InTrans: A virtualized SoC platform architecture for mini autonomous drones

在RoboBees项目最新成果的基础上，该INTRANS项目探索了新计算模式的设计，这些模式能够在能源和重量受限的广泛应用中实现可扩展的性能和能效，从微型自主无人机(例如，RoboBees)到更大的小型飞行机器人。追求高能效的计算性能仍然是一个重要的目标，但计算模式会随着时间的推移而不断发展。对移动性和便携性的需求催生了笔记本电脑，然后是更小的智能手机，它们将昔日电脑的功能和性能打包在手中。随着物联网(IoT)设备和小型无人机的激增，技术正处于另一种范式转变的尖端。尽管人们认为cmos技术的规模正在进入平台期，但这些应用对节能计算的要求越来越高，外形尺寸也越来越小，这就要求电路、体系结构和系统进入一个新时代。一个极端的例子是哈佛大学的RoboBees项目，该项目致力于创造一群自主机器人蜜蜂：500 mg、昆虫大小的扑翼机器人，具有足够的感知、计算和驱动能力，以实现自主飞行。这个由美国国家科学基金会资助的项目设计、实施并测试了一种“大脑芯片”，它满足了严格的重量和实时计算要求。它包括一个通用核心，带有一系列专用硬件加速器，用于自主飞行所需的特定传感、图像处理和控制算法。虽然与仅使用通用内核的芯片相比，该芯片显著提高了功率和性能，但组合了多个一次性加速器的平台不能灵活地应对计算需求的后续变化。未来用于自主无人机的计算系统必须随时适应和适应不断变化的工作负载和应用需求。一个很有前途的研究方向是开发一个由可组合加速器构建的虚拟化平台体系结构，该加速器可以通过虚拟化提供可扩展性。换句话说，下一代计算系统将包括足够灵活的计算元素，以跨一系列应用程序运行，同时保留专业化的好处。通过与英特尔研究人员的密切合作，该INTRANS项目将(1)在结合了传感、计算和驱动的各种嵌入式系统中确定有趣的目标应用程序，以及(2)开发和演示新的计算机体系结构，这些体系结构可以轻松地在各种平台和系统限制下扩展性能和能耗。

Building on recent results from the RoboBees project, this InTrans project explores the design of new computing modalities that enable scalable performance and energy efficiency across a wide range of energy- and weight-constrained applications, from miniature autonomous drones (e.g., RoboBees) to larger small-scale flying robots. The pursuit of energy-efficient compute performance remains an important objective, but computing modalities continue to evolve over time. Demand for mobility and portability led to laptops and then to smaller smart phones that pack the functionality and performance of yesterday's computer into one's hand. Technology is now at the cusp of another paradigm shift with the proliferation of "internet of things" (IoT) devices and small-scale drones. Despite the perception that CMOS technology scaling is reaching a plateau, these applications require ever higher levels of energy-efficient computing with ever shrinking form factors, demanding a new era of circuits, architectures, and systems.One extreme example is the RoboBees project at Harvard, which set out to create a colony of autonomous robotic bees: 500mg, insect-sized, flapping-wing robots with sufficient sensing, computing, and actuation to achieve autonomous flight. This NSF-funded project designed, implemented, and tested a "brain chip" that met severe weight and real-time computation requirements. It comprises a general-purpose core with a collection of dedicated hardware accelerators for the specific sensing, image processing, and control algorithms needed for autonomous flight. While this chip significantly improves power and performance compared to those only using general-purpose cores, a platform that combines multiple one-off accelerators is inflexible to subsequent changes in computing needs. Future computing systems for autonomous drones must readily accommodate and adapt to changing workloads and application needs. A promising research direction is to develop a virtualized platform architecture constructed out of composable accelerators that can provide scalability via virtualization. In other words, next-generation computing systems will comprise computing elements flexible enough to operate across a range of applications while retaining the benefits of specialization. Via close collaboration with researchers at Intel, this InTrans project will (1) identify interesting applications to target within the broad range of embedded systems that combine sensing, computing, and actuation and (2) develop and demonstrate new computer architectures that readily scale performance and energy consumption across a broad range of platforms and system constraints.