We set out 26 years ago to transform computer graphics.
Fueled by the massive growth of the gaming market and its insatiable demand for better 3D graphics, we’ve evolved the GPU into a computer brain at the intersection of virtual reality, high performance computing, and artificial intelligence.
NVIDIA GPU computing has become the essential tool of the da Vincis and Einsteins of our time. For them, we’ve built the equivalent of a time machine.
Our invention of the GPU in 1999 made real-time programmable shading possible, giving artists an infinite palette for expression.
In 2018, the introduction of the Turing architecture and NVIDIA RTX™ ray-tracing technology fulfilled another vision of computer scientists, paving the way to new levels of art and realism in real-time graphics.
We’ve led the field of visual computing for decades.
Turing-based Quadro® RTX delivers photoreal graphics that creators didn’t expect for another 5-10 years.
Quadro RTX GPUs can now accelerate photoreal rendering for large industries that previously only used CPU server farms: film, animation, architecture, product design, and others.
NVIDIA has reinvented computer graphics, again.
GeForce® RTX has redefined what’s possible in gaming. Real-time ray tracing and neural graphics processing come together to create eye-popping images and deliver a level of photorealism never before seen in PC gaming.
RTX is bringing a new visual dimension to AAA games like Call of Duty Modern Warfare, Control, and Watch Dogs: Legion.
And it’s opened entirely new possibilities for games like Minecraft — the world’s best-selling video game — where players shape the game’s visuals in real time.
In 2006, the creation of our CUDA programming model and Tesla® GPU platform brought parallel processing to general-purpose computing. A powerful new approach to computing was born.
Now, the paths of high performance computing and AI innovation are converging.
From the world’s largest supercomputers to the vast datacenters that power the cloud, this new computing model is helping to answer complex questions, discover new science, and bring amazing capabilities to our mobile devices.
Now, the world’s largest industries — transportation, healthcare, logistics, manufacturing, robotics, smart cities, retail — are tapping into accelerated computing to bring AI to the edge.
Accelerated computing is the way forward for the world’s most powerful computers. More than 600 applications support CUDA today, including the top 15 in HPC.
NVIDIA powers U.S.-based Summit, the world’s fastest supercomputer, as well as the fastest systems in Europe and Japan. More than 130 supercomputers on the TOP500 list are accelerated by NVIDIA, including five of the top 10.
In 2012, GPU-accelerated AlexNet ushered in the era of superhuman image recognition. Since then, we’ve used deep learning to teach AI how to observe and identify images and sounds, to understand their condition, and to infer what may come next.
With the latest breakthroughs in natural language understanding, AI is learning the code of human knowledge. Computers can have natural dialogue, read and summarize for us, and more naturally collaborate with us.
Building amazing AI applications begins with training neural networks. NVIDIA DGX-2 is the world’s most powerful tool for AI training, uniting 16 GPUs to deliver 2 petaflops of training performance.
With the extreme IO performance of Mellanox InfiniBand networking, DGX-2 systems can quickly scale to supercomputer-class NVIDIA DGX SuperPODs.
In 2019, DGX-2 set world records on MLPerf, a new set of industry benchmarks designed to test deep learning performance.
Trained AI applications are deployed in large-scale, highly complex cloud data centers that serve voice, video, image, and recommendation services to billions of users.
To be useful to our daily lives, they must work incredibly fast – a demand that is increasing exponentially with the rise of conversational AI.
NVIDIA TensorRT™ software and the T4 GPU converge to optimize, validate, and accelerate the world’s most demanding neural networks.
AI is spilling out of the cloud and into the edge where oceans of raw data are generated by the world’s largest industries. On factory floors. In stores. On city streets. In urgent care facilities.
The NVIDIA EGX platform puts AI performance closer to the data to drive real-time decisions when and where they’re needed most.
AI breakthroughs no longer come from scientific labs and hyperscale cloud providers alone.
Self-driving cars, automated farm equipment, and autonomous factory robots have moved quickly from ideas to reality. And it’s only the beginning.
The fourth industrial revolution has begun.
Autonomous vehicles will revolutionize the $10 trillion transportation industry.
NVIDIA DRIVE is an open platform and enables researchers and programmers to develop new algorithms or adapt them for specific vehicles.
To train the network, data from all over the world needs to be collected and fed into an NVIDIA DGX supercomputer.
Simulation expands the training set and covers dangerous scenarios that can’t be captured on the road. The trained model is deployed on an in-car supercomputer, for capabilities like pedestrian detection and driver monitoring.
NVIDIA Jetson™ AGX Xavier delivers the energy-efficient computational power needed for embedded systems like robots, drones, and smart cities. And the new Jetson Nano™ will enable millions more small, low-power AI systems for embedded IoT apps.
From Xavier to Nano, all of NVIDIA’s AI computers run on the same CUDA-X AI software stack.