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A 32x32 Time-Domain Wavefront Computing Accelerator for Path Planning and Scientific Simulations

机译:用于路径规划和科学仿真的32x32时域波前计算加速器

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Recent hardware accelerators based on FPGA –[2] and ASIC –[4] have demonstrated high throughput and energy-efficient processing of path planning for applications, including the manipulation of arm-robots on a high-resolution map [1] and the autonomous navigation of battery-powered micro-robots [4]. The accelerators have focused on demonstrating the modified shortest path planning algorithms, such as extended-stride A$st$ [1] and dual-tree rapid-exploring random tree (RRT) [4], and achieved much higher throughput and energy efficiency (two-to-three orders of magnitude higher) than traditional implementations with CPU and GPU. A two-dimensional processing element (PE) array [5] was proposed as an alternative computing paradigm for searching the shortest path based on the expansion of wavefront in the time-domain. The time-domain delay accumulation was used for finding the shortest paths by accumulating time delays while propagating through the PEs that correspond to the pixels in a two-dimensional searching space. However, it still follows the existing A$st$ algorithm using an extra gradient control circuit with resistor ladders to estimate the remaining distances, resulting in inaccurate results (i.e. sub-optimal paths) with extra hardware and energy overhead.
机译:基于FPGA - [2]和ASIC - [4]的最近的硬件加速器已经证明了用于应用的路径规划的高吞吐量和节能处理,包括在高分辨率地图[1]和自主的手臂机器人的操纵电池供电的微机器人导航[4]。加速器专注于展示改进的最短路径规划算法,例如延长步伐A $ AST $ [1]和双树快速探索随机树(RRT)[4],并实现了更高的吞吐量和能量效率(比具有CPU和GPU的传统实现高出二到三个数量级。提出了一种二维处理元件(PE)阵列[5]作为用于在时域中的波前的扩展的基于波前的扩展来搜索最短路径的替代计算范例。时域延迟累积用于通过累积时间延迟来找到最短路径,同时传播通过对应于二维搜索空间中的像素的PE的PE。然而,它仍然遵循现有的$ ast $算法使用额外的梯度控制电路,该电阻梯子估计剩余的距离,从而导致具有额外硬件和能量开销的结果不准确的结果(即次优路)。

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