Industry-leading! High precision of NLP using HDD.
We will implement state-of-the-art algorithms, integrate them into the network, and aim for acceleration!
In the field of NLP, one approach to improving accuracy is the introduction of memory layers. However, storing a large amount of memory can lead to the problem of slow retrieval times. To solve this, by accelerating approximate nearest neighbor search, it is possible to enhance the network's accuracy! 【Technical Details】 ■ Acceleration of Faiss - Implement state-of-the-art algorithms and aim for acceleration by integrating them into the network. ■ Development of approximate nearest neighbor search algorithms - Further tune Faiss to aim for overall acceleration during training. *For more details, please download the PDF or feel free to contact us.
basic information
【Goal Image】 ■High precision of NLP networks By accelerating approximate nearest neighbor search, it becomes possible to utilize a massive memory layer. ■Efficient use of storage By storing memory not only in the GPU but also in storage, we aim to improve accuracy while minimizing GPU memory consumption. *For more details, please download the PDF or feel free to contact us.
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For more details, please download the PDF or feel free to contact us.
