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Visual Parallel Programming and Determinancy: A Language Specification,an Analysis Technique,and a Programming Tool
Affiliation:1. State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zu Chong Zhi Road, Zhangjiang Hi-Tech Park, Shanghai 201203, China;2. The First Affiliated Hospital of Jinzhou Medical University, 2 Renmin Road, Jinzhou 121001, China;3. School of Pharmaceutical Sciences, Jinzhou Medical University, Jinzhou 121001, China;4. Open Studio for Drugability Research of Marine Natural Products, Qingdao National Laboratory for Marine Science and Technology, 1 Wenhai Road, Aoshanwei, Jimo, Qingdao 266237, China;5. College of Materials Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, China;1. Department of Biotechnology, CSIR-North East Institute of Science and Technology, Jorhat 785006, India;2. Academy of Scientific and Innovative Research, Rafi Marg, New Delhi 110001, India
Abstract:Phred is a visual parallel programming language in which programs can be statically analyzed for deterministic behavior. This paper presents the Phred language, techniques for analyzing the language, and a programming environment which supports Phred programming. There are many methods for specifying synchronization and data sharing in parallel programs. The Phred programmer uses graph constructs for describing parallelism, synchronization, and data sharing. These graphs are formally described in this paper as a graph grammar. The use of graphs in Phred provides an intuitive and visual representation for parallel computations. The inadvertent specification of nondeterministic computations is a common error in parallel programming. Phred addresses the issue of determinacy by visually indicating regions of a program where nondeterminacy may exist. This analysis and its integration into a programming environment is presented here. The Phred programming environment supports the specification, analysis, and execution of Phred programs. The distribution of the programming environment itself over several workstations is also described.
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