The wide acceptance and data deluge in medical imaging processing require faster and more efficient systems to be built.Due to the advances in heterogeneous architectures recently,there has been a resurgence in the fi...The wide acceptance and data deluge in medical imaging processing require faster and more efficient systems to be built.Due to the advances in heterogeneous architectures recently,there has been a resurgence in the first research aimed at FPGA-based as well as GPGPU-based accelerator design.This paper quantitatively analyzes the workload,computational intensity and memory performance of a single-particle 3D reconstruction application,called EMAN,and parallelizes it on CUDA GPGPU architectures and decouples the memory operations from the computing flow and orchestrates the thread-data mapping to reduce the overhead of off-chip memory operations.Then it exploits the trend towards FPGA-based accelerator design,which is achieved by offloading computingintensive kernels to dedicated hardware modules.Furthermore,a customized memory subsystem is also designed to facilitate the decoupling and optimization of computing dominated data access patterns.This paper evaluates the proposed accelerator design strategies by comparing it with a parallelized program on a 4-cores CPU.The CUDA version on a GTX480 shows a speedup of about 6 times.The performance of the stream architecture implemented on a Xilinx Virtex LX330 FPGA is justified by the reported speedup of 2.54 times.Meanwhile,measured in terms of power efficiency,the FPGA-based accelerator outperforms a 4-cores CPU and a GTX480 by 7.3 times and 3.4 times,respectively.展开更多
SRAM(static random access memory)-based FPGA(field programmable gate array), owing to its large capacity, high performance, and dynamical reconfiguration, has become an attractive platform for So PC(system on programm...SRAM(static random access memory)-based FPGA(field programmable gate array), owing to its large capacity, high performance, and dynamical reconfiguration, has become an attractive platform for So PC(system on programmable chip) development. However, as the configuration memory and logic memory of the SRAM-based FPGA are highly susceptible to SEUs(single-event upsets) in deep space, it is a challenge to design and implement a highly reliable FPGA-based system for spacecraft, and no practical architecture has been proposed. In this paper, a new architecture for a reliable and reconfigurable FPGAbased computer in a highly critical GNC(guidance navigation and control) system is proposed. To mitigate the effect of an SEU on the system, multi-layer reconfiguration and multi-layer TMR(triple module redundancy) techniques are proposed, with a reliable reconfigurable real-time operating system(Space OS) managing the system level fault tolerance of the computer in the architecture. The proposed architecture for the reconfigurable FPGA-based computer has been implemented with COTS(commercial off the shelf) FPGA and has firstly been applied to the GNC system of a circumlunar return and reentry flight vehicle. The in-orbit results show that the proposed architecture is capable of meeting the requirements of high reliability and high availability, and can provide the expressive varying functionality and runtime flexibility for an FPGA-based GNC computer in deep space.展开更多
基金Supported by the National Basic Research Program of China(No.2012CB316502)the National High Technology Research and DevelopmentProgram of China(No.2009AA01A129)the National Natural Science Foundation of China(No.60921002)
文摘The wide acceptance and data deluge in medical imaging processing require faster and more efficient systems to be built.Due to the advances in heterogeneous architectures recently,there has been a resurgence in the first research aimed at FPGA-based as well as GPGPU-based accelerator design.This paper quantitatively analyzes the workload,computational intensity and memory performance of a single-particle 3D reconstruction application,called EMAN,and parallelizes it on CUDA GPGPU architectures and decouples the memory operations from the computing flow and orchestrates the thread-data mapping to reduce the overhead of off-chip memory operations.Then it exploits the trend towards FPGA-based accelerator design,which is achieved by offloading computingintensive kernels to dedicated hardware modules.Furthermore,a customized memory subsystem is also designed to facilitate the decoupling and optimization of computing dominated data access patterns.This paper evaluates the proposed accelerator design strategies by comparing it with a parallelized program on a 4-cores CPU.The CUDA version on a GTX480 shows a speedup of about 6 times.The performance of the stream architecture implemented on a Xilinx Virtex LX330 FPGA is justified by the reported speedup of 2.54 times.Meanwhile,measured in terms of power efficiency,the FPGA-based accelerator outperforms a 4-cores CPU and a GTX480 by 7.3 times and 3.4 times,respectively.
基金supported by the Major Special Projects on National Medium and Long-term Science and Technology Development Planning
文摘SRAM(static random access memory)-based FPGA(field programmable gate array), owing to its large capacity, high performance, and dynamical reconfiguration, has become an attractive platform for So PC(system on programmable chip) development. However, as the configuration memory and logic memory of the SRAM-based FPGA are highly susceptible to SEUs(single-event upsets) in deep space, it is a challenge to design and implement a highly reliable FPGA-based system for spacecraft, and no practical architecture has been proposed. In this paper, a new architecture for a reliable and reconfigurable FPGAbased computer in a highly critical GNC(guidance navigation and control) system is proposed. To mitigate the effect of an SEU on the system, multi-layer reconfiguration and multi-layer TMR(triple module redundancy) techniques are proposed, with a reliable reconfigurable real-time operating system(Space OS) managing the system level fault tolerance of the computer in the architecture. The proposed architecture for the reconfigurable FPGA-based computer has been implemented with COTS(commercial off the shelf) FPGA and has firstly been applied to the GNC system of a circumlunar return and reentry flight vehicle. The in-orbit results show that the proposed architecture is capable of meeting the requirements of high reliability and high availability, and can provide the expressive varying functionality and runtime flexibility for an FPGA-based GNC computer in deep space.
