Tackling computationally challenging problems with high efficiency often requires the combination of algorithmic innovation, advanced architecture, and thorough exploitation of parallelism. We demonstrate this synergy through synthetic aperture radar (SAR) via backprojection, an image reconstruction method that can require hundreds of TFLOPS. Computation cost is significantly reduced by our new algorithm of approximate strength reduction; data movement cost is economized by software locality optimizations facilitated by advanced architecture support; parallelism is fully harnessed in various patterns and granularities. We deliver over 35 billion backprojections per second throughput per compute node on an Intel® Xeon® processor E5-2670-based cluster, equipped with Intel® Xeon Phi™ coprocessors. This corresponds to processing a 3K×3K image within a second using a single node. Our study can be extended to other settings: backprojection is applicable elsewhere including medical imaging, approximate strength reduction is a general code transformation technique, and many-core processors are emerging as a solution to energy-efficient computing.

中文翻译：

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具有多核处理器的基于高效反投影的合成孔径雷达计算

要高效地解决计算难题，通常需要结合算法创新，先进的体系结构和对并行性的充分利用。我们通过合成孔径雷达（SAR）通过反投影展示了这种协同作用，这是一种可能需要数百个TFLOPS的图像重建方法。我们的近似强度折减新算法大大降低了计算成本；先进的架构支持促进了软件局部性优化，从而节省了数据移动成本；并行性在各种模式和粒度中得到了充分利用。在配备了英特尔®至强融核™协处理器的基于英特尔®至强®处理器E5-2670的集群上，每个计算节点每秒可提供超过350亿个反投影吞吐量。这对应于使用单个节点在一秒钟内处理3K×3K图像。我们的研究可以扩展到其他设置：反投影可应用于包括医学成像在内的其他地方，近似强度降低是一种通用的代码转换技术，并且许多核处理器正在成为节能计算的解决方案。