Techniques for Mapping Synthetic Aperture Radar Processing Algorithms to Multi-GPU Clusters
AIR FORCE RESEARCH LAB ROME NY INFORMATION DIRECTORATE
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This paper presents a design for parallel processing of synthetic aperture radar SAR data using multiple Graphics Processing Units GPUs. Our approach supports real-time reconstruction of a two-dimensional image from a matrix of echo pulses and their response values. Key to runtime efficiency is a partitioning scheme that divides the output image into tiles and the input matrix into a collection of pulses associated with each tile. Each image tile and its associated pulse set are distributed to thread blocks across multiple GPUs, which support parallel computation with near-optimal IO cost. The partial results are subsequently combined by a host CPU. Further efficiency is realized by the GPUs low-latency thread scheduling, which masks memory access latencies. Performance analysis quantifies runtime as a function of inputoutput parameters and number of GPUs. Experimental results were generated with 10 nVidia Tesla C2050 GPUs having maximum throughput of 972 Gflops. Our approach scales well for output reconstructed image sizes from 2,048 x 2,048 pixels to 8,192 x 8,192 pixels.
- Operations Research
- Active and Passive Radar Detection and Equipment