An Interpolating Memory Unit for Function Evaluation: Analysis and Design
IEEE Transactions on Computers
Wattch: a framework for architectural-level power analysis and optimizations
Proceedings of the 27th annual international symposium on Computer architecture
Digital Image Warping
Combined DRAM and logic chip for massively parallel systems
ARVLSI '95 Proceedings of the 16th Conference on Advanced Research in VLSI (ARVLSI'95)
SIGGRAPH '83 Proceedings of the 10th annual conference on Computer graphics and interactive techniques
Understanding Digital Signal Processing (2nd Edition)
Understanding Digital Signal Processing (2nd Edition)
Accelerating Compute-Intensive Applications with GPUs and FPGAs
SASP '08 Proceedings of the 2008 Symposium on Application Specific Processors
Accelerating the Nonuniform Fast Fourier Transform Using FPGAs
FCCM '10 Proceedings of the 2010 18th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines
An algorithm-architecture co-design framework for gridding reconstruction using FPGAs
Proceedings of the 48th Design Automation Conference
Measuring the Gap Between FPGAs and ASICs
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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In this paper we present a local interpolation-based variant of the well-known polar format algorithm used for synthetic aperture radar (SAR) image formation. We develop the algorithm to match the capabilities of the application-specific logic-in-memory processing paradigm, which off-loads lightweight computation directly into the SRAM and DRAM. Our proposed algorithm performs filtering, an image perspective transformation, and a local 2D interpolation, and supports partial and low-resolution reconstruction. We implement our customized SAR grid interpolation logic-in-memory hardware in advanced 14 nm silicon technology. Our high-level design tools allow to instantiate various optimized design choices to fit image processing and hardware needs of application designers. Our simulation results show that the logic-in-memory approach has the potential to enable substantial improvements in energy efficiency without sacrificing image quality.