Multi-mode CORDIC processor on a dynamically reconfigurable array

Author(s):  
Qimua Fu ◽  
Dong Wang ◽  
Xiaoming Ding
Author(s):  
Christian Plessl ◽  
Marco Platzner

Numerous research efforts in reconfigurable embedded processors have shown that augmenting a CPU core with a coarse-grained reconfigurable array for application-specific hardware acceleration can greatly increase performance and energy-efficiency. The traditional execution model for such reconfigurable co-processors however requires the accelerated function to fit onto the reconfigurable array as a whole, which restricts the applicability to rather small functions. In the authors’ research presented in this chapter, the authors have studied hardware virtualization approaches that overcome this restriction by leveraging dynamic reconfiguration. They present two different hardware virtualization methods, virtualized execution and temporal partitioning, and introduce the Zippy reconfigurable processor architecture that has been designed with specific hardware virtualization support. Further, the authors outline the corresponding hardware and software tool flows. Finally, the authors demonstrate the potential provided by hardware virtualization with two case studies and discuss directions for future research.


Author(s):  
Teng Long ◽  
Zhu Yang ◽  
Bingyi Li ◽  
Liang Chen ◽  
Zegang Ding ◽  
...  

With the development of satellite load technology and very-large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. Limited by severe size, weight, and power consumption constraints, a key challenge of on-board SAR imaging system design is to achieve high real-time processing performance. In addition, with the rise of multi-mode SAR applications, the reconfiguration of the on-board processing system is beginning to receive widespread attention. This paper presents a multi-mode SAR imaging chip with SoC architecture based on the reconfigurable double-operation engines and multilayer switching network. We decompose the commonly used extend chirp scaling (CS) SAR imaging algorithm into 8 types of double-operation engines according to the computing orders, and design a three-level switching network to connect these engines for data transition. The CPU is responsible for engine scheduling based on data flow driven with instructions to implement each part of the CS algorithm. Thus, multi-mode floating-point SAR imaging processing can be integrated into a single Application-Specific Integrated Circuit (ASIC) chip instead of relying on distributed technologies. As a proof of concept, a prototype measurement system with chip-included board is implemented, and the performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. A chip requires 9.2 s, 50.6 s and 7.4 s for a stripmap with 16,384×16,384 granularity, multi-channel stripmap with 65.536×8192 granularity and multi-channel scan mode with 32,768×4096 granularity and 6.9 W for the system hardware to process the SAR raw data.


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