In this guest article, our friends at Intel discuss how benchmarks show key workloads average 31% better on Intel Xeon Platinum 9282 than AMD EYPC “Rome” 7742. Intel analysis provides strong evidence that the 2nd Generation Intel Xeon Scalable Processor (Cascade Lake “CLX”) architecture provides dramatic performance for real-world workloads. An impressive array of benchmarks shows 2S systems built with Intel’s 56 core processors (Intel Xeon Platinum 9282 processor) solidly ahead of systems built with AMD’s 64 core processors (AMD EYPC 7742).
2nd Generation Intel® Xeon® Scalable Processors Demonstrate Amazing HPC Performance
December 5, 2019 by 3 Comments
Cloud Adoption for HPC: Trends and Opportunities
November 19, 2019 by Leave a Comment
This whitepaper is an insideHPC Special Research Report sponsored by Univa. “Today many organizations solve their most difficult computational challenges by creating their own on-premises, compute-intensive, high performance data center. The latest hardware and software innovations have removed barriers that prevented many organizations from embracing HPC solutions. With more enterprises extending their own on-premises clusters into the cloud with hybrid configurations, finding the right tools for managing and scheduling workflows and automatically controlling cost remains a critical challenge.”
Are You Ready for the Exascale Era? Find Out at SC19
November 15, 2019 by Leave a Comment
As we head into the biggest supercomputing event of the year, all eyes are on exascale. The frontrunners in the race to exascale, including our friends over at Altair, will convene at SC19 in Denver this November to share updates, address challenges, and help paint the picture of an exascale-fueled future for HPC.
The Use of High-Performance Polymers in HPC and Data Center Applications
November 15, 2019 by Leave a Comment
“Polymer components in liquid cooling systems are attractive for several reasons: they are lightweight, typically less expensive than metal counterparts, and are impervious to corrosion that can render parts inoperable or introduce debris into flow paths. The challenges with many polymers used to date, however, are their abilities to handle high temperatures and physical stressors without deforming, cracking or creeping. These shortcomings become significant when leaks occur, leading to downtime or damage to equipment.”
Optimizing in a Heterogeneous World is (Algorithms x Devices)
November 11, 2019 by Leave a Comment
In this guest article, our friends at Intel discuss how CPUs prove better for some important Deep Learning. Here’s why, and keep your GPUs handy! Heterogeneous computing ushers in a world where we must consider permutations of algorithms and devices to find the best platform solution. No single device will win all the time, so we need to constantly assess our choices and assumptions.
Data Center Transformation: Why a Workload-Driven and Scalable Architecture Matters
November 7, 2019 by Leave a Comment
The QCT Platform on Demand (QCT POD) combines advanced technology with a unique user experience to help enterprises reach better performance and gain more insights. “With flexibility and scalability, QCT POD enables enterprises to address a broader range of HPC, Deep Learning, and Data Analytic demands that fulfill various applications.”
Getting Smart About Slurm in the Cloud
October 25, 2019 by Leave a Comment
This timely article from our friends over at Univa takes a look at how often the popular HPC workload manager Slurm (Simple Linux Utility for Resource Management) is used in the cloud. In a recent InsideHPC survey sponsored by Univa, all Slurm users surveyed reported using public cloud services to at least some degree.
Deep Learning for Natural Language Processing – Choosing the Right GPU for the Job
October 23, 2019 by Leave a Comment
In this new whitepaper from our friends over at Exxact Corporation we take a look at the important topic of deep learning for Natural Language Processing (NLP) and choosing the right GPU for the job. Focus is given to the latest developments in neural networks and deep learning systems, in particular a neural network architecture called transformers. Researchers have shown that transformer networks are particularly well suited for parallelization on GPU-based systems.
Cloud Automation: Five Ways to Contain HPC Cloud Spending
October 17, 2019 by Leave a Comment
This timely article from our friends over at Univa examines how the cloud is attractive for organizations that need fast access to specialized resources, and that want to avoid the cost and complexity of on-premise infrastructure. The article then offer five important ways that Cloud Automation can reduce cost.
Heterogeneous Computing: Long Live the CPU
October 15, 2019 by Leave a Comment
In this guest article, our friends at Intel discuss how the company is investing in heterogeneous computing. Intel recently spoke about supporting heterogeneous computing with the catch phrase “One Size Does Not Fit All” in talking about software and Intel’s commitment to help programmers with oneAPI.
