Visual Archives - Page 3 of 3

Landon 04/06/2021 Visual

Computers in the workplace: employee data protection

What data can employers collect about employees and applicants? Can the boss control how employees use the Internet and e-mail? Who can employees contact? An overview of employee data protection. GDPR Everyone has heard of data protection before, but only…

Landon 04/06/2021 Visual

Your privacy on the Internet

The protection of personal data such as web profiles or buying behavior is essential on the Internet. Our tips show how you can effectively protect your online identity. According to a recent study by the University of Hohenheim, three-quarters of…

Landon 02/05/2021 Visual

Why read something on the GPU?

Everyone has long known that video cards can be used not only to play with toys, but also to do things that have nothing to do with games, for example, train a neural network, memorize a cryptocurrency, or perform scientific…

Landon 01/23/2021 Visual

GPU Core collecting data

(The data is collected from open sources, there is no data for 2019-20, because not everything is so beautiful there, but GPUs still win) Well, tempting, isn’t it? We shift all calculations from the CPU to the GPU and get…

Landon 01/18/2021 Visual

GPU Limitations and Capabilities

What restrictions does this architecture impose on the algorithms being executed: What opportunities opens up: Reduction of classical algorithms to SIMD representation Transformation We have two arrays, A and B, and we want to add an element from array B…

Landon 01/15/2021 Visual

Sorting

We have an array of n elements. At the first stage, we start n / 2 threads and each thread adds two elements, i.e. in one iteration, we add together half of the elements in the array. And then in…

Landon 01/12/2021 Visual

Aggregation

And here it is already interesting, the threadIdx variable appeared, which we did not seem to declare anywhere. Yes, the system provides us with it. Imagine that in the previous example, the array has three elements, and you want to…

Landon 01/11/2021 Visual

Where to start in computing

There are two most common technologies that can be used for GPU programming: OpenCL is a standard supported by most video card manufacturers, incl. and on mobile devices, also code written in OpenCL can be run on the CPU. You…

As we said before, the two main resources of a video card are computing cores and memory.

For example, we have several processes or containers using a video card, and we would like to be able to share the video card between them.

Unfortunately, there is no simple API for this. NVIDIA offers vGPU technology, but I did not find the

Tesla k80 card in the list of supported ones, and as far as I could understand from the description, the technology is more focused on virtual displays than on computing.

Perhaps AMD is offering something more appropriate.

Therefore, if you plan to use the GPU in your projects, you should rely on the fact that the application will use the video card exclusively, or you will programmatically control the amount of memory allocated and the number of cores used for calculations.

If you figured out the resource limitation, then the next logical question is: what if the server has several video cards?

Again, you can decide at the application level which GPU it will use.

Another more convenient way is Docker containers. You can use regular containers, but NVIDIA offers its own NGC containers, with optimized versions of various software, libraries and drivers. For one container, you can limit the number of GPUs used and their visibility for the container. Overhead on container usage is about 3%.