Enabling massively parallel, ad hoc exploration of the design space for simulation models within a serverless environment

Andrew Gibson, Manuel D Rossetti
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Abstract

This paper presents a massively parallel, cloud-computing framework for the ad hoc evaluation of discrete-event simulation (DES) models to enable broad exploration of the design space for model parameters. Parallel evaluation is enabled through use of a serverless computing environment allowing thousands of simultaneous experiments, on demand, without the need to explicitly provision or manages hardware. A standard Simulation Evaluation application programming interface (API) was designed for evaluating simulation functions that enables language independence between client application and simulation model, encouraging reuse of simulation models for multiple purposes (what-if analysis, ranking and selection, sensitivity analysis, or optimization). Extensions to the Java Simulation Library (JSL)27 enable rapid deployment of models built with the JSL as parameterized serverless functions implementing the Simulation Evaluation API. New Java packages facilitate the calling of any serverless functions that implement the Simulation Evaluation API.
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在无服务器环境中对仿真模型的设计空间进行大规模并行特别探索
本文介绍了一种大规模并行云计算框架,用于对离散事件仿真(DES)模型进行临时评估,以广泛探索模型参数的设计空间。并行评估是通过使用无服务器计算环境实现的,该环境允许按需同时进行数千次实验,而无需明确提供或管理硬件。为评估仿真功能设计了一个标准的仿真评估应用编程接口(API),使客户端应用程序和仿真模型之间不依赖语言,鼓励为多种目的(假设分析、排序和选择、灵敏度分析或优化)重复使用仿真模型。通过对 Java 仿真库(JSL)27 的扩展,可以将使用 JSL 构建的模型快速部署为实现仿真评估 API 的参数化无服务器函数。新的 Java 包有助于调用任何实现仿真评估 API 的无服务器函数。
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