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      NVIDIA V100 TENSOR CORE GPU

      The Most Advanced Data Center GPU Ever Built

      七妹福利官方导航

      Welcome to the Era of AI.

      Finding the insights hidden in oceans of data can transform entire industries, from personalized cancer therapy to helping virtual personal assistants converse naturally and predicting the next big hurricane. 


      NVIDIA? V100 Tensor Core is the most advanced data center GPU ever built to accelerate AI, high performance computing (HPC), data science and graphics. It’s powered by NVIDIA Volta architecture, comes in 16 and 32GB configurations, and offers the performance of up to 32 CPUs in a single GPU. Data scientists, researchers, and engineers can now spend less time optimizing memory usage and more time designing the next AI breakthrough.

      Run AI and HPC workloads in a virtual environment for better security and manageability using NVIDIA Virtual Compute Server (vComputeServer) software

      32X Faster Training Throughput than a CPU

      ResNet-50 training, dataset: ImageNet2012, BS=256 | NVIDIA V100 comparison: NVIDIA DGX-2? server, 1x V100 SXM3-32GB, MXNet 1.5.1, container=19.11-py3, mixed precision, throughput: 1,525 images/sec | Intel comparison: Supermicro SYS-1029GQ-TRT, 1 socket Intel Gold 6240@2GHz/3.9Hz Turbo, Tensorflow 0.18, FP32 (only precision available), throughput: 48 images/sec

      AI Training

      From recognizing speech to training virtual personal assistants and teaching autonomous cars to drive, data scientists are taking on increasingly complex challenges with AI. Solving these kinds of problems requires training deep learning models that are exponentially growing in complexity, in a practical amount of time.

      With 640 Tensor Cores, V100 is the world’s first GPU to break the 100 teraFLOPS (TFLOPS) barrier of deep learning performance. The next generation of NVIDIA NVLink? connects multiple V100 GPUs at up to 300 GB/s to create the world’s most powerful computing servers. AI models that would consume weeks of computing resources on previous systems can now be trained in a few days. With this dramatic reduction in training time, a whole new world of problems will now be solvable with AI.

      SEE HOW YOU CAN ACCELERATE YOUR AI MODELS WITH MIXED PRECISION ON TENSOR CORES

      24X Higher Inference Throughput than a CPU Server

      BERT Base fine-tuning inference, dataset: SQuADv1.1, BS=1, sequence length=128 | NVIDIA V100 comparison: Supermicro SYS-4029GP-TRT, 1x V100-PCIE-16GB, pre-release container, mixed precision, NVIDIA TensorRT? 6.0, throughput: 557 sentences/sec | Intel comparison: 1 socket Intel Gold 6240@2.6GHz/3.9Hz Turbo, FP32 (only precision available), OpenVINO MKL-DNN v0.18, throughput: 23.5 sentences/sec

      AI Inference

      To connect us with the most relevant information, services, and products, hyperscale companies have started to tap into AI. However, keeping up with user demand is a daunting challenge. For example, the world’s largest hyperscale company recently estimated that they would need to double their data center capacity if every user spent just three minutes a day using their speech recognition service. 

      V100 is engineered to provide maximum performance in existing hyperscale server racks. With AI at its core, V100 GPU delivers 47X higher inference performance than a CPU server. This giant leap in throughput and efficiency will make the scale-out of AI services practical.

      One V100 Server Node Replaces Up to 135 CPU-Only Server Nodes

      Application (Dataset): MILC (APEX Medium) and Chroma (szscl21_24_128) | CPU Server: Dual-Socket Intel Xeon Platinum 8280 (Cascade Lake)

      high performance computing (HPC)

      HPC is a fundamental pillar of modern science. From predicting weather to discovering drugs to finding new energy sources, researchers use large computing systems to simulate and predict our world. AI extends traditional HPC by allowing researchers to analyze large volumes of data for rapid insights where simulation alone cannot fully predict the real world.

      V100 is engineered for the convergence of AI and HPC. It offers a platform for HPC systems to excel at both computational science for scientific simulation and data science for finding insights in data. By pairing NVIDIA CUDAcores and Tensor Cores within a unified architecture, a single server with V100 GPUs can replace hundreds of commodity CPU-only servers for both traditional HPC and AI workloads. Every researcher and engineer can now afford an AI supercomputer to tackle their most challenging work.

      DATA CENTER GPUs

      Data Center Tesla V100 NVLink

      NVIDIA V100 FOR NVLINK

      Ultimate performance for deep learning.

      Data Center Tesla V100 PCle

      NVIDIA V100 FOR PCle

      Highest versatility for all workloads.

      NVIDIA V100 Specifications

       

      V100 for NVLink

      V100 for PCIe

      V100S for PCIe

      PERFORMANCE
      with NVIDIA GPU Boost

      Double-Precision
      7.8 teraFLOPS

      Single-Precision
      15.7 teraFLOPS

      Deep Learning
      125 teraFLOPS

      Double-Precision
      7 teraFLOPS

      Single-Precision
      14 teraFLOPS

      Deep Learning
      112 teraFLOPS

      Double-Precision
      8.2 teraFLOPS

      Single-Precision
      16.4 teraFLOPS

      Deep Learning
      130 teraFLOPS

      INTERCONNECT BANDWIDTH
      Bi-Directional

      NVLink
      300 GB/s

      PCIe
      32 GB/s

      PCIe
      32 GB/s

      MEMORY
      CoWoS Stacked HBM2

      CAPACITY
      32/16 GB HBM2

      BANDWIDTH
      900 GB/s

      CAPACITY
      32 GB HBM2

      BANDWIDTH
      1134 GB/s

      POWER
      Max Consumption


      300 WATTS


      250 WATTS

      Take a Free Test Drive

      The World's Fastest GPU Accelerators for HPC and
      Deep Learning.

      WHERE TO BUY

      Find an NVIDIA Accelerated Computing Partner through
      our NVIDIA Partner Network (NPN).