For a long time, the Von Neumann has been a successful model of computation for sequential computing .Many models including the dataflow model have been unsuccessfully developed to emulate the same results in parallel computing. It is widely accepted that high performance computation is better-achieved using parallel architectures and is seen as the basis for future computational architectures with the ever-increasing need for high performance computation. We describe a new model of parallel computation known as the Arithmetic Deduction Model (AriDem) which has some similarities with the Von Neumann. A theoretical evaluation conducted on this model in comparison with the predominant von Neumann model indicated AriDeM to be more efficient in resources utilization. In this paper, we conduct an empirical evaluation of the model and the results reflect the output of the theoretical evaluation.

翻译：长期以来，冯·诺依曼模型一直是顺序计算的成功计算范式。尽管包括数据流模型在内的多种模型曾被尝试用于并行计算，但均未能成功复现相同效果。业界普遍认为，高性能计算更适合通过并行架构实现，且随着对高性能计算需求的持续增长，并行架构已成为未来计算架构的发展基础。本文提出一种名为算术推演模型（AriDeM）的新型并行计算模型，该模型与冯·诺依曼模型存在若干相似之处。与此前占主导地位的冯·诺依曼模型进行的理论评估表明，AriDeM在资源利用率方面更具优势。本文对该模型进行了实证评估，其结果与理论评估结论一致。