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  6. Manufacturing Industry: PC for SOM Product Implementation

Manufacturing Industry: PC for SOM Product Implementation

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last updated:Feb 02, 2026

アプライド
アプライド
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This is a guide to the optimal PC for implementing self-driving robots into SOM products within autonomous driving systems!

<Flow of hardware aspects to realize autonomous mobile robots and autonomous driving systems> 1. AI processing using HPC (learning and optimization) Utilizing HPC environments with vast computational resources (such as GPU clusters and supercomputers) for model training and optimization for edge deployment. 2. Build and deploy to SOM products The optimized model is embedded into a specific SOM and operated in a real environment. Here is a recommendation for the optimal PC during the above build process!

    Desktop PC
SOM.png

Manufacturing Industry: PC for SOM Product Implementation

SOM.png
SOM.png
  • Special site - Product/service details - https://pr.mono.ipros.com/applied/product/

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In the build of SOM (System on Module) products, the selection and optimization of memory capacity is one of the most important factors for the stable operation, performance, and overall product lifecycle of the system. If the memory capacity is insufficient, the speed of the entire system will drastically decrease. Therefore, in this PC, we have chosen a model that pays attention to both memory capacity and CPU performance!

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P5

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Please contact us for details

Applications/Examples of results

1. AI processing using HPC (learning and optimization) Utilizing HPC environments with vast computational resources (such as GPU clusters and supercomputers), we perform model training and optimization for edge deployment. 2. Build and deploy to SOM products The optimized model is integrated into specific SOMs and operated in real environments. Targeted SOMs: AMD (Xilinx) Kria SOM (K26/K24, etc.): Powerful inference capabilities based on FPGA (Vitis AI environment). NVIDIA Jetson series (Orin/Xavier): Fast inference based on GPU (using TensorRT). NXP S32G, etc.: Automotive processors for in-vehicle use. Build process: Hardware-in-the-loop (HIL): Connect the SOM board to a PC to verify that the built model operates correctly on the actual hardware. SDK/toolchain: Use manufacturer-provided tools (Vitis AI, NVIDIA DeepStream/TensorRT) to create edge applications.

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The optimal PC for implementing SOM products.

The optimal PC for implementing SOM products.

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アプライド

アプライド

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Applied Corporation is a computer manufacturing company based in Hakata-ku, Fukuoka City, Fukuoka Prefecture, with 65 locations nationwide. We provide the latest business proposals, from cutting-edge computers to the implementation of DX and solutions, for corporate clients across the country.

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