We can help you to fully exploit the vast potential laying in GPUs. If you want your code to evolve and reveal new possibilities - we can do it for you quickly and effectively.

We will leverage your application with GPU cloud computing technology to make it efficient and scalable as never before.

The potential of GPU computing

Originally GPUs (Graphics Processing Units) were known only for handling the graphical output of a computer. However, the vast potential laying in the massively parallel architecture and rapid increase of the computing power of GPUs compared to CPUs resulted in popularization of General Puropose computing on Graphics Processing Units (GPGPU). Harnessing the power of high-performance many-core processors GPUs results in speedups of orders of magnitude.

GPGPU has already found application in many industries such as medical imaging, numerical analytics, structural mechanics, oil industry or molecular dynamics or materials science.

Our approach

Depending on how advanced is your application in terms of GPU utilization, there are a few ways that we can follow to enable your code to fully exploit the potential of GPU:

Code porting
If your application is currently running only on CPU, we will convert it to CUDA or OpenCL so it can run efficiently on GPU. If you already have introduced support for a single GPU to your code, we can turn it into an efficient multi-GPU solution. We will also port code from other languages to C++. You can expect from us tidily prepared documentation of changes - developers of Renegatt Software know how to properly maintain the code.
Tailored libraries
We deliver customized libraries that can be seamlessly incorporated to your application. With this change you will easily turn your current single-node solution into a powerful and scalable GPU-enabled multi-node computing environment. And with an optional InfiniBand support the potential of your application will truly skyrocket.
Code optimization
Our experts and engineers will audit and optimize your code towards better utilization of both CPU and GPU. With our years of experience in parallel programming and cloud computing, we know how to make an efficient and scalable code that can make the best possible use of the potential laying in hardware.

Ask us about the best solutions that can be applied in your case:
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