While NVIDIA is best known for its hardware platforms, software plays a key role advancing the GPU-accelerated computing. The commpany today announced at its annual GPU Technology Conference the updated NVIDIA SDK.
The new SDK takes advantage of Mvidia's new Pascal architecture and makes it easier for developers to create solutions on Nvidia's platforms.
Here’s a look at the software updates Nvidia is introducing in seven key areas:
1) Deep Learning
What’s new - cuDNN 5, Nvidia's GPU-accelerated library of primitives for deep neural networks, now includes Pascal GPU support; acceleration of recurrent neural networks, which are used for video and other sequential data; and additional enhancements used in medical, oil & gas and other industries.
Deep learning developers rely on cuDNN’s optimized routines so they can focus on designing and training neural network models, rather than low-level performance tuning.
2) Accelerated Computing
What’s new - CUDA 8, the latest version of Nvidia's parallel computing platform, gives developers direct access to new Pascal features such as unified memory and NVLink. Also included in this release is a new graph analytics library - nvGRAPH - which can be used for robotic path planning, cyber security and logistics analysis, expanding the application of GPU acceleration in the realm of big data analytics. One new feature developers is critical path analysis, which automatically identifies latent bottlenecks in code for CPUs and GPUs. And for visualizing volume and surface datasets, NVIDIA IndeX 1.4 is now available as a plug-in for Kitware ParaView, bringing interactive visualization of large volumes with high-quality rendering to ParaView users.
3) Self-Driving Cars
What’s new - At GTC, Nvidia also announced its end-to-end HD mapping solution for self-driving cars. The system is built on Nvidia's DriveWorks software development kit, part of our deep learning platform for the automotive industry.
4) Design Visualization
What’s new - At GTC, Nvidia brought NVIDIA Iray - its photorealistic rendering solution - to the world of VR with the introduction of new cameras within Iray that let users create VR panoramas and view their creations with accuracy in virtual reality. Nvidia also announced Adobe’s support of Nvidia's Materials Definition Language, bringing the possibility of physically based materials to a wide range of creative professionals.
5) Autonomous Machines
What’s new - Nvidia is bringing deep learning capabilities to devices that will interact with - and learn from - the environment around them. Nvidia's cuDNN version 5, noted above, improves deep learning inference performance for common deep neural networks, allowing embedded devices to make decisions faster and work with higher resolution sensors. NVIDIA GPU Inference Engine (GIE) is a neural network inference solution for application deployment. Developers can use GIE to generate optimized implementations of trained neural network models that deliver the fastest inference performance on NVIDIA GPUs.
What’s new - Nvidia recently announced three new technologies for NVIDIA GameWorks, its combination of development tools, sample code and advanced libraries for real-time graphics and simulation for games. They include Volumetric Lighting, Voxel-based Ambient Occlusion and Hybrid Frustum Traced Shadows.
7) Virtual Reality
What’s new - Nvidia is continuing to add features to VRWorks - its suite of APIs, sample code and libraries for VR developers. For example, Multi-Res Shading accelerates performance by up to 50 percent by rendering each part of an image at a resolution that better matches the pixel density of the warped VR image. VRWorks Direct Mode treats VR headsets as head-mounted displays accessible only to VR applications, rather than a normal Windows monitor in desktop mode.