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On the way to a Third Generation Real-Time Cellular Neural Network Processor

机译:在通往第三代实时蜂窝神经网络处理器的途中

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In this proceeding, the architecture of a third generation Real-Time Cellular Neural Network (CNN) Processor (RTCNNP-v3) is disclosed, which is a digital CNN emulator to be implemented on an FPGA device. The previous generation emulator, RTCNNP-v2, is the only CNN implementation reported to be capable of processing full-HD 1080p@60 (1080 x 1920 resolution at 60 Hz frame rate) video images in real-time. However, there are some weaknesses in both the design and implementation of RTCNNP-v2, like the inability to process different parts of the video images in parallel, lack of support for recording and recalling intermediate frames using external memory and it has some jitter issues at computation rates above 200 MHz. All of those issues are addressed in the next architecture of our CNN emulator, RTCNNP-v3, which is being implemented of an FPGA device.
机译:在此过程中,公开了第三代实时蜂窝神经网络(CNN)处理器(RTCNNP-v3)的架构,该架构是要在FPGA器件上实现的数字CNN仿真器。据报道,上一代仿真器RTCNNP-v2是唯一能够实时处理全高清1080p @ 60(60 Hz帧速率下的1080 x 1920分辨率)视频图像的CNN实现。但是,RTCNNP-v2的设计和实现都存在一些弱点,例如无法并行处理视频图像的不同部分,缺乏对使用外部存储器记录和调用中间帧的支持,并且存在一些抖动问题。 200 MHz以上的计算速率。所有这些问题将在我们的CNN仿真器RTCNNP-v3的下一个体系结构中解决,该体系结构由FPGA器件实现。

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