August 20196 For a large portion of the decade, HPC and supercomputing were intrinsically linked where specialized computing resources were necessary to help researchers and scientists extracts insights from massive data sets. HPC confined was high to the domains of top-tier research universities, global banks, and the energy industry owing to skyrocketing infrastructure budgets.However, in the last few years, HPC has become more accessible, with parallel computing on a large number of servers proving to be more efficient than specialized systems. The technology is gaining massive traction in computing research with the ability to quickly generate insights from large data sets, allowing for breakthroughs like more immediate cancer detection, as well as advancing promising technologies like artificial intelligence.While a majority of HPC work continues performed in-house, in dedicated or private clouds, HPC workloads in public cloud are significantly growing. More HPC friendly options from large public cloud providers like Amazon Web Services and Microsoft Azure are attracting traditional HPC users, who are now able to use the public cloud to extend what they do on-premise. Non-traditional HPC users are also leveraging public cloud HPC solutions to solve machine learning and artificial intelligence challenges.Massive data sets are now being used to train machine learning models, while computing capacity has increased to train larger and more complex models faster. With the help of HPCs, it's no longer cutting edge to create AI chatbots that can answer customer questions, build recommendation engines that suggest "what to buy next" or develop voice recognition software for the masses. Moreover, technologies like Siri and shopping experiences on Amazon.com are evolving owing to the highly sophisticated AI concepts introduced to the mainstream and have upped the game on what customers expect from businesses, and what companies can offer. Amidst this development, GPUs-that were initially built for high-resolution gaming are also being used to perform data-intensive work ranging from machine learning to self-driving cars. GPUs have proven to be superior chips for processing HPC workloads due to their singular focus on data computations. It's a highly exciting time for HPC providers now that the tools available to synthesize and process data have matured to take high-performance computing from the research labs to the mainstream. This edition brings you some of the most prominent players operating in the HPC landscape that have excelled with their service and will be significant drivers of the trends above to the mainstream.Let us know your thoughts!Annie Johnson To subscribe to APACCIOOutlookVisit www.apacciooutlook.comArt & GraphicsAmelia StewartFlynn SmythToby LangtonJie Ch'angManaging EditorAnnie JohnsonEditorialAggregating the Computing Power Senior WritersLane Adams Clara MathewRoyce D'SouzaEditorialAlfred MardinLouis BeckerRachael ClarkRoy ChowDai ShihShiv ShankerCopyright © 2019 ValleyMedia Inc. All rights reserved. Reproduction in whole or part of any text, photography or illustrations without written permission from the publisher is prohibited. The publisher assumes no responsibility for unsolicited manuscripts, photographs or illustrations. Views and opinions expressed in this publication are not necessarily those of the magazine and accordingly, no liability is assumed by the publisher thereof.AUGUST - 05 - 2019, Volume 05 - Issue - 38 (ISSN 2644-2876)Published by ValleyMedia Inc.*"Some of the Insights are based on the interviews with respective CIOs and CXOs to our editorial staff"Emailsales@apacciooutlook.comeditor@apacciooutlook.commarketing@apacciooutlook.comContact usPhone: +1 510.996.5168Fax: 510-894-8405Annie JohnsonManaging Editoreditor@apacciooutlook.com
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