Aided by developers’ requests, NVIDIA has built tools, libraries and enhancements to the CUDA programming model to help developers accelerate and build the next generation of AI and HPC applications.

The level of interest in GPU computing has exploded, fueled by advancements in AI.

The latest SDK updates introduce new capabilities and performance optimizations for GPU-accelerated applications:

New CUDA 9 speeds up HPC and deep learning applications with support for Volta GPUs, up to 5x faster performance for libraries, a new programming model for thread management, and updates to debugging and profiling tools.

Developers of end-user applications such as AI-powered web services and embedded edge devices benefit from 3.5x faster deep learning inference with the new TensorRT 3. With built-in support for optimizing both Caffe and TensorFlow models, developers can take trained neural networks to production faster than ever.

Engineers and data scientists can benefit from 2.5x faster deep learning training using Volta optimizations for frameworks such as Caffe2, Microsoft Cognitive Toolkit, MXNet, PyTorch and TensorFlow.