XPS:DSD:Synthesizing Domain Specific Systems

信息技术现在是人类奋进各个方面创新的主要催化剂。因此，保持计算设备的指数级性能增长至关重要，四十多年来，计算设备一直是信息技术进步的关键推动因素。过去，半导体技术为我们提供了不断增加的晶体管密度和不断减少的电源，使我们能够在不增加能耗的情况下提高性能。然而，在当前和未来技术中缺乏电源缩放使得所有计算系统能量受限。提高能源效率是一个决定性的挑战，也是提高所有计算系统（从智能手机到仓库规模的数据中心）能力的先决条件。该项目的目标是通过弥合高级应用程序开发与节能计算专用硬件设计之间的差距，实现具有成本效益的定制计算。专业化是节能计算的主流方法，因为定制单元可以消除通用核心的能源开销。然而，设计和管理定制硬件的复杂性目前限制了专业化对大容量、缓慢发展的应用程序的好处。我们将创建特定于领域的合成工具，给定一个以易于使用的特定于领域的编程语言编写的应用程序，将生成特定于领域或应用程序的硬件：计算单元和存储系统。我们的方法的核心领域特定的合成是一个特定领域的语言来捕捉高层次的应用程序信息，特定领域的优化，并行性和局部性优化，并从并行性和局部性模式的硬件生成的组合。

Information technology is now a major catalyst for innovation across all aspects of human endeavor. Hence, it is vital to maintain the exponential performance growth of computing devices that has been the key enabler for information technology advances for more than four decades. In the past, semiconductor technology provided us with increasing transistor densities and decreasing power supplies, allowing us to improve performance without increasing energy consumption. However, the lack of power supply scaling in current and future technologies has made all computing systems energy limited. Improving energy efficiency is a defining challenge and the prerequisite to increasing the capabilities of all computing systems, from smartphones to warehouse-scale data-centers. The goal of this project is to enable cost-effective customized computing by bridging the gap between high-level application development and the design of specialized hardware for energy efficient computing. Specialization is the prevailing approach for energy efficient computing, as customized units can eliminate the energy overheads of general-purpose cores. However, the complexity of designing and managing customized hardware is currently limiting the benefits from specialization to high-volume, slowly evolving applications. We will create domain specific synthesis tools that, given an application written in an easy-to-use, domain-specific programming language, will generate domain or application specific hardware: compute units and memory systems. The core of our approach to domain specific synthesis is a combination of domain specific languages to capture high-level application information, domain-specific optimization, parallelism and locality optimization, and hardware generation from parallelism and locality patterns.