Sign up for our newsletter and get the latest HPC news and analysis.
Send me information from insideHPC:

Red Hat Teams with NVIDIA to Accelerate Machine Learning in the Cloud

Today Red Hat announced it has deepened its alliance with NVIDIA to accelerate the enterprise adoption of AI, machine learning and data analytics workloads in production environments. To move thins along, Red Hat is launching an early access program for prospective customers. “High-performance technologies are moving at a brisk rate into enterprise data centers to accelerate product development and business operations – including financial services, ERP and sales analysis, fraud detection and cybersecurity, and machine learning-AI,” said Steve Conway, senior vice president of research, Hyperion Research. “The hybrid cloud solutions from Red Hat and NVIDIA are designed to make accelerated computing use easier for enterprises on-premise and in the cloud.”

Google Cloud TPU Pods Speed Machine Learning

Today Google announced that its Google Cloud TPU Pods are now publicly available in beta. Designed to help Machine Learning researchers iterate faster and train more capable machine learning models, TPU Pods can include more than 1,000 individual TPU chips connected by an ultra-fast, two-dimensional toroidal mesh network.

DDN Moves Closer to the Edge with Nexenta Acquisition

Today DDN announced its intent to acquire Nexenta, the market leader in Software Defined Storage for 5G and Internet of Things (IoT). “Our clients benefit from the flexibility and performance of Nexenta’s robust SDS solutions and platform-agnostic strategy, which provide great differentiation for the HPC, AI, and high-performance data analytics (HPDA) verticals we serve. With escalating demands from our clients for ultra-scalable compute and data storage platforms, we look forward to the exciting developments which will result from this new relationship.”

Interview: Cray in Azure Steps up with Dedicated Supercomputing in the Cloud

In this interview, Joseph George from Cray describes the company’s new offerings for Cray in Azure. “The Cray and Microsoft Azure teams have been actively working on numerous customer engagements together, in an effort to clearly understand the optimal cloud model for large scale HPC workloads, and the best consumption model for HPC users. With all that research as a foundation, it has become clear to us that a dedicated and reserved instance cloud model allows for an ideal HPC experience at large scale.”

Video: NAG Launches HPC Cost of Ownership Calculator

In this video, Mike Croucher from NAG demonstrates the company’s new Total Cost of Ownership Calculator for HPC. “Should your next HPC procurement be on-premise or in the cloud? This is one of the questions that our clients ask us to help with and part of the answer involves Total Cost of Ownership of the resulting facility. This calculator is provided as a working example of a TCO model.”

Cornell Investigates Multi-cloud Cost Management with RightScale

The Cornell University Center for Advanced Computing (CAC) is collaborating with RightScale, recently acquired by Flexera, to understand how to best manage and optimize costs in a multi-cloud world. “Universities and research facilities are beginning to recognize that cloud management platforms (CMPs) are a useful tool for monitoring and controlling research expenditures, particularly as scientists seek different clouds for different capabilities,” said David A. Lifka, vice president for information technologies and CIO at Cornell. “By working with the Optima team, we’re adding to our current CMP experience and gaining knowledge on how to effectively address the unique needs of research computing and education users.”

HPC Breaks Through to the Cloud: Why It Matters

In this special guest feature, Scot Schultz from Mellanox writes researchers are benefitting in a big way from HPC in the Cloud. “HPC has many different advantages depending on the specific use case, but one aspect that these implementations have in common is their use of RDMA-based fabrics to improve compute performance and reduce latency.”

Micron steps up with NVMe SSDs

Micron recently unveiled its new series of flagship solid-state drives (SSDs) featuring the NVMe protocol, bringing industry-leading storage performance at higher capacities to cloud and enterprise computing markets. The Micron 9300 series of NVMe SSDs enables companies with data-intensive applications to access and process data faster, helping reduce response time.

Is Ubiquitous Cloud Bursting on the Horizon for Universities?

In this special guest feature from Scientific Computing World, Mahesh Pancholi from OCF writes a growing number of universities are taking advantage of public cloud infrastructures that are widely available from large companies like Amazon, Google and Microsoft. “Public cloud providers are surveying the market and partnering with companies, like OCF, for their pedigree in providing solutions to the UK Research Computing community. In order to help Universities take advantage of their products by integrating them with the existing infrastructure such as HPC clusters.”

Personalized Healthcare with High Performance Computing in the Cloud

Wolfgang Gentzsch from the UberCloud gave this talk at the HPC User Forum. “The concept of personalized medicine has its roots deep in genomic research. Indeed, the successful completion of the Human Genome Project in 2003 marked a critical milestone for the field. That project took $3 billion over 13 years. Today, thanks to technological progress, a similar sequencing task would take only about $4,000 and a few weeks. Such computational power is possible thanks to cloud technology, which eliminates the barriers to high-performance computing by removing software and hardware constraints.”