Streamline virtual reality, visualization, and simulation workflows with Quadro GP100

NVIDIA has introduced a new Quadro family of products in response to the rise of photorealism, VR, and deep learning technologies.

With the rise of photorealism, virtual reality (VR), and deep learning technologies, the size and complexity of data are increasing, and workflows such as design and engineering are evolving to meet these demands.

Accordingly, the NVIDIA Quadro line provides an enterprise-class visual computing platform and ultra-fast memory that streamlines design and simulation workflows with up to twice the performance compared to the previous generation.



NVIDIA has completed the Quadro lineup with the announcement of the GP100, P4000, P2000, P1000, P600, and P400, alongside the existing P6000, P5000, and mobile GPUs. The new Quadro lineup provides the graphics and computing capabilities required for artificial intelligence, virtual reality, and photorealism.

In particular, the GP100 integrates simulation, HPC, rendering, and design capabilities. Equipped with high double-precision performance and 16GB of high-speed memory (HBM2), the GP100 enables users to perform simulations simultaneously while proceeding with the design process. It also allows for faster aggregation of realistic multiphysics simulations.

The GP100 is an ideal development platform for implementing deep learning in Windows and Linux environments, providing over 20 teraflops of 16-bit floating-point operations. In addition, it is optimized for VR, enabling the creation of detailed and realistically immersive environments.

Going forward, the latest Quadro GPUs are expected to be supported across various industries.

Rob Herman, General Manager and Executive Vice President of the Workstation Business Unit at Lenovo, stated, “The new NVIDIA GP100 will be useful for customers in fields requiring extreme computing power due to large datasets, such as design and manufacturing,” adding that “with up to three NVIDIA GP100s, customers in the fields of deep learning, artificial intelligence, and simulation can utilize optimal performance and process more data in real time.”