Sorting is one of the more computationally intensive tasks a computer performs. One of the most effective ways to speed up the task of sorting is by using parallel algorithms. When implementing a parallel algorithm, the designer has to make several decisions. Among the decisions are the algorithm and the physical implementation of the algorithm. A dedicated hardware solution is often physically quicker than a software solution. In this thesis, we will investigate the optimization of a hardware implementation of max-min sort. I propose an optimization to the data structures used in the algorithm. The new data structure allows quicker sorting by changing the basic workings of the max-min sort. The results are presented by comparing the new data structure with the original data structure. The thesis also discusses the design and performance issues related to implementing the algorithm in hardware. / Graduation date: 1998

Thesis (M.S.)--Brigham Young University. School of Technology, 2006. / Includes bibliographical references (p. 119-121).

published_or_final_version / Computer Science / Master / Master of Philosophy

No description available.

Thesis (M.S.)--Ohio University, August, 1998. / Title from PDF t.p.

Thesis (M. Phil.)--University of Hong Kong, 1997. / Includes bibliographical references (leaf 63-64).

No description available.

The effective use of computational resources requires a good understanding of parallel architectures and algorithms. The effect of the parallel architecture and also the parallel application on the performance of the parallel systems becomes more complex with increasing numbers of processors. We will address this issue in this thesis, and develop a methodology to predict the overall execution time of a parallel application as a function of the system and problem size by combining simple analysis with a few experimental results. We show that runtimes and speedup can be predicted more accurately by analyzing the functional forms of the sequential and parallel times of critical code segments of a parallel application that affect the speedup of a parallel program. We then combine the functional forms to model the runtime of a parallel application. A small set of experiments are sufficient to get a good estimate of the coefficients for the runtime models obtained. Speedup can then be derived for any case from the runtime model. We also analyze the effect of the 1/0 on runtimes in memory bounded parallel systems, and how speedup is affected by communication and 1/0. Throughout the thesis we use the bitonic merge sort as a typical realistic parallel application to illustrate our methodology. Several variations of the sorting algorithm (such as problem size greater than or equal to the system size, unlimited or limited buffer size) suitable for a wide range of problem sizes are implemented in two parallel environments and the speedups for them are measured and compared with different speedup predictions. We have conducted numerous experiments using Multi and PVM to empirically study speedup for the different realistic implementations of the bitonic merge sort. The results show how well the various models predicted speedup, and that our methodology can predict speedup accurately for a given parallel application. One interesting value from a speedup curve is the roll-off point - the system size beyond which speedup actually decreases when the number of processors is increased. Results show that simple theoretic models predicted roll-off point to be higher than the actual values, where as our methodology predicted it to be less than and closer to the actual values. The predictions by our methodology also compare well with the speedup estimates provided by the Multi tool.

The Republic of Guinea is located on the west coast of Africa at about 11° North latitude. A large portion of Guinea's supply of protein is dried fish. The actual drying method operates under open air, the foodstuff being unprotected from unexpected rains, windborne dirt and dust, and from infestation by insects, rodents, and other animals. More, the deforestation rate is increasing year after year, depleting the source of fuel for drying. Practical ways of drying fish cheaply and sanitarily would be welcome.Recently, much work has been devoted to developing algorithms for parallel processors. Parallel algorithms have received a great deal of attention because of the advances in computer hardware technology. These parallel processors and algorithms have been used to improve computational speed, especially in the areas of sorting, evaluation of polynomials, arithmetic expressions, matrix and graphic problems.Sorting is an important operation in business and computer engineering applications. The literature contains many sorting algorithms, both sequential and parallel, which have been developed and used in practical applications. bubble sort, quick sort, insertion sort, enumeration sort, bucket and odd-even transposition sort. Ada, a new excellent programming language that offers high-level concurrent processing facilities called tasks, is used in this thesis to introduce, implement, compare and evaluate some of the parallel sorting algorithms. This thesis will also show that parallel sorting algorithms reduce the time requirement to perform the tasks. / Department of Computer Science

Thesis (M.S.)--State University of New York at Binghamton, Department of Computer Science, Thomas J. Watson School of Engineering and Applied Science, 2007. / Includes bibliographical references.