Last week, we were joined by speakers from Intel and Amazon Web Services to present the live webinar, Migrating HPC Workloads to the Cloud, and attracted more than 100 attendees. We discussed best practices and key capabilities required to make…
Among Grid Engine users, there is a high interest in cloud computing. In a recent InsideHPC survey sponsored by Univa, 92% of users said that they were “open to or already using cloud,” and 64% described cloud as “having proven…
Used by thousands of organizations around the world, Grid Engine is one of the world’s most popular and capable grid management systems with a vibrant, growing user community. When application providers describe their support for Grid Engine, they often lump…
We are pleased to announce that the highly anticipated Navops Launch 2.0 is now available! The General Availability release helps enterprises easily extend HPC workloads to the cloud, boosting efficiency and productivity, and dramatically improving cloud ROI while reducing cloud-related…
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…
Put simply, we can’t wait for SC19. After unveiling Navops Launch 2.0 with newly added Slurm support, we knew this Supercomputing Conference would be one of our most exciting exhibitions to date. Drop by booth 849 from Tuesday, November 19…
Using cloud for HPC can be expensive and a key reason why enterprises are not willing to adopt cloud. However, if managed well, you can leverage cloud resources to meet computational peaks, very quickly resulting in substantial reduction in overall…
Workload monitoring and reporting solutions for clusters have been around for many years. Cluster Administrators have always needed data about workloads and resource usage to help fine-tune sharing policies, identify bottlenecks, plan capacity and provide chargeback and showback accounting. In…
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…
