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Universal Numbers Library: design and implementation of a high-performance reproducible number systems library
arXiv - CS - Mathematical Software Pub Date : 2020-12-20 , DOI: arxiv-2012.11011
E. Theodore L. Omtzigt, Peter Gottschling, Mark Seligman, William Zorn

With the proliferation of embedded systems requiring intelligent behavior, custom number systems to optimize performance per Watt of the entire system become essential components for successful commercial products. We present the Universal Number Library, a high-performance number systems library that includes arbitrary integer, decimal, fixed-point, floating-point, and introduces two tapered floating-point types, posit and valid, that support reproducible arithmetic computation in arbitrary concurrency environments. We discuss the design of the Universal library as a run-time for application development, and as a platform for application-driven hardware validation. The library implementation is described, and examples are provided to show educational examples to elucidate the number system properties, and how specialization is used to yield very high-performance emulation on existing x86, ARM, and POWER processors. We will highlight the integration of the library in larger application environments in computational science and engineering to enable multi-precision and adaptive precision algorithms to improve performance and efficiency of large scale and real-time applications. We will demonstrate the integration of the Universal library into a high-performance reproducible linear algebra run-time. We will conclude with the roadmap of additional functionality of the library as we are targeting new application domains, such as Software Defined Radio, instrumentation, sensor fusion, and model-predictive control.

中文翻译:

通用号码库:高性能可复制号码系统库的设计和实现

随着要求智能行为的嵌入式系统的泛滥,用于优化整个系统每瓦性能的定制编号系统已成为成功商业产品的基本组成部分。我们介绍了通用数字库,这是一个高性能的数字系统库,其中包括任意整数,十进制,定点数,浮点数,并引入了两个渐变浮点类型(正数和有效数),它们支持任意并发中的可重现算术计算。环境。我们将讨论通用库的设计,作为应用程序开发的运行时以及作为应用程序驱动的硬件验证的平台。描述了库的实现,并提供了一些示例来显示教育示例,以阐明数字系统的特性,以及如何使用专业化在现有x86,ARM和POWER处理器上产生非常高性能的仿真。我们将重点介绍库在计算科学和工程学中在更大的应用程序环境中的集成,以使多精度和自适应精度算法能够提高大规模和实时应用程序的性能和效率。我们将展示通用库到高性能可重现线性代数运行时的集成。当我们针对新的应用领域时,我们将以库的其他功能路线图作为结束,这些领域包括软件定义无线电,仪器仪表,传感器融合和模型预测控制。我们将重点介绍库在计算科学和工程学中在更大的应用程序环境中的集成,以使多精度和自适应精度算法能够提高大规模和实时应用程序的性能和效率。我们将展示通用库到高性能可重现线性代数运行时的集成。当我们针对新的应用领域时,我们将以库的其他功能路线图作为结束,这些领域包括软件定义无线电,仪器仪表,传感器融合和模型预测控制。我们将重点介绍库在计算科学和工程学中在更大的应用程序环境中的集成,以使多精度和自适应精度算法能够提高大规模和实时应用程序的性能和效率。我们将展示通用库到高性能可重现线性代数运行时的集成。当我们针对新的应用领域时,我们将以库的其他功能路线图作为结束,这些领域包括软件定义无线电,仪器仪表,传感器融合和模型预测控制。我们将展示通用库到高性能可重现线性代数运行时的集成。当我们针对新的应用领域时,我们将以库的其他功能路线图作为结束,这些领域包括软件定义无线电,仪器仪表,传感器融合和模型预测控制。我们将展示通用库到高性能可重现线性代数运行时的集成。当我们针对新的应用领域时,我们将以库的其他功能路线图作为结束,这些领域包括软件定义无线电,仪器仪表,传感器融合和模型预测控制。
更新日期:2020-12-22
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