(nD)$ travel distance. Implementation of the sorting and navigation use communication messages of fixed size, and are a practical solution for large populations of low-cost robots