Reduction in the number of GPUs! Enables training of large networks without increasing the required number of GPUs.
There is a problem of insufficient GPU memory for training large deep learning networks, while GPUs are expensive compared to HDDs and DRAM, making expansion difficult. By utilizing other hardware, it is possible to train large networks using only a single GPU. 【Technical Details】 ■ Data transfer to HDD using CUDA Unified Memory - Users can transfer data from GPU memory to Host memory without being aware of the transfer. - A technology has been implemented to transfer data to HDD when Host memory is insufficient by extending the Nvidia Driver. ■ Analysis of computational graphs - Development of a technology that keeps only the necessary data in the GPU, moving the rest to Host memory or storage, and transferring it back to the GPU when it is likely to be needed for computation. *For more details, please download the PDF or feel free to contact us.
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Smart Group provides a diverse range of high-quality IT services to customers in the manufacturing industry, particularly in the automotive sector, with "ENGINEERING × VISUALIZATION" as its core competence. Leveraging the group's comprehensive capabilities, we pride ourselves on our ability to flexibly respond to various needs while aiming to enrich future living and actively challenging new fields. ■ Smartscape Inc. Engaged in the development of information systems that support design, manufacturing, production, and sales, as well as the development and sale of products characterized by efficiency tools, IoT, AI development, UI/UX design development, and 3D technology. ■ Smart Engineer Inc. Offers system service business that stably supports IT infrastructure and a new technology development business represented by content production using 3DCG, the metaverse, and XR. ■ Smart Implement Inc. Provides engineering services that demonstrate high technical capabilities in areas such as vehicle control system development.
