万数库：高性能可重复数系统库的设计和实现(CS)

E. 西奥多·奥姆齐格特， 彼得·戈茨林， 马克·塞利格曼， 威廉·佐恩

随着嵌入式系统的激增需要智能行为，定制编号系统优化整个系统每瓦的性能成为成功商业产品的基本组件。我们介绍了通用数字库，这是一个高性能的数字系统库，包括任意整数、十进制、定点、浮点，并引入了两种锥形浮点类型（假设和有效类型），它们支持任意并发环境中的可重复算术计算。我们将通用库的设计作为应用程序开发的时间，以及应用程序驱动的硬件验证平台。介绍了库实现，并提供了示例来演示说明数字系统属性的教育示例，以及如何使用专业化技术在现有 x86、ARM 和 POWER 处理器上生成非常高性能的仿真。我们将重点介绍该库在计算科学和工程中更大的应用环境中的集成，以实现多精度和自适应精度算法，以提高大规模和实时应用的性能和效率。我们将演示通用库与高性能可重复线性代数运行时的集成。我们将以库的其他功能路线图结束，因为我们的目标是新的应用领域，如软件定义的无线电、仪器仪表、传感器融合和模型预测控制。

Universal Numbers Library: design and implementation of a high-performance reproducible number systems library

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.