Data security is the top priority of every CTO. If you are deploying Quadro RTX graphics cards in mission-critical workstations or servers, and want to secure your data, Quadro RTX graphics cards are the right choice. PNY can help you permanently disable the data path on the VirtualLink (USB Type-C) port to prevent unauthorized data access through VirtualLink.

Topics: PNY, NVIDIA, NVIDIA Quadro, PNY PRO, NVIDIA GPUs, NVIDIA RTX Technology, Pro Tip, rtx 6000, rtx 5000, RTX 4000, NVIDIA Quadro RTX 6000, nvidia quadro rtx, virtuallink, GeForce RTX, NVIDIA Quadro RTX 5000, QuadroRTX8000, NVIDIA Quadro RTX 8000, RTX Server

In this blog post, let’s address the difference between the following driver variations and help you choose the right driver for your graphics card investment.

1. GeForce Game-Ready driver vs. Studio driver
2. Quadro ODE driver vs. QNF driver
3. Standard Package vs DCH Package

Topics: Workflow, OEMs, IT Professionals, NVIDIA Quadro Advantage, Pro Tip, Update, Quadro RTX, Recommended, nvidia quadro rtx, GeForce RTX, Windows10, Win10, rtx for creators, Driver

This is going to be a long blog post, but by the end, you will have an Ubuntu environment connected to the NVIDIA GPU Cloud platform, pulling a TensorFlow container and ready to start benchmarking GPU performance. 

Let's split this into four phases:

1) Install Ubuntu 18.04 LTS and NVIDIA Graphics Driver
2) Install Docker CE and NVIDIA Docker v 2.0
3) Setup NVIDIA GPU Cloud and pull down GPU optimized docker containers
4) Run the TensorFlow benchmark

It's time to get started!

Topics: PNY, NVIDIA, PNYPRO, CUDA, NVIDIA GPU Cloud, Pro Tip, Tensor Cores, Quadro RTX, nvidia quadro rtx, NVIDIATuring, GeForce RTX, NGC, data science, NVIDIA CUDA, Linux, Tensorflow, benchmark

In this blog post, I will go over the hardware considerations I used when putting together a system for benchmarking GPU performance for Deep Learning using Ubuntu 18.04, NVIDIA GPU Cloud (NGC) and TensorFlow. Keep in mind that everyone will have different budgets and requirements for their own systems, which can and will result in a wide range of configurations. My particular list should serve only as a reference; your system will likely be different based on your own requirements.

Before we dive into the details, let’s go over what we are seeking to accomplish.  Our goal is to build a system to test the compute performance between different GPUs; therefore the GPU should be the only variable that changes between the different test runs.  To ensure the consistency of our tests, we will remove any potential bottlenecks that will negatively impact GPU performance. 

Topics: PNY, NVIDIA, NVIDIA Quadro, PNYPRO, NVIDIA GPU Cloud, Pro Tip, Turing, Quadro RTX, Artificial Intelligence, GeForce RTX, NGC, GPU-accelerated machine learning, NVIDIA CUDA, CUDA-X, Linux, Tensorflow, benchmark

As a PC enthusiast, I love pitting hardware solutions against each other to determine their relative performance when completing a particular task.  This process is also known as “Benchmarking.”  Benchmarking results are usually considered the best tool to evaluate the merits of competing systems when making a purchase decision.

In this 3-part blog series, we’ll discuss how to build a system, with an emphasis on benchmarking GPU performance for Deep Learning using Ubuntu 18.04, NVIDIA GPU Cloud (NGC) and TensorFlow.

Topics: Deep Learning, NVIDIA GPU, NVIDIA GPUs, NVIDIA Quadro GPUs, CUDA, NVIDIA RTX Technology, Pro Tip, Tensor Cores, Quadro RTX, NVIDIA Turing Architecture, nvidia quadro rtx, Artificial Intelligence, NVIDIATuring, GeForce RTX, Data Science Workstation, NGC, data science, RAPIDS, GPU-accelerated machine learning, NVIDIA CUDA, analytics, CUDA-X, Linux, Tensorflow, benchmark

SOLIDWORKS Visualize is a powerful tool used by engineers and designers to turn CAD files into photorealistic rendered images or immersive VR experiences. The ability to quickly generate photorealistic quality rendering is crucial for design reviews, factory floor (or other) training, and collaboration with marketing and sales.

Topics: PNY, Quadro, NVIDIA, GeForce, GPU, Solidworks, NVIDIA Quadro, Solidworks Visual Professional, Visualize, Quadro for VR, NVIDIA GPUs, NVIDIA Quadro GPUs, PNYPRO, Pro Tip

Today, we will conclude our three part discussion about VirtualLink.

In Tip #7, we covered the intended application of VirtualLink to simplify future VR headset connection, then in Tip #9, we covered the alternative applications, such as high-speed data transfer and easy monitor hook up. Today, we will cover the potential issues with the inclusion of this new standard and how PNY can assist you in dealing with these issues.

Topics: PNY, Quadro, NVIDIA, GeForce, GPU, NVIDIA Quadro, Quadro for VR, VR capability, VR Solution, NVIDIA GPUs, NVIDIA Quadro GPUs, PNYPRO, VR Headset, Pro Tip, virtuallink

In our PNY Pro Tip #7, we introduced the latest VirtualLink addition to the Turing RTX GPU output offering, and how it was developed to make VR more accessible. While the idea of one cable connection for VR is great, there are currently no VR HMDs (Head Mounted Display) available with VirtualLink. In this follow up blog, we will go over 3 ideas that our readers can use the VirtualLink port for.

Topics: PNY, Quadro, NVIDIA, GeForce, GPU, NVIDIA Quadro, Quadro for VR, VR capability, VR Solution, NVIDIA GPUs, NVIDIA Quadro GPUs, PNYPRO, VR Headset, Pro Tip, virtuallink

Did you know the NVIDIA Windows 10 Drivers for Quadro and GeForce RTX Turing based GPUs are incompatible with Windows 10 RS2 or earlier? This includes Windows 10 Threshold 1, Threshold 2, Redstone 1, and Redstone 2 operating systems.

Topics: PNY, Quadro, NVIDIA, GeForce, GPU, NVIDIA Quadro, NVIDIA GPUs, NVIDIA Quadro GPUs, PNYPRO, Pro Tip, NVIDIA Turing Architecture, NVIDIATuring, Windows10, Win10

Topics: PNY, Quadro, NVIDIA, GeForce, GPU, NVIDIA Quadro, Quadro for VR, VR capability, VR Solution, NVIDIA GPUs, NVIDIA Quadro GPUs, PNYPRO, VR Headset, Pro Tip, virtuallink