SHF: Small: Workload Characterization and Benchmark Synthesis for Emerging Computing Systems

SHF：小型：新兴计算系统的工作负载表征和基准综合

• 批准号: 1117895
• 负责人: Lizy John
• 金额: $ 42.5万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1117895&HistoricalAwards=false
• 关键词: SHF; Small; Workload; Characterization; Benchmark

The face of emerging computing systems is changing rapidly. On one hand computers are looking smaller than ever. The smart phone is nothing but a pocket computer which also has the ability to make a phone call. On the other hand, computers are getting bigger than ever, as in a cloud computing server. These cloud systems are distributed systems with a large number of processors, abundant memory and disks and plentiful network resources and bandwidth, and are huge. This project is on workload characterization and benchmark synthesis for emerging computing systems such as the embedded computer and the cloud computer.The first component of this project consists in characterizing and understanding workloads on emerging computing platforms. Characteristics of embedded computing software in embedded Java or paradigms such as the .NET, or cloud applications such as Hadoop are not well-understood. It is also unclear whether next generation cloud servers should use simple energy efficient processors or more powerful processors geared towards performance. The characterization component of our project is geared towards understanding these issues. The second component of this project consists of benchmark synthesis to create workload proxies that have equivalent performance and energy characteristics as the original applications but without the functionality. These proxy workloads will enable efficient pre-silicon design exploration and sharing of proprietary applications.At a broader level, the research creates mechanisms that enable hardware and software developers to collaborate on joint product development without fear of loss of intellectual property. It also trains several graduate and undergraduate students in an important research area, and influences courses on embedded and cloud computing.

新兴计算系统的面貌正在迅速改变。一方面，计算机看起来比以往任何时候都更小。智能手机只是一台袖珍电脑，它也有打电话的能力。另一方面，计算机变得比以往任何时候都更大，就像云计算服务器一样。这些云系统是分布式系统，具有大量的处理器、充足的内存和磁盘以及丰富的网络资源和带宽，并且非常庞大。这个项目是关于嵌入式计算机和云计算等新兴计算系统的工作负载表征和基准综合。该项目的第一个组成部分是表征和了解新兴计算平台上的工作负载。嵌入式Java中的嵌入式计算软件或范例(如.NET)或云应用程序(如Hadoop)的特征尚未得到很好的理解。下一代云服务器是应该使用简单的节能处理器，还是应该使用更强大的处理器来提高性能，目前还不清楚。我们项目的特征部分是为了理解这些问题。该项目的第二个组件包括基准测试合成，以创建与原始应用程序具有相同性能和能源特征但没有功能的工作负载代理。这些代理工作负载将实现高效的芯片前设计探索和专有应用程序的共享。在更广泛的层面上，该研究创建了一种机制，使硬件和软件开发人员能够在联合产品开发方面进行协作，而不必担心失去知识产权。它还在一个重要的研究领域培养了几名研究生和本科生，并影响了嵌入式和云计算的课程。