Tag Archives: NVIDIA DRIVE PX 2

NVIDIA DRIVE PX 2 : First AI Supercomputer For Cars

NVIDIA DRIVE PX 2 : First AI Supercomputer For Cars

Special by Danny Shapiro, NVIDIA

Take a supercomputer. Give it wheels. The result: a robot that can take you anywhere you want to go. No wonder self-driving cars were the hot topic at CES last week, and the talk of the Detroit Auto Show this week.

Building this new generation of super-smart cars requires some serious intelligence. That’s why we introduced NVIDIA DRIVE PX 2, our artificial intelligence supercomputer for the car. We’re taking the GPU technology at the heart of a revolution that’s giving computers superhuman powers of perception and putting it in your driveway.

Here’s why your next car might be your first supercomputer:

 

NVIDIA DRIVE PX 2 : First AI Supercomputer For Cars

Only next generation AI has the adaptability, and the power, to understand what cars encounter on the road.

There aren’t enough engineers in Silicon Valley to hand-code software that can account for everything that happens when you drive. To deal with all the stuff a car sees on the road – and thanks to modern sensors, they see more and more – you need deep learning, a form of artificial intelligence. Last year, GPU-powered deep learning systems exceeded human levels of perception for the first time.

 

Our GPUs Make AI Practical

GPUs are built for parallel computing. So they’re ideal for deep neural networks – complex mathematical models that mimic the brain. DNNs are trained by feeding massive amounts of data into powerful computers. Parallel computing is the only practical way to digest this info rapidly. And DNNs are ideal for driving, because the more data you give them, the smarter they get.

 

NVIDIA DRIVE PX 2 Brings AI to the Road

NVIDIA DRIVE PX 2 can perform 24 trillion deep learning operations per second, and it has the processing power of 150 MacBook Pros. It lets developers to replace the trunk full of GPU-based workstations in their vehicles with a supercomputer the size of a lunchbox.

 

We Built DRIVE PX 2 to be a Scalable Platform for Car Companies

We designed DRIVE PX 2 to handle everything from advanced driver assistance systems to fully self-driving vehicles. It can be configured as a single-processor, air-cooled system for driver assistance, up to a four-processor, liquid-cooled system for autonomous driving. Whatever the case, it’s based on one scalable Architecture – the same that powers the world’s most advanced supercomputers.

 

DRIVE PX 2 Is An Open Platform

NVIDIA DRIVE PX 2 is built with the same open, programmable GPU architecture that’s driving an AI revolution. Audi, BMW, Ford, Mercedes and ZMP (makers of the RoboTaxi) are already using our AI platform for their autonomous car R&D.

Our open, programmable platform is being used by More than 50 automakers, Tier 1 suppliers, software companies and startups are using NVIDIA DRIVE PX to develop deep neural networks.

 

Car Companies Can Make Their Cars Safer Every Day

GPUs have already accelerated the training of deep neural networks by 20 to 30 times. What used to take months to train, now takes just days. This lets us create a brain for autonomous vehicles that is always alert, and can achieve superhuman levels of situational awareness.  The more data these cars scoop up and share with one another, the smarter they all get.

 

AI-Equipped Cars Are Coming Soon

[adrotate group=”2″]

Earlier this month, Volvo announced it selected NVIDIA DRIVE PX 2 to power its fleet of autonomous cars. They’re outfitting their award-winning XC90 SUV with it – and will let drivers put these cars into autonomous driving mode on public roads around its hometown of Gothenburg, Sweden.

 

Everyone’s Investing in Automotive Supercomputing

GM has invested $500 million with Lyft on self-driving technologies. Toyota recently earmarked $1 billion for AI research. Just yesterday, the U.S. government put forth a $4 billion investment plan in support of autonomous driving technologies and the infrastructure to enable it.

This is just the start. Our goal is to make this technology available across all vehicle types and segments.  Putting supercomputers on wheels is going to reduce the number accidents, injuries and fatalities. It’s going to make new capabilities – and new kinds of transportation – possible.

Go Back To > Automotive | Home

 

Support Tech ARP!

If you like our work, you can help support our work by visiting our sponsors, participating in the Tech ARP Forums, or even donating to our fund. Any help you can render is greatly appreciated!

Automotive Innovators Motoring to NVIDIA DRIVE

Written by Danny Shapiro, NVIDIA

Automotive Innovators Motoring to NVIDIA DRIVE

Audi. BMW. Ford. Mercedes-Benz. Volvo. Some of the world’s biggest automotive names are flocking to DRIVE, our powerful engine for in-vehicle artificial intelligence.

So are a group of fast-moving, smaller innovators that are shaking up the auto industry. Companies such as ZMP, Preferred Networks and AdasWorks are using DRIVE PX to give automobiles astonishing new capabilities.

Unveiled Monday at CES 2016, in Las Vegas, DRIVE PX 2 provides supercomputer-class performance — up to 24 trillion operations per second for artificial intelligence applications — in a case the size of a shoebox.

Here’s a look at just three of the companies working with DRIVE PX:

 

Bringing Autonomous Driving to Taxis

Tokyo-based ZMP — which is working to help create autonomous taxis, among other projects — is using deep learning technology and NVIDIA DRIVE PX to dramatically improve accuracy of detection and decision-making algorithms for autonomous driving.

“ZMP is achieving remarkable results using deep neural networks on NVIDIA GPUs for pedestrian detection,” said Hisashi Taniguchi, CEO of ZMP. “We will expand our use of deep learning on NVIDIA GPUs to realize our driverless Robot Taxi service.”

 

In Gear with Toyota

[adrotate group=”2″]

Preferred Networks is one of the best-known machine learning startups in Japan. The Tokyo-based company is working closely with Toyota — which purchased a 3% stake in Preferred Networks just a few weeks ago — to give cars autonomous driving capabilities.

With the NVIDIA deep learning platform, Preferred Networks has greatly improved performance on a variety of applications, such as image recognition for automotive and surveillance cameras, automated control of robotics, and health diagnostics, according to Preferred Networks founder Daisuke Okanohara.

“The remarkable thing is that we did it all with a single NVIDIA GPU-powered deep neural network, in a very short time,” Okanohara said.

 

Eyes on the Road

We’re also working with AdasWorks, a Budapest-based developer of artificial intelligence-based software for automated driving, to bring the power of our GPUs to Volvo Cars.

olvo will use the NVIDIA DRIVE PX 2 deep learning-based computing platform to power a fleet of 100 Volvo XC90 SUVs that will hit public roads next year, driven by actual customers as part of the the Swedish carmaker’s Drive Me autonomous-car pilot program.

AdasWorks worked with Volvo to help create a system that processes data from multiple sensors in real time to provide 360-degree detection of lanes, vehicles, pedestrians, signs and more, enabling a variety of autopilot functions.

NVIDIA DRIVE is more than just a component automakers can bolt into their cars. It’s an end-to-end solution for deep learning that includes a wide variety of tools and technologies, such as our DIGITS software for neural network training.

To see how it all comes together, visit our booth at CES. We’re in the North Hall, right in the middle of this year’s automotive action.

Go Back To > Automotive | Home

 

Support Tech ARP!

If you like our work, you can help support our work by visiting our sponsors, participating in the Tech ARP Forums, or even donating to our fund. Any help you can render is greatly appreciated!

Volvo XC90 To Use NVIDIA DRIVE PX 2 Computer

Jan. 5, 2016—Volvo Cars will use the NVIDIA DRIVE PX 2 deep learning- based computing engine to power a fleet of 100 Volvo XC90 SUVs starting to hit the road next year in the Swedish carmaker’s Drive Me autonomous car pilot programme, NVIDIA announced today.

Autonomous technology is an important contributor to Volvo’s Vision 2020 – its guiding principles for creating safer vehicles. This work has resulted in world-leading advancements in autonomous and semi-autonomous driving, and a new safety benchmark for the automotive industry.

“Our vision is that no one should be killed or seriously injured in a new Volvo by the year 2020,” said Marcus Rothoff, director of the Autonomous Driving Programme at Volvo Cars. “NVIDIA’s high-performance and responsive automotive platform is an important step towards our vision and perfect for our autonomous drive programme and the Drive Me project.”

 

The Volvo XC90 Drive Me Project

Volvo’s Drive Me autonomous pilot programme will equip the Volvo XC90 luxury cars with the NVIDIA DRIVE PX 2 engine, which uses deep learning to navigate the complexities of driving. The cars will operate autonomously on roads around Gothenburg, the carmaker’s hometown, and semi-autonomously elsewhere.

“Volvo’s Drive Me project is the ideal application of our DRIVE PX 2 engine and deep learning,” said Rob Csongor, vice president and general manager of Automotive at NVIDIA. “We are bringing years of work by thousands of NVIDIA engineers to help Volvo achieve its safety goals and move self-driving cars from Gothenburg to the rest of the globe.”

 

Recognising Objects Beyond Reach of Human Algorithms

The NVIDIA DRIVE PX 2 engine enables cars to utilise deep learning – a form of artificial intelligence – to recognise objects in their environment, anticipate potential threats and navigate safely. With 8 teraflops of processing power – equivalent to 250 MacBook Pros – it processes data from multiple sensors in real time, providing 360-degree detection of lanes, vehicles, pedestrians, signs and more, to enable a variety of autopilot functions.

Recent deep-learning breakthroughs have greatly enhanced computers’ ability to perceive the outside world. Using vast amounts of data and processing power, they can write software to recognise complex objects at a level beyond the reach of human-coded algorithms.

Much deep learning work is powered by NVIDIA’s supercomputing GPUs. For example, Microsoft and Google have used GPUs to create image-recognition systems that beat a well-trained human in the ImageNet Large Scale Visual Recognition Challenge. And Microsoft researchers recently trained a deep neural net that beat a human in IQ tests.

 

Map Localisation and Path Planning

[adrotate group=”2″]

For map localisation and path planning, the system can compare real-time situational awareness with a known high-definition map, enabling it to plan a safe route and drive precisely along it, adjusting to ever-changing circumstances.

DRIVE PX 2 will also perform other critical functions such as stitching camera inputs to create a complete surround-view of the car.

Because self-driving cars require massive computing resources to interpret the data from multiple sensors, most early prototypes have contained a trunk full of computers. In contrast, DRIVE PX 2, which carries out the same functions, is the size of a tablet.

Go Back To > Automotive | Home

 

Support Tech ARP!

If you like our work, you can help support our work by visiting our sponsors, participating in the Tech ARP Forums, or even donating to our fund. Any help you can render is greatly appreciated!

NVIDIA DRIVE PX 2 AI Computer For Cars Launched

Jan. 5, 2016—Accelerating the race to autonomous cars, NVIDIA today launched NVIDIA DRIVE PX 2 – the world’s most powerful engine for in-vehicle artificial intelligence.

NVIDIA DRIVE PX 2 allows the automotive industry to use artificial intelligence to tackle the complexities inherent in autonomous driving. It utilises deep learning on NVIDIA’s most advanced GPUs for 360-degree situational awareness around the car, to determine precisely where the car is and to compute a safe, comfortable trajectory.

“Drivers deal with an infinitely complex world,” said Jen-Hsun Huang, co-founder and CEO, NVIDIA. “Modern artificial intelligence and GPU breakthroughs enable us to finally tackle the daunting challenges of self-driving cars.

“NVIDIA’s GPU is central to advances in deep learning and supercomputing. We are leveraging these to create the brain of future autonomous vehicles that will be continuously alert, and eventually achieve superhuman levels of situational awareness. Autonomous cars will bring increased safety, new convenient mobility services and even beautiful urban designs – providing a powerful force for a better future.”

 

NVIDIA DRIVE PX 2 Deep Learning

Created to address the needs of NVIDIA’s automotive partners for an open development platform, DRIVE PX 2 provides unprecedented amounts of processing power for deep learning, equivalent to that of 100 MacBook Pros.

Its two next-generation Tegra® processors plus two next-generation discrete GPUs, based on the Pascal architecture, deliver up to 24 trillion deep learning operations per second, which are specialised instructions that accelerate the math used in deep learning network inference. That’s over 10 times more computational horsepower than the previous-generation product.

DRIVE PX 2’s deep learning capabilities enable it to quickly learn how to address the challenges of everyday driving, such as unexpected road debris, erratic drivers and construction zones. Deep learning also addresses numerous problem areas where traditional computer vision techniques are insufficient – such as poor weather conditions like rain, snow and fog, and difficult lighting conditions like sunrise, sunset and extreme darkness.

For general purpose floating point operations, DRIVE PX 2’s multi-precision GPU architecture is capable of up to eight trillion operations per second. That’s over four times more than the previous-generation product. This enables partners to address the full breadth of autonomous driving algorithms, including sensor fusion, localisation and path planning. It also provides high precision compute when needed for layers of deep learning networks.

 

Deep Learning in Self-Driving Cars

[adrotate group=”2″]

Self-driving cars use a broad spectrum of sensors to understand their surroundings. DRIVE PX 2 can process the inputs of 12 video cameras, plus lidar, radar and ultrasonic sensors. It fuses them to accurately detect objects, identify them, determine where the car is relative to the world around it, and then calculate its optimal path for safe travel.

This complex work is facilitated by NVIDIA DriveWorks, a suite of software tools, libraries and modules that accelerates development and testing of autonomous vehicles. DriveWorks enables sensor calibration, acquisition of surround data, synchronisation, recording and then processing streams of sensor data through a complex pipeline of algorithms running on all of the DRIVE PX 2’s specialised and general-purpose processors.

Software modules are included for every aspect of the autonomous driving pipeline, from object detection, classification and segmentation to map localisation and path planning.

 

End-to-End Solution for Deep Learning

NVIDIA delivers an end-to-end solution – consisting of NVIDIA DIGITS and DRIVE PX 2 – for both training a deep neural network, as well as deploying the output of that network in a car.

DIGITS is a tool for developing, training and visualising deep neural networks that can run on any NVIDIA GPU-based system – from PCs and supercomputers to Amazon Web Services and the recently announced Facebook Big Sur Open Rack-compatible hardware. The trained neural net model runs on NVIDIA DRIVE PX 2 within the car.

 

Strong Market Adoption

Since NVIDIA delivered the first-generation DRIVE PX last summer, more than 50 automakers, tier 1 suppliers, developers and research institutions have adopted NVIDIA’s AI platform for autonomous driving development. They are praising its performance, capabilities and ease of development.

“Using NVIDIA’s DIGITS deep learning platform, in less than four hours we achieved over 96 percent accuracy using Ruhr University Bochum’s traffic sign database. While others invested years of development to achieve similar levels of perception with classical computer vision algorithms, we have been able to do it at the speed of light.” — Matthias Rudolph, director of Architecture Driver Assistance Systems at Audi

“BMW is exploring the use of deep learning for a wide range of automotive use cases, from autonomous driving to quality inspection in manufacturing. The ability to rapidly train deep neural networks on vast amounts of data is critical. Using an NVIDIA GPU cluster equipped with NVIDIA DIGITS, we are achieving excellent results.” — Uwe Higgen, head of BMW Group Technology Office USA

“Due to deep learning, we brought the vehicle’s environment perception a significant step closer to human performance and exceed the performance of classic computer vision.” — Ralf G. Herrtwich, director of Vehicle Automation at Daimler

“Deep learning on NVIDIA DIGITS has allowed for a 30X enhancement in training pedestrian detection algorithms, which are being further tested and developed as we move them onto NVIDIA DRIVE PX.” — Dragos Maciuca, technical director of Ford Research and Innovation Center

 

NVIDIA DRIVE PX 2 Availability

The DRIVE PX 2 development engine will be generally available in the fourth quarter of 2016. Availability to early access development partners will be in the second quarter.

Go Back To > Automotive | Home

 

Support Tech ARP!

If you like our work, you can help support our work by visiting our sponsors, participating in the Tech ARP Forums, or even donating to our fund. Any help you can render is greatly appreciated!