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Deep learning algorithms use large amounts of data and the computational power of the GPU to learn information directly from data such as images, signals, and text. NVIDIA® DIGITS offers an interactive workflow-based solution for image classification. Deep learning frameworks offer more flexibility with designing and training custom deep neural networks and provide interfaces to common programming language. The NVIDIA Deep Learning SDK offers powerful tools and libraries for the development of deep learning frameworks such as Caffe, CNTK, TensorFlow, Theano, and Torch.

NVIDIA Deep Learning SDK

The NVIDIA Deep Learning SDK provides powerful tools and libraries for designing and deploying GPU-accelerated deep learning applications. It includes libraries for deep learning primitives, inference, video analytics, linear algebra, sparse matrices, and multi-GPU communications.

 

  • Deep Learning Primitives (cuDNN): High-performance building blocks for deep neural network applications including convolutions, activation functions, and tensor transformations
  • Deep Learning Inference Engine (TensorRT): High-performance deep learning inference runtime for production deployment
  • Deep Learning for Video Analytics (DeepStream SDK): High-level C++ API and runtime for GPU-accelerated transcoding and deep learning inference
  • Linear Algebra (cuBLAS): GPU-accelerated BLAS functionality that delivers 6x to 17x faster performance than CPU-only BLAS libraries
  • Sparse Matrix Operations (cuSPARSE): GPU-accelerated linear algebra subroutines for sparse matrices that deliver up to 8x faster performance than CPU BLAS (MKL), ideal for applications such as natural language processing
  • Multi-GPU Communication (NCCL): Collective communication routines, such as all-gather, reduce, and broadcast that accelerate multi-GPU deep learning training on up to eight GPUs
The Deep Learning SDK requires CUDA Toolkit, which offers a comprehensive development environment for building new GPU-accelerated deep learning algorithms, and dramatically increasing the performance of existing applications

NVIDIA DIGITS

NVIDIA DIGITS helps computer vision data scientists and engineers solve complex image classification problems. DIGITS lets you quickly design the best deep neural network (DNN) for your data—interactively, without writing any code—to reach state-of-the-art results with deep learning.


Import data for image classification and object detection neural networks


Choose predefined LeNet, AlexNet, GoogLeNet or provide custom networks


Visualize deep neural network architectures


Import data for image classification and object detection neural networks


Choose predefined LeNet, AlexNet, GoogLeNet or provide custom networks


Visualization of inference results

Deep Learning Frameworks

The NVIDIA Deep Learning SDK accelerates widely used deep learning frameworks such as Caffe, CNTK, TensorFlow, Theano, and Torch, as well as many other deep learning applications. Visit the Deep Learning Frameworks page to learn more about these popular deep learning frameworks, their key features, and how to download and get started.