CISE:CNS:EAGER: Exploring Managed Soft Computing for Data Intensive Applications

计算中的不准确性通常被认为具有负面含义，因此，传统计算系统的设计具有严格的正确性概念。然而，不准确或近似并不总是不好的，因为几个应用程序域本质上容忍不同程度的准确性松弛，因此，可以利用这种属性来显著提高应用程序性能或容错性。这个EAGER项目的动机是研究在数据密集型应用程序中利用这种近似（也称为“软计算”）来预测性能-功率-精度权衡的可行性。这项研究包括三个相互交织的任务。第一个任务将检查各种高性能计算（HPC）和MapReduce风格的数据分析应用程序，并确定哪类应用程序适合软计算。研究的第二个组成部分旨在开发促进软计算的适当技术，而最后一个任务侧重于检查开发用于形式化各种权衡分析的控制理论模型的可能性。该项目旨在证明，通过软计算可以为各种数据密集型应用程序获得显著的功率和性能。本研究中采用的方法有可能影响许多科学和商业应用程序的编程范式，以优化电源性能行为。这项研究的交叉性质有可能在几个领域培养新的研究方向，包括高性能计算、计算机体系结构、编译器和系统/应用软件。参与本研究的本科生和研究生将在多个领域得到全面的培训。本研究开发的软件工具将用于现有课程和新课程的教学，并将向公众开放。

Inaccuracy in computation has usually been considered with a negative connotation and, therefore,conventional computing systems have been designed with a strict notion of correctness.However, inaccuracy or approximation is not always bad since several application domainsare intrinsically tolerant to varying degrees of relaxation in accuracy,and thus, such a property can be exploited for significant gain in application performance or fault-tolerance.The motivation of this EAGER project is to investigate the feasibility of utilizing such approximation,also known as "soft computing", for data-intensive applications for predicting the performance-power-accuracytrade-offs. The research consists of three intertwined tasks. The first task would examine a variety ofhigh performance computing (HPC) and MapReduce style data analytic applications, and determinewhich classes of applications are suitable for soft computing.The second component of the research is aimed at developing appropriate techniques for facilitatingsoft computing, while the last task focuses on examining the possibility of developing a control theoreticmodel for formalizing the various tradeoff analysis.This project aims at demonstrating that it is possible to achieve significant power and performancegain for a wide variety of data intensive applications through soft computing. The approach adopted in this research has the potential to influence the programming paradigm for manyclasses of scientific and business applications for optimizing the power-performance behavior.The cross-cutting nature of this research has potential to foster new research directions in several areas,spanning high performance computing, computer architecture, compilers, and system/application software.Undergraduate and graduate students involved in this research will get versatile training in several areas.The software tools developed in this research will be used in teachingexisting and new courses, and will be made publicly available.