SHF: Small: Accelerating Asynchronous Programs through Synergistic Hardware/Software Customization

标题：SHF：Small：通过协作式硬件/软件定制加速异步程序今天构建的计算系统中有很大一部分使用异步编程来提高人机交互性能。所有的Web 2.0 JavaScript应用程序(例如，Gmail、Facebook)都使用异步编程。苹果应用商店和Google Play之间现在有200多万个移动应用程序可用，这些应用程序都是使用异步编程编写的。物联网(IoT)、嵌入式系统、传感器网络、桌面图形用户界面应用等都依赖于异步编程模型来确保快速响应。尽管异步编程的使用无处不在，但今天的通用处理器体系结构已经针对同步编程模型进行了大量优化。该项目的智能优势是一套名为EBOOST(Event Boost)的硬件和软件协同优化，可以缩短响应时间并节省能源。该项目更广泛的意义和重要性是对Web2.0和移动设备等异步平台功能的改进。此外，该项目还支持多样性和推广工作，如面向高中生的MiBytes计算机夏令营。EBOOST优化定制了计算堆栈，以利用异步程序的独特特征。在异步编程模型中，计算作为事件发布到事件队列中，在线程中从事件队列中异步处理计算。这些事件在很大程度上相互独立。EBOOST通过将事件队列暴露给处理器来利用这种潜在的事件级并行性(ELP)。此外，EBOOST估计事件的关键程度，并使用它来确定关键事件的优先顺序，甚至可以跳过不重要的事件，以改善用户体验和节省能源。该项目还在构建一组用于评估异步程序的基准。

Title: SHF: Small: Accelerating Asynchronous Programs through Synergistic Hardware/Software CustomizationA huge fraction of computing systems built today use asynchronous programming to improve human-computer interactive performance. All the Web 2.0 JavaScript applications (e.g., Gmail, Facebook) use asynchronous programming. There are now more than two million mobile applications available between the Apple App Store and Google Play, which are all written using asynchronous programming. Internet-of-Things (IoT), embedded systems, sensor networks, desktop GUI applications, etc., all rely on the asynchronous programming model for ensuring quick responsiveness. In spite of the ubiquitous use of asynchronous programming, today's general-purpose processor architectures are heavily optimized for the synchronous programming model. The intellectual merits of this project are a set of synergistic hardware and software optimizations named as eBoost (event Boost) that improve response time and save energy. The project's broader significance and importance are improvements to the capabilities of asynchronous platforms such as Web 2.0 and mobile devices. Furthermore, the project is supporting diversity and outreach efforts such as the MiBytes Computer Camp for high school students.The eBoost optimizations customize the computing stack for exploiting the unique characteristics of asynchronous programs. In the asynchronous programming model, computations are posted as events to an event queue from where they get processed asynchronously in a thread. These events are largely independent of each other. eBoost exploits this latent event-level parallellism (ELP) by exposing the event queue to the processor. Furthermore, eBoost estimates the criticality of events, and uses it to prioritize critical events or may even skip unimportant events to improve user experience and save energy. This project is also constructing a set of benchmarks for evaluating asynchronous programs.