On the Optimality of Tape Merge of Two Lists with Similar Size

The problem of merging sorted lists in the least number of pairwise comparisons has been solved completely only for a few special cases. Graham and Karp \cite{taocp} independently discovered that the tape merge algorithm is optimal in the worst case when the two lists have the same size. In the seminal papers, Stockmeyer and Yao\cite{yao}, Murphy and Paull\cite{3k3}, and Christen\cite{christen1978optimality} independently showed when the lists to be merged are of size $m$ and $n$ satisfying $m\leq n\leq\lfloor\frac{3}{2}m\rfloor+1$, the tape merge algorithm is optimal in the worst case. This paper extends this result by showing that the tape merge algorithm is optimal in the worst case whenever the size of one list is no larger than 1.52 times the size of the other. The main tool we used to prove lower bounds is Knuth's adversary methods \cite{taocp}. In addition, we show that the lower bound cannot be improved to 1.8 via Knuth's adversary methods. We also develop a new inequality about Knuth's adversary methods, which might be interesting in its own right. Moreover, we design a simple procedure to achieve constant improvement of the upper bounds for $2m-2\leq n\leq 3m$

New Parallel Sorting Schemes

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryJoint Services Electronics Program / DAAB-07-72-C-0259National Science Foundation / NSF MCS-76-1732

A taxonomy of parallel sorting

TR 84-601In this paper, we propose a taxonomy of parallel sorting that includes a broad range of array and file sorting algorithms. We analyze the evolution of research on parallel sorting, from the earliest sorting networks to the shared memory algorithms and the VLSI sorters. In the context of sorting networks, we describe two fundamental parallel merging schemes - the odd-even and the bitonic merge. Sorting algorithms have been derived from these merging algorithms for parallel computers where processors communicate through interconnection networks such as the perfect shuffle, the mesh and a number of other sparse networks. After describing the network sorting algorithms, we show that, with a shared memory model of parallel computation, faster algorithms have been derived from parallel enumeration sorting schemes, where keys are first ranked and then rearranged according to their rank

Parallel Algorithms for the Maximum Flow

The problem of finding the maximal flow through a given network has been intensively studied over the years. The classic algorithm for this problem given by Ford and Fulkerson has been developed and improved by a number of authors including Edmonds and Karp. With the advent of parallel computers, it is of great interest to see whether more efficient algorithms can be designed and implemented. The networks which we will consider will be both capacitated and bounded. Compared with a capacitated network, the problem of finding a flow through a bounded network is much more complicated in that a transformation into an auxiliary network is required before a feasible flow can be found. In this thesis, we review the algorithms of Ford and Fulkerson and Edmonds and Karp and implement them in a standard sequential way. We also implement the transformation required to handle the case of a bounded network. We then develop two parallel algorithms, the first being a parallel version of the Edmonds and Karp algorithm while the second applies the Breadth-First search technique to extract as much parallelism as possible from the problem. Both these algorithms have been written in the Occam programming language and implemented on a transputer system consisting of an IBM PC host, a B004 single transputer board and a network of four transputers contained on a B003 board supplied by Inmos Ltd. This is an example of a multiprocessor machine with independent memory. The relative efficiency of the algorithms has been studied and we present tables of the execution times taken over a variety of test networks. The transformation of the original network into an auxiliary network has also been implemented using parallel techniques and the problems encountered in the development of the algorithm are described. We have also investigated in detail one of the few parallel algorithms for this problem described in the literature due to Shiloach and Vishkin. This algorithm is described in the thesis. It has not been possible to implement this algorithm because it is specifically designed to run on a multiprocessor machine with shared memory

Size bounds and parallel algorithms for networks

SIGLEAvailable from British Library Document Supply Centre- DSC:D34009/81 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Parallel alogorithms for MIMD parallel computers

This thesis mainly covers the design and analysis of asynchronous parallel algorithms that can be run on MIMD (Multiple Instruction Multiple Data) parallel computers, in particular the NEPTUNE system at Loughborough University. Initially the fundamentals of parallel computer architectures are introduced with different parallel architectures being described and compared. The principles of parallel programming and the design of parallel algorithms are also outlined. Also the main characteristics of the 4 processor MIMD NEPTUNE system are presented, and performance indicators, i.e. the speed-up and the efficiency factors are defined for the measurement of parallelism in a given system. Both numerical and non-numerical algorithms are covered in the thesis. In the numerical solution of partial differential equations, a new parallel 9-point block iterative method is developed. Here, the organization of the blocks is done in such a way that each process contains its own group of 9 points on the network, therefore, they can be run in parallel. The parallel implementation of both 9-point and 4- point block iterative methods were programmed using natural and redblack ordering with synchronous and asynchronous approaches. The results obtained for these different implementations were compared and analysed. Next the parallel version of the A.G.E. (Alternating Group Explicit) method is developed in which the explicit nature of the difference equation is revealed and exploited when applied to derive the solution of both linear and non-linear 2-point boundary value problems. Two strategies have been used in the implementation of the parallel A.G.E. method using the synchronous and asynchronous approaches. The results from these implementations were compared. Also for comparison reasons the results obtained from the parallel A.G.E. were compared with the ~ corresponding results obtained from the parallel versions of the Jacobi, Gauss-Seidel and S.O.R. methods. Finally, a computational complexity analysis of the parallel A.G.E. algorithms is included. In the area of non-numeric algorithms, the problems of sorting and searching were studied. The sorting methods which were investigated was the shell and the digit sort methods. with each method different parallel strategies and approaches were used and compared to find the best results which can be obtained on the parallel machine. In the searching methods, the sequential search algorithm in an unordered table and the binary search algorithms were investigated and implemented in parallel with a presentation of the results. Finally, a complexity analysis of these methods is presented. The thesis concludes with a chapter summarizing the main results