Architecture independent parallel selection with applications to parallel priority queues

AbstractWe present a randomized selection algorithm whose performance is analyzed in an architecture independent way on the bulk-synchronous parallel (BSP) model of computation along with an application of this algorithm to dynamic data structures, namely parallel priority queues. We show that our algorithms improve previous results upon both the communication requirements and the amount of parallel slack required to achieve optimal performance. We also establish that optimality to within small multiplicative constant factors can be achieved for a wide range of parallel machines. While these algorithms are fairly simple themselves, descriptions of their performance in terms of the BSP parameters is somewhat involved; the main reward of quantifying these complications is that it allows transportable software to be written for parallel machines that fit the model

Portable and architecture independent parallel performance tuning

A call-graph profiling tool has been designed and implemented to analyse the efficiency of programs written in bsplib. This tool highlights computation and communication imbalance in parallel programs, exposing portions of program code which are amenable to improvement. A unique feature of this profiler is that it uses the BSP cost model, thus providing a mechanism for portable and architecture-independent parallel performance tuning. In order to test the capabilities of the model on a real-world example, the performance characteristics of an SQL query processing application are investigated on a number of different parallel architectures

A Note on Probabilistic Integer Sorting

We present a new probabilistic sequential algorithm for stable sorting n uniformly distributed keys in an arbitrary range. The algorithm runs in linear time with veryhigh probability 1 \Gamma 2 \Gamma\Omega\Gamma n) (the best previously known probability bound has been 1 \Gamma 2 \Gamma\Omega\Gamma n=(lg n lg lg n)) ). We also describe an EREW PRAM version of the algorithm that sorts in O((n=p + lg p) lg n= lg (n=p + lg n)) time using p n processors within the same probability bound. Additionally, we present experimental results for the sequential algorithm that establish the practicality of our algorithm

Deterministic Sorting and Randomized Median Finding on the BSP model

We present new BSP algorithms for deterministic sorting and randomized median finding. We sort n general keys by using a partitioning scheme that achieves the requirements of efficiency (one-optimality) and insensitivity against data skew (the accuracy of the splitting keys depends solely on the step distance, which can be adapted to meet the worstcase requirements of our application). Although we employ sampling in order to realize efficiency, we can give a precise worst-case estimation of the maximum imbalance which might occur. We also investigate optimal randomized BSP algorithms for the problem of finding the median of n elements that require, with high-probability, 3n=(2p) + o(n=p) number of comparisons, for a wide range of values of n and p. Experimental results for the two algorithms are also presented