Image processing algorithms implemented using custom hardware or FPGAs of can be orders-of-magnitude more energy efficient and performant than software. Unfortunately, converting an algorithm by hand to a hardware description language suitable for compilation on these platforms is frequently too time consuming to be practical. Recent work on hardware synthesis of high-level image processing languages demonstrated that a single-rate pipeline of stencil kernels can be synthesized into hardware with provably minimal buffering. Unfortunately, few advanced image processing or vision algorithms fit into this highly-restricted programming model. In this paper, we present Rigel1, which takes pipelines specified in our new multi-rate architecture and lowers them to FPGA implementations. Our flexible multi-rate architecture supports pyramid image processing, sparse computations, and space-time implementation tradeoffs. We demonstrate depth from stereo, Lucas-Kanade, the SIFT descriptor, and a Gaussian pyramid running on two FPGA boards. Our system can synthesize hardware for FPGAs with up to 436 Megapixels/second throughput, and up to 297× faster runtime than a tablet-class ARM CPU.
CITATION STYLE
Hegarty, J., Daly, R., De Vito, Z., Ragan-Kelley, J., Horowitz, M., & Hanrahan, P. (2016). Rigel: Flexible multi-rate image processing hardware. In ACM Transactions on Graphics (Vol. 35). Association for Computing Machinery. https://doi.org/10.1145/2897824.2925892
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