In our previous article, we looked at the fundamentals of GPU resource scheduling in GPU Sharing with Univa Grid Engine Part I. GPUs power a wide variety of HPC and AI workloads. Given the high-cost of GPU-capable servers and cloud…
Increasingly, GPUs power a wide variety of HPC and AI workloads from structural analysis to molecular modeling. In April of 2020, Univa’s State of the GPU in HPC survey found that 83% of survey respondents reported running GPUs with fully…
A primer on using Univa Grid Engine with GPU-aware applications In Part I of this two-part article, I provided a short primer on GPUs, explained how they are used in HPC and AI, and covered some of the challenges users…
A primer on using Univa Grid Engine with GPU-aware applications For almost two decades, GPUs (Graphics Processing Units) have been steadily revolutionizing high-performance computing (HPC) and AI. Originally designed for graphics-intensive applications such as gaming and image processing, it didn’t…
At Univa, we continue to see rapid growth in GPU adoption in applications ranging from Deep Learning to Inference to traditional HPC. Many factors are driving increased GPU adoption: GPU applications deliver better performance They are more cost-efficient They are…
