This book brings together current research direction in the mapping of dynamic programming recurrence equations for Knapsack Type problems, which include Unbounded Knapsack Problem, 0/1 Knapsack Problem, Subset Sum Problem, Change Making Problem, onto so-called regular parallel architectures. In particular, it focuses on heuristic and more formal techniques for mapping. The text is based on substantially revised papers published by the authors and their colleagues in the literature but re-written to provide an overall view of the subject area.

Abstract: "We shall describe an [sic] parallel algorithm for solving the knapsack feasibilty problem, also known as the subset sum problem. The use of a random branching technique is described and its implementation on a parallel processor is discussed. Computational results show this to be an effective method for solving large problems. Using this approach we have solved problems with as many as 2 million variables in an average of 800 seconds on the Sequent Symmetry parallel processor. Furthermore, a coarse parallelization overcomes some of the problems that are present when serial algorithms are used to solve the knapsack problem."

Efficient parallel solutions have been found to many problems. Some of them can be obtained automatically from sequential programs, using compilers. However, there is a large class of problems - irregular problems - that lack efficient solutions. IRREGULAR 94 - a workshop and summer school organized in Geneva - addressed the problems associated with the derivation of efficient solutions to irregular problems. This book, which is based on the workshop, draws on the contributions of outstanding scientists to present the state of the art in irregular problems, covering aspects ranging from scientific computing, discrete optimization, and automatic extraction of parallelism. Audience: This first book on parallel algorithms for irregular problems is of interest to advanced graduate students and researchers in parallel computer science.

Mathematics of Computing -- Parallelism.

Abstract: "We shall describe an [sic] parallel algorithm for solving the knapsack feasibilty problem, also known as the subset sum problem. The use of a random branching technique is described and its implementation on a parallel processor is discussed. Computational results show this to be an effective method for solving large problems. Using this approach we have solved problems with as many as 2 million variables in an average of 800 seconds on the Sequent Symmetry parallel processor. Furthermore, a coarse parallelization overcomes some of the problems that are present when serial algorithms are used to solve the knapsack problem."

This book brings together current research direction in the mapping of dynamic programming recurrence equations for Knapsack Type problems, which include Unbounded Knapsack Problem, 0/1 Knapsack Problem, Subset Sum Problem, Change Making Problem, onto so-called regular parallel architectures. In particular, it focuses on heuristic and more formal techniques for mapping. The text is based on substantially revised papers published by the authors and their colleagues in the literature but re-written to provide an overall view of the subject area.