SOYNET, established in South Korea in 2018, is a software-based inference accelerator developer. Our proprietary solution, SoyNet, provides model optimization for deep learning. We have also introduced Model Market, the first-ever marketplace for SoyNet-optimized models. These deep learning models are, on average, 6 times faster and consume around 3 times less memory than public frameworks like TensorFlow, Pytorch and TensorRT. With the help of NVIDIA’s SDK, SoyNet ensures the optimized models consume significantly less GPU memory so that you can run multiple models on a lower end GPU. SoyNet’s optimized models are provided in a bin folder/Docker file that can be quickly executed and deployed on cloud, on premises or on edge devices. Using the 5-step API process, the optimized models are easily integrated with C++, Java or Python applications.

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SoyNet, a Fast and Affordable Solution for Inference Optimization

This blog post was originally published by SOYNET. It is reprinted here with the permission of SOYNET. To deliver the best end-user experience for your consumers, lower the cost of AI installations, and increase ROI for your AI initiatives, AI inference performance at scale is crucial. Currently, businesses face many problems in implementing AI in …

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