Many-core processors target improved computational performance by making available various forms of architectural parallelism, including but not limited to multiple cores and vector instructions. However, approaches to parallel programming based on targeting these low-level parallel mechanisms directly leads to overly complex, non-portable, and often unscalable and unreliable code. A more struc...

Using a new domain-theoretic characterisation we show that Berry’s constructive semantics is a conservative approximation of the recently proposed sequentially constructive (SC) model of computation. We prove that every Berry-constructive program is deterministic and deadlock-free under sequentially admissible scheduling. This gives, for the first time, a natural interpretation of Berry-constru...

Want to get experience? Want to get any ideas to create new things in your life? Read non deterministic concurrent logic programming in pandora now! By reading this book as soon as possible, you can renew the situation to get the inspirations. Yeah, this way will lead you to always think more and more. In this case, this book will be always right for you. When you can observe more about the boo...

Orc is a new model of distributed programming which provides a strong theoretical foundation for internet computing based on compositions of web-services. Orc combines some of the power and flexibility of process algebra with the simplicity and determinism of synchronous programming models. We present an operational semantics of Orc and prove some laws analogous to those of Kleene algebra. We v...

With the increasing reliance on modeling optimization problems in practical applications, a number of theoretical and algorithmic contributions of optimization have been proposed. The approaches developed for treating optimization problems can be classified into deterministic and heuristic. This paper aims to introduce recent advances in deterministic methods for solving signomial programming p...

There are many cases that a nonlinear fractional programming, generated as a result of studying fractional stochastic programming, must be solved. Sometimes an approximate solution may be sufficient enough to start a new process of calculations. To this end, this author introduces a new linear approximation technique for solving a fractional chance constrained programming (CCP) problem. After i...

We address the resource-constrained generalizations of the assignment problem with uncertain resource capacities, where the resource capacities have an unknown distribution that can be sampled. We propose three stochastic programming-based formulations that can be used to solve this problem, and provide exact and approximate solution techniques for the resulting models. We also present numerica...

Functional logic languages combine lazy (demand-driven) evaluation strategies from functional programming with non-deterministic computations from logic programming. To provide a strategy-independent semantics, most languages are based on the call-time choice semantics where parameters are passed as values. From an implementation point of view, the call-time choice semantics fits well with shar...

2 Deterministic Dynamic Programming and Viscosity Solutions 5 2.