Parallel processing improvements have also been reported through hybrid CPU/GPU algorithms that intelligently balance the computational load between host and device, leading to significant ...

The development of the VTK-m toolkit, a scientific visualization toolkit for emerging architectures, is a critical advancement in support of scientific visualization on exascale and GPU-accelerated ...

The GPU is also important to Skyhook, which does visualization of big geographic datasets. “If you got a million devices in the field and pinging location a couple times a minute, you are ...

CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on its own GPUs (graphics processing units).CUDA enables developers to speed up compute ...

You are going to have to write a parallel program to effectively use any modern CPU. So, it’s not parallel programming per se that makes GPU programming more difficult than CPU programming. Much of ...

In this video from SC17, Peter Messmer from NVIDIA presents: Visualization on GPU Accelerated Supercomputers. “This talk is a summary about the ongoing HPC visualization activities, as well as a ...

It's unlikely to replace GPU-based training any time soon, because it's far easier to add multiple GPUs to one system than multiple CPUs. (The aforementioned $100,000 GPU system, for example, has ...

S-LoRA dramatically reduces the costs associated with deploying fine-tuned LLMs, which enables companies to run hundreds or even thousands of models on a single graphics processing unit (GPU).

Surgical Theater Unveils Medical Virtual Reality Visualization at NVIDIA GPU Technology Conference. Contacts. For Surgical Theater Denise Carson, 310-890-8360 [email protected].

GPU-based sorting algorithms have emerged as a crucial area of research due to their ability to harness the immense parallel processing power inherent in modern graphics processing units. By ...