mAPN：数学和数学适应性的建模、分析和探索
mAPN: Modeling, Analysis, and Exploration of Algorithmic and Parallelism Adaptivity
摘要：
如今，使用并行嵌入式系统的情况越来越多。由于在一个应用程序中集成多个功能或同时运行多个功能，它们变得越来越复杂。这涉及广泛的应用，包括通常在嵌入式系统中使用的流应用。这些应用程序必须实现适应性强且可靠的算法，以在各种情况下提供所需的性能（例如，在平台上运行应用程序、输入数据、平台种类等）。考虑到流应用程序、目标系统和自适应性要求的复杂性，使用传统编程模型设计此类系统是令人生畏的。这就是为什么基于模型的策略与适当的计算模型（MoC）长期以来一直在研究嵌入式系统设计。这项工作提供了算法的自适应性的顶部的并行动态的并行化来表达更大的变量集。我们提出了一个多替代过程网络（mAPN），一个高层次的抽象表示，其中同一应用程序的几个变种共存于同一个图中表达不同的实现。我们介绍mAPN属性和它的形式主义来描述各种本地实现的替代方案。此外，mAPN用元数据丰富，以根据特定度量为替代方案提供定量注释。为了帮助用户分析丰富的变量空间，我们提出了一种方法来提取用户和硬件约束下的可行的变量。该方法的核心是一种算法，用于计算从紧凑的mAPN规范执行不同的替代品的全局度量。我们验证我们的方法，探索几种可能的变种创建的自动字幕应用程序（ASA）在两个硬件平台上。
英文摘要：
Using parallel embedded systems these days is increasing. They are getting more complex due to integrating multiple functionalities in one application or running numerous ones concurrently. This concerns a wide range of applications, including streaming applications, commonly used in embedded systems. These applications must implement adaptable and reliable algorithms to deliver the required performance under varying circumstances (e.g., running applications on the platform, input data, platform variety, etc.). Given the complexity of streaming applications, target systems, and adaptivity requirements, designing such systems with traditional programming models is daunting. This is why model-based strategies with an appropriate Model of Computation (MoC) have long been studied for embedded system design. This work provides algorithmic adaptivity on top of parallelism for dynamic dataflow to express larger sets of variants. We present a multi-Alternative Process Network (mAPN), a high-level abstract representation in which several variants of the same application coexist in the same graph expressing different implementations. We introduce mAPN properties and its formalism to describe various local implementation alternatives. Furthermore, mAPNs are enriched with metadata to Provide the alternatives with quantitative annotations in terms of a specific metric. To help the user analyze the rich space of variants, we propose a methodology to extract feasible variants under user and hardware constraints. At the core of the methodology is an algorithm for computing global metrics of an execution of different alternatives from a compact mAPN specification. We validate our approach by exploring several possible variants created for the Automatic Subtitling Application (ASA) on two hardware platforms.
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