A must-see for those struggling with GPU memory shortages! Efficient use of hardware using AI.
Reduction in the number of GPUs! It will be possible to train 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 computation graphs - Development of a technology that keeps only the necessary data in the GPU, moving others to Host memory or storage, and transferring them back to the GPU when computation is likely needed. *For more details, please download the PDF or feel free to contact us.
basic information
For more details, please download the PDF or feel free to contact us.
Price range
Delivery Time
Applications/Examples of results
For more details, please download the PDF or feel free to contact us.
