CAREER: Advancing the Frontier in System Architectures for Artificially Intelligent Services and Applications

社会与当今移动的技术的互动方式正在迅速改变，因为这些设备在我们的生活中无处不在，变得越来越个性化和知识化。智能助理（IA），如苹果的Siri，谷歌的Google Now，微软的Cortana和亚马逊的Echo，正在继续变得更加复杂，并且随着可穿戴设备继续获得吸引力，预计将越来越受欢迎。支持这些技术趋势所需的计算能力继续朝着智能系统发展，这些系统在音频和视觉交互的关键路径上使用复杂的机器学习和计算机视觉算法。在这项拟议的工作中，PI Jason Mars旨在了解未来的云和移动的系统应该如何设计（和共同设计），以支持用户不断增长的需求。这项拟议的工作推进了以下两个方面：1）当前计算平台的效率，以降低其能源，成本和环境足迹，2）扩展开放的端到端系统，具有最先进的算法功能，以实现新的，更复杂的智能技术，并迎来未来的研究和调查。PI Mars的技术方法包含三大创新支柱。这些支柱涵盖应用洞察，为基础系统的设计提供信息，垂直创新为新兴应用和服务推进系统堆栈的跨层设计，水平创新为跨越移动的硬件和云硬件的计算结构提供理由，以创建统一的计算平台。除了对国家利益、经济发展和技术产生影响外，这项拟议的工作还在本科和研究生教育方面进行了重大创新。本提案中描述的Intelleo和DeepSirius系统将用于设计最先进的数据中心设计的本科生和研究生课程。此外，所有文物和教学材料将通过开放源码和创造性共享广泛传播。

The way society interacts with today's mobile technologies is rapidly changing as such devices - omnipresent in our lives - become increasingly personal and knowledgeable. Intelligent assistants (IAs), such as Apple's Siri, Google's Google Now, Microsoft's Cortana, and Amazon's Echo, are continuing to become more sophisticated and are expected to grow in popularity as wearables continue to gain traction. The computing capabilities required to support these technology trends continue to evolve toward intelligent systems that use sophisticated machine learning and computer vision algorithms on the critical path of audio and vision interactions. In this proposed work, PI Jason Mars aims to understand how future cloud and mobile systems should be designed (and co-designed) to support increasing demand from users. This proposed work advances both 1) the efficiency of current computing platforms to reduce their energy, cost, and environmental footprint, and 2) the expansion of open end-to-end systems with state-of-the-art algorithmic capabilities to enable new, more sophisticated, intelligent technologies and usher in future research and inquiry. PI Mars' technical approach incorporates three pillars of innovation. These pillars span application insights, to inform the design of underlying systems, vertical innovation to advance the cross-layer design of the system stack for emerging applications and services, and horizontal innovation to reason about a computational fabric spanning mobile hardware and cloud hardware to create a unified platform for computation. In addition to having impact on national interests, economic advancement, and technology in general, this proposed work incorporates significant innovation in undergraduate, and graduate education. The Intelleco and DeepSirius systems described in this proposal will be used to design an undergraduate and graduate course for state-of-the-art datacenter design. In addition all artifacts and teaching materials will be disseminated broadly through open source and creative commons.