April 26, 2018
Rackspace is expanding its managed private cloud services with the addition of six new bare metal instances that it collectively refers to as bare metal as a se Read more…
April 6, 2016
OpenPOWER Foundation, the mostly IBM-driven effort to create an alternative architecture to Intel x86, took a major step forward today with the announcement of a joint effort by Google and Rackspace to co-develop an open data center server architecture design specification based on... Read more…
September 5, 2013
Last week, 30 stakeholders from research and industry met at Argonne National Labs to explore the potential for cloud-based cyber-infrastructure to support existing and emerging use cases in a range of research disciplines. Read more…
July 26, 2013
A study done by Deepfield found that Google accounts for approximately 25 percent of all internet traffic in the United States. That makes it more far-reaching than Facebook, Twitter, and Netflix combined. Read more…
July 17, 2013
With the Rackspace’s announcement this month that they were getting involved with some of CERN’s cloud computing and the news of IBM acquiring SoftLayer last month, Amazon’s HPC instances may be facing some competition in the not so distant future. To battle that impending competition, Amazon reportedly dropped their price to rent their dedicated servers, machines that operate solely for one institution. Read more…
July 17, 2013
A public cloud setup and a hybrid cloud one are incompatible for comparison, according to Rackspace Chief Technology Officer John Engates. However, when Amazon announces a cost reduction that could seemingly cut into Rackspace’s business, and has incidentally has ended up dropping the Rackspace stock by 8.5 percent, there exists a necessity to shed light on those differences. Read more…
July 3, 2013
Amazon Web Services is the cloud provider most often cited in scientific articles about high performance applications in the cloud. Meanwhile, cloud competitor Rackspace has not ventured much into the high scientific computing arena. That is, until this week when Rackspace, noted provider of cloud services, will be looking at getting into the cloud based HPC game by partnering with CERN, a development that was announced on Monday. Read more…
September 25, 2012
This week, not one but two groups of IT heavyweights launched with plans to expand the scope of the Internet while protecting the free flow of ideas it provides. The Internet Infrastructure Coalition (i2Coalition) counts already 42 founding members, including infrastructure providers Rackspace, Softlayer, ProfitBricks and Tucows, while the Internet Association's 14-strong roster claims Web giants Google, Yahoo, Facebook, eBay and Amazon. Read more…
The increasing complexity of electric vehicles result in large and complex computational models for simulations that demand enormous compute resources. On-premises high-performance computing (HPC) clusters and computer-aided engineering (CAE) tools are commonly used but some limitations occur when the models are too big or when multiple iterations need to be done in a very short term, leading to a lack of available compute resources. In this hybrid approach, cloud computing offers a flexible and cost-effective alternative, allowing engineers to utilize the latest hardware and software on-demand. Ansys Gateway powered by AWS, a cloud-based simulation software platform, drives efficiencies in automotive engineering simulations. Complete Ansys simulation and CAE/CAD developments can be managed in the cloud with access to AWS’s latest hardware instances, providing significant runtime acceleration.
Two recent studies show how Ansys Gateway powered by AWS can balance run times and costs, making it a compelling solution for automotive development.
Five Recommendations to Optimize Data Pipelines
When building AI systems at scale, managing the flow of data can make or break a business. The various stages of the AI data pipeline pose unique challenges that can disrupt or misdirect the flow of data, ultimately impacting the effectiveness of AI storage and systems.
With so many applications and diverse requirements for data types, management systems, workloads, and compliance regulations, these challenges are only amplified. Without a clear, continuous flow of data throughout the AI data lifecycle, AI models can perform poorly or even dangerously.
To ensure your AI systems are optimized, follow these five essential steps to eliminate bottlenecks and maximize efficiency.
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