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MAY-JUN 2019

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SYSTEM INTEGRATION INTECH MAY/JUNE 2019 27 every camera comes fitted with a dedicated ASIC chip. These high-end cameras cannot be repur- posed for any other application. To make matters worse, inspection processes and packaging in manufacturing facilities are modified from time to time. Tweaking the vision inspection system to work with the new processes or packaging requires extensive and expensive modifications. Given these limitations, machine vision sys- tems must be designed so they can be reused for multiple applications and easily modified to meet changing product designs, manufacturing pro - cesses, varying components, and business needs. Reconfigurable computing is the best bet Selection of computing platforms for automa- tion tasks is often governed by the trade-off between two important parameters: efficiency and flexibility. The search for a balance between the approaches brings us to reconfigurable computing. Reconfigurable systems are imple - mented with programmable logic. The best part is that hardware circuits can be easily upgraded to meet the demands of fresh or modified vision applications. Processors with a fixed architecture allow the user to temporarily compose the operations pro- vided by the arithmetic logic unit (ALU). ASIC processors are implemented by spatially compos- ing dedicated functional units. Reconfigurable computing uses both temporal and spatial com- position—that is, these systems typically have a programmable hardware logic and a group of programmable interconnection networks. There are several approaches available to accomplish a reconfigurable computing system: ● fine-grained systems: FPGAs and logic gates as programmable elements, connected by switches and wires ● coarse-grained systems: software-configu- rable processors and a programmable net- work on chips ● heterogeneous reconfigurable systems: a combination of fine-grained and coarse- grained elements The ramifications are awesome. Take a tradi- tional packaging vision system that comes with a prefed ASIC in a dedicated camera setup. If the product packaging were changed, new patterns and components were added, or the text on the package was modified, we would need a new ASIC chip for every production line in every manufac- turing plant of this company. The costs and time involved in design, fabrication, testing, and roll- out are massive. On the other hand, with reconfigurable com- puting, the camera system can be trained to ac- commodate modifications to the packaging or the inspection process. Ideal reconfigurable computing platform Whatever the approach may be, configuration management and development systems are inte- gral parts of a reconfigurable computing platform. There are a variety of choices when considering the development of a reconfigurable system. Some of the critical elements to bear in mind when im- plementing a task on reconfigurable systems are: ● Overhead for run-time reconfiguration: How much additional work needs to be done to use the flexibility offered by the reconfigurable systems? ● Configuration granularity: To what level can an algorithm be decomposed during the imple- FAST FORWARD ● Legacy vision systems are limited by the need for a dedicated design architecture for every application. This is expensive and not scalable. ● We can now deploy reconfigurable machine vision systems that are reus- able for multiple applications and can be easily modified for changing product designs, manufacturing processes, varying components, and business needs. ● Advanced AI and deep learning tools have taken this one step further by augmenting machines with the intelligence to make right decisions based on the images captured. Concept of reconfigurable computing Composition of a reconfigurable system Configuration memory RC device ASIC Data Data Processor Processor Program Data RC ASIC Application Software environment Development system Configuration management Reconfigurable computing engine HDL Compiler CAD tools

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