New-Tech Europe Magazine | August 2017

reVISION Stack The reVISION Stack was developed to enable Embedded Vision developers to address the four key challenges identified above, which are evident within the embedded vision sphere. These challenges can be summarized as responsivity, reconfigurability, connectivity and software defined. To address these four driving trends, the reVISION Stack combines a wide range of resources enabling platform, application and algorithm development. As such, the stack is aligned into three distinct levels: 1. Platform layer. This is the lowest level of the stack and is the one on which the remaining layers of the stack are built. As such it provides both a hardware definition of the configuration of the Zynq-7000 / Zynq UltraScale+ MPSoC and the software definition via a customized operating system to support the hardware definition. This hardware definition can define the configuration of either a development or production ready board such as a System on Module. It is within the hardware definition that the sensor and system interfaces are defined. The hardware platform will be captured using Vivado® HLX, and may leverage IP blocks from both Xilinx and third party suppliers along with the use of high level synthesis

developers All Programmable System on Chip (SoC) and Multi Processor System on Chip (MPSoC) devices from the Zynq®- 7000 and Zynq® UltraScale™+ MPSoC families to implement their solution. These devices provide high performance processors closely coupled with programmable logic, allowing the Embedded Vision developer to optimize their solution. The use of Zynq SoC or Zynq UltraScale+ MPSoC devices enable the developer to benefit from the any-to-any connectivity which comes with the use of programmable logic. This programmable logic can also implement the image processing pipeline(s), providing a performance increase due to its parallel nature. Using the programmable logic increases the system performance, connectivity and the performance per watt of power dissipated providing a more efficient solution overall. The processing cores can be used for higher level application functionality, such as decision making based on the provided information and communication between systems and with the cloud. To address the security concerns which come with autonomous and remote applications, both device families provide a secure environment with support for encrypted secure boot and ARM® Trust Zone technology within the processor, and the ability to implement anti tamper functionality. Using Zynq-7000 and Zynq UltraScale+ MPSoC devices provide significant capability to the Embedded Vision developers allowing the challenges and trends to be addressed. Leveraging these capabilities requires a development ecosystem that enables the Embedded Vision developer to utilize not only the benefits of using these devices, but also provide the ability to still use the commonly used frameworks within their solution. This is where the reVISION™ Stack comes in. use Xilinx®

to create specialist IP. This layer will also provide software drivers for IP modules and an updated PetaLinux configuration if required, to support the software defined environment at the higher level. 2. The middle level of the stack is called the algorithm layer. Development at this level takes place within the eclipse based SDSoC™ environment. SDSoC is a system optimizing compiler which allows development using a software defined environment. Crucially as we develop our software algorithms, bottlenecks in performance can be identified and removed by accelerating functions into the programmable logic. To the user this process is seamless, using a combination of High Level Synthesis and a connectivity framework to move a function from executing in software to implementation in the programmable logic. It is at this level OpenCV is used to implement the image processing algorithms for the application at hand. To reduce identified bottlenecks within the image processing algorithm, reVISION provides a wide range of acceleration ready OpenCV functions. Support is also provided at this level for the most common neural network libraries, including AlexNet, GoogLeNet, SqueezeNet, SSD, and FCN.

Figure 1 - reVISION Stack

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