NVIDIA GPU for AI, Deep Learning, Machine Learning, IoT etc
NVIDIA Tesla V100, P100, T4, P4, P40, M60 and M10 are NVIDIA’s flagship GPU products for Artificial Intelligence (AI), Deep Learning, Machine Learning and are suitable for autonomous cars, molecular dynamics, computational biology, fluid simulation, advanced physics and Internet of Things (IoT) and Big Data Analytics etc.
In the new era of AI and intelligent machines, deep learning is shaping our world like no other computing model in history. Interactive speech, visual search, and video recommendations are a few of many AI-based services that we use every day. Accuracy and responsiveness are key to user adoption for these services. As deep learning models increase in accuracy and complexity, CPUs are no longer capable of delivering a responsive user experience.
NVIDIA® Tesla products are world’s most advanced data center GPUs ever built to accelerate AI, HPC, and graphics. Powered by NVIDIA Pascal or Volta™, the latest GPU architecture, Tesla offers the performance of up to 100 CPUs in a single GPU—enabling data scientists, researchers, and engineers to tackle challenges that were once thought impossible. The two main AI functions NVIDIA Tesla help researchers with are :
Training increasingly complex models faster is key to improving productivity for data scientists and delivering AI services more quickly. Servers powered by the NVIDIA® Tesla® V100 or P100 use the performance of cut deep learning training time from months to hours.
Inference is where a trained neural network really goes to work. As new data points come in such as images, speech, visual and video search, inference is what gives the answers and recommendations at the heart of many AI services. A server with a single Tesla GPU can deliver 27X higher inference throughput than a single-socket CPU-only server resulting in dramatic cost savings.
You can buy NVIDIA Tesla GPU for major server players such as Dell, HPE, NEC, Supermicro, Tyan, Lenovo etc below. For Deep Learning servers, please visit below: