Loop Iteration Counts Research Articles

An efficient interior point method for sequential quadratic programming based optimal power flow

This paper presents a new sequential quadratic programming algorithm for solving the optimal power flow problem. The algorithm is structured with an outer linearization loop and an inner optimization loop. The inner loop solves a relaxed reduced quadratic programming problem. Because constraint relaxation keeps the inner loop problem of small dimension, the algorithm is quite efficient. Its outer loop iteration counts are comparable to Newton power flow and the inner loops are efficient interior point iterations. Several IEEE test systems were run. The results indicate that both outer and inner loop iteration counts do not vary greatly with problem size.

On estimating the useful work distribution of parallel programs under P3T: a static performance estimator

In order to improve a parallel program's performance it is critical to evaluate how even the work contained in a program is distributed over all processors dedicated to the computation. Traditional work distribution analysis is commonly performed at the machine level. The disadvantage of this method is that it cannot identify whether the processors are performing useful or redundant (replicated) work. The paper describes a novel method of statically estimating the useful work distribution of distributed-memory parallel programs at the program level, which carefully distinguishes between useful and redundant work. The amount of work contained in a parallel program, which correlates with the number of loop iterations to be executed by each processor, is estimated by accurately modeling loop iteration spaces, array access patterns and data distributions. A cost function defines the useful work distribution of loops, procedures and the entire program. Lower and upper bounds of the described parameter are presented. The computational complexity of the cost function is independent of the program's problem size, statement execution and loop iteration counts. As a consequence, estimating the work distribution based on the described method is considerably faster than simulating or actually compiling and executing the program. Automatically estimating the useful work distribution is fully implemented as part of P3T, which is a static parameter based performance prediction tool under the Vienna Fortran Compilation System (VFCS). The Lawrence Livermore Loops are used as a test case to verify the approach.