The use of Arm-based systems in HPC received another boost in December 2019 when Fujitsu announced that it had begun shipping systems for the Fugaku supercomputer. Fugaku was jointly developed by Fujitsu and the RIKEN Center for Computational Science in…
Univa Grid Engine, the enterprise-grade workload manager with first-class support for container workloads, meets Azure CycleCloud in the simplest way to manage high-performance computing (HPC) workloads. This collaboration realizes end-to-end enterprise support for HPC workloads running on Azure – including…
A big motivator for deploying HPC workloads to the cloud is improving application throughput and performance with scalability. This is especially true in life sciences and CAE, where workloads tend to be cloud-friendly, and customers have an insatiable appetite for…
Last week, we were joined by two speakers from NVIDIA Corporation to present the live webinar, Maximizing the utilization of GPU resources on-premise and in the cloud. Users are increasingly taking advantage of GPUs, containers, and cloud-resources for high-performance applications;…
Anyone working in high-performance computing (HPC) has likely come across Grid Engine at some point in their career. Grid Engine has been around in various forms since 1993. The scheduler caught fire with Sun Microsystems’ acquisition of Gridware in the…
Virtualizing and sharing GPU devices In GPU Sharing with Univa Grid Engine Part I, we looked at the basics of GPU resource scheduling with Univa Grid Engine. In the second article in this series (GPU Sharing with Univa Grid Engine…
Join NVIDIA and Univa for an exclusive webinar on optimizing GPUs As users increasingly take advantage of GPUs, containers, and cloud-resources for high-performance applications, effective management of GPU workloads is more important than ever. We are excited to announce an…
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…
Last month, I had the opportunity to partner with a colleague from Google and co-present at this year’s Design Automation Conference (DAC). We conducted a tutorial session and shared best practices based on our experience helping EDA users shift workloads…
