The company’s founder and CEO Jensen Huang delivered what was described as a ‘sweeping’ opening keynote at San Jose State University, describing the company’s progress in supporting a variety of dynamic industries and he took the opportunity to point to advances the company has been making in developing the computing power needed to transform data into insights and intelligence.
"Accelerated computing is not just about the chips," Huang said. "It is a collaboration, a codesign, a continuous optimisation between the architecture of the chip, the systems, the algorithm and the application."
Huang used his address to conference to make several announcements.
The first was that mainstream servers optimised to run NVIDIA’s data science acceleration software were now available from seven of the world’s largest systems manufacturers, including Cisco, Dell EMC, Fujitsu, Hewlett Packard Enterprise (HPE), Inspur, Lenovo and Sugon.
Featuring NVIDIA 4 GPUs and fine-tuned to run NVIDIA CUDA-X AI acceleration libraries, the servers provide an efficient platform for data analytics as well as a wide range of other enterprise workloads.
Very power efficient, the T4 GPUs can accelerate AI training and inference, machine learning, data analytics and virtual desktops and have helped to create a new class of enterprise servers that, through GPU acceleration, can provide businesses with much greater versatility.
"The rapid adoption of T4 heralds a new modern era in enterprise computing - one in which GPU acceleration has become standard," said Ian Buck, vice president and general manager of Accelerated Computing at NVIDIA.
Turning to the automotive sector, Huang said that NVIDIA was collaborating with Toyota, Toyota Research Institute-Advanced Development in Japan and Toyota Research Institute in the United States in developing, training and validating self-driving vehicles.
Building on its existing relationship with Toyota to use DRIVE AGX Xavier AV compute, the deal expands that collaboration to new testing validation using DRIVE Constellation - which is now available and allows automakers to simulate billions of miles of driving in all conditions.
Jetson Nano
Huang also unveiled the Jetson Nano, an AI computer.
The CUDA-X AI computer is able to deliver 472 GFLOPS of compute performance and can be used to run modern AI workloads and is, according to Huang, highly power-efficient, consuming just 5W.
The Jetson Nano comes in two versions - a $99 devkit for developers, makers and enthusiasts and a slightly more expensive production-ready module for companies looking to create mass-market edge systems.
The Jetson Nano can support high-resolution sensors, can process many sensors in parallel and run multiple modern neural networks on each sensor stream. It also supports a number of popular AI frameworks.
The aim, according to the company, is to make it easy for developers to integrate their preferred models and frameworks into the product.
The Jetson Nano is part of the company’s Jetson family lineup, which includes the Jetson AGX Xavier for fully autonomous machines and the Jetson TX2 for AI at the edge.
The Jetson AI computer platform is also now able to support the Amazon Web Services (AWS) RoboMaker, enabling both simulation and development to take place in the cloud.
AWS’s RoboMaker is a service that developers can use to develop, test and deploy intelligent robotic applications at scale.
It includes a development environment that enables the editing and debugging of robotics applications in the cloud and a simulation service that lets developers fine-tune robotics applications in simulated environments, rather than perform costly and time-consuming physical testing.
An over-the-air update system means that it is possible to securely deploy the application to Jetson-powered robots and it’s possible to push updates while they’re in use.
"The AWS RoboMaker provides pre-built functionality to support customers during their entire project, making it significantly easier to build robots, simulate performance in various environments, iterate faster and drive greater innovation," said Roger Barga, of AWS’s Robotics and Automation Services division.
