Opportunistic Computing: A New Paradigm for Scalable Programming on Multicore Processors

多核处理器个人计算平台的引入，如台式机、笔记本电脑和游戏机，为终端用户打开了有趣的应用可能性，使并行比以往任何时候都更加普遍。趋势显示，身临其境的多媒体和游戏应用程序越来越多地出现在较新的个人计算平台上。这类应用程序的理想特征之一是，这些应用程序根据其执行平台的资源丰富性表现出不同程度的复杂程度。当前的编程范例在表达可以动态扩展到资源可用性的应用程序的可变语义的能力方面受到限制。这种限制导致了巨大的障碍，导致应用程序随着平台的出现而缓慢发展。另一方面，多核处理器正在快速发展，如果无法使用额外的核心，它们的价值将严重缩水。为了弥合这一差距，重要的是开发语言和编译器技术，以提供应用程序语义与处理器能力的扩展。这项工作研究了一种新的范例，称为机会主义计算，它允许在应用程序中指定可扩展的语义，该规范可以丰富，从而适应运行时可用资源的数量。涉及C++扩展的领域特定编程语言允许程序员定义如何机会主义地丰富程序的当前语义的规范。它可以采取额外计算的形式，在运行时为给定的结果质量选择最佳计算，或者将当前计算调整为更好的计算。这项工作开发和研究了新的分析和技术，用于在编译器控制下管理运行时和软件事务存储器，并结合编译器控制的软实时任务调度。

The introduction of multi-core processors personal computing platforms such as desktops, laptops and game consoles open up interesting end-user application possibilities making parallelism more ubiquitous than ever. Trends show an increasing presence of immersive multimedia and gaming applications on newer personal computing platforms. One of the desirable features of such applications is that the applications exhibit varying degrees of sophistication based on the resource-richness of the platform on which they execute. Current programming paradigms are limited in their ability to express variable semantics of applications that could scale dynamically to the resource availability. This limitation leads to huge barriers causing applications to evolve slowly as the platforms emerge. On the other hand, multi-core processors are rapidly evolving and if one is unable to use the extra cores their value will be severely diminished. In order to bridge this gap, it is important to develop languages and compiler technology that offers a scaling of application semantics with the processor power.This work investigates a new paradigm, called Opportunistic Computing, that allows a specification of scalable semantics in applications that can be enriched and thus adapt to the amount of available resources at runtime. A domain specific programming language involving extensions to C++ allows the programmer to define a specification of how the current semantics of a program can be opportunistically enriched. It can take the form of an additional computation, the choice of the best computation at runtime for a given quality of result or the adaptation of the current computation into a better one. The work develops and investigates new analyses and techniques for managing the runtime and software transactional memory under compiler control coupled with the compiler controlled scheduling of soft real-time tasks.