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Why hardware matters in the cognitive enterprise

The hallmark of the cognitive enterprise will be optimized technology stacks that meet the demands of AI workloads – and that must start with hardware.

As the industrial age gives way to the digital era, automation and various forms of artificial intelligence (AI) are driving a fundamental shift in how enterprises engage with customers, deliver services and optimize business functions.

Leading organizations are using AI to enable rapid decision making, capture and codify value-driving organizational expertise, and to deliver actionable insights at the point of engagement. The application of these technologies demands that organizations reshape both their organizational models and their technology stack to transform themselves into what we call a Cognitive Enterprise.

While most enterprises are at some stage of their technology transformation, many of them are taking too narrow a view and looking only at the software layer as they do so. This limited focus may prove to be a mistake, as the demands of the cognitive enterprise require a reimagining of the stack from hardware on up.

Why software is not enough

The industry is in the throes of a movement toward ‘software-defined’ architectures. The rationale is compelling: abstract the software that provides logic, orchestration, and management from the physical infrastructure and you get vastly improved efficiency and agility.

As a result, this software-defined approach was one of the chief enablers as cloud companies deployed what we now call web-scale architectures.

Understandably, enterprise organizations have been frantically trying to replicate these approaches as they strive to transform themselves. There are, therefore, now viewing infrastructure as a pure commodity and focusing all of their efforts on software optimization.

Because of their compute-intensive nature, however, AI workloads require an optimized stack that extends beyond the software layer and which optimizes both the underlying hardware as well as the integration among software components.

Web-scale companies have already realized this dependence on optimized hardware and have therefore been developing proprietary, purpose-built, and fully integrated architectures from the hardware layer on up to power their demanding AI workloads.

Enterprise organizations are likewise finding that their AI workloads are driving exponential growth in both data and compute demand and they will, therefore, need to follow suit.

The AI-optimized stack

As organizations begin to develop their AI-optimized stack, they quickly realize that commodity hardware is insufficient for the optimization they seek. Such optimization must start at the processor level with a laser-focus on removing bottlenecks, increasing core performance, expanding memory bandwidth and enabling compute acceleration.

But creating an AI-optimized stack is about more than just having optimized hardware. They must also tune their entire software stack to meet the particular needs of AI workloads.

This software optimization must occur at two levels. First, the software must be optimized to work with the specialized hardware to fully take advantage of these purpose-built hardware innovations. Second, the software must be configured to work together as efficiently as possible in the context of workload demands.

The Intellyx take

As enterprise leaders transform their organizations into cognitive enterprises, they will need to differentiate workloads based on both business value and the demands they place on the technology stack.

The most critical to their transformative efforts will be these intensive AI workloads, which will leave them seeking the most effective ways to rapidly build and deploy stacks optimized to power them.

IBM has developed fully integrated and vertically-oriented solutions to help enterprise organizations more rapidly deploy these AI-optimized architectures and realize value more quickly. Its approach includes purpose-built hardware solutions based on its new POWER9 chip, along with a full complement of open source packages IBM has optimized for its hardware and to meet the demands of AI (what it calls its PowerAI offering).

Whether or not organizations use these sorts of pre-built solutions, their objective must be to focus on optimizing the stack for the particular demands of AI workloads and then ensure that they can rapidly deploy these architectures to meet dynamically changing business demands. The ability to do so will be one of the hallmarks of the cognitive enterprise.

Copyright © Intellyx LLC. IBM is an Intellyx client. Intellyx retains full editorial control over the content of this paper.

This article was originally published on the IBM website: https://www.ibm.com/blogs/systems/why-hardware-matters-in-the-cognitive-enterprise/

Read the original blog entry...

More Stories By Jason Bloomberg

Jason Bloomberg is the leading expert on architecting agility for the enterprise. As president of Intellyx, Mr. Bloomberg brings his years of thought leadership in the areas of Cloud Computing, Enterprise Architecture, and Service-Oriented Architecture to a global clientele of business executives, architects, software vendors, and Cloud service providers looking to achieve technology-enabled business agility across their organizations and for their customers. His latest book, The Agile Architecture Revolution (John Wiley & Sons, 2013), sets the stage for Mr. Bloomberg’s groundbreaking Agile Architecture vision.

Mr. Bloomberg is perhaps best known for his twelve years at ZapThink, where he created and delivered the Licensed ZapThink Architect (LZA) SOA course and associated credential, certifying over 1,700 professionals worldwide. He is one of the original Managing Partners of ZapThink LLC, the leading SOA advisory and analysis firm, which was acquired by Dovel Technologies in 2011. He now runs the successor to the LZA program, the Bloomberg Agile Architecture Course, around the world.

Mr. Bloomberg is a frequent conference speaker and prolific writer. He has published over 500 articles, spoken at over 300 conferences, Webinars, and other events, and has been quoted in the press over 1,400 times as the leading expert on agile approaches to architecture in the enterprise.

Mr. Bloomberg’s previous book, Service Orient or Be Doomed! How Service Orientation Will Change Your Business (John Wiley & Sons, 2006, coauthored with Ron Schmelzer), is recognized as the leading business book on Service Orientation. He also co-authored the books XML and Web Services Unleashed (SAMS Publishing, 2002), and Web Page Scripting Techniques (Hayden Books, 1996).

Prior to ZapThink, Mr. Bloomberg built a diverse background in eBusiness technology management and industry analysis, including serving as a senior analyst in IDC’s eBusiness Advisory group, as well as holding eBusiness management positions at USWeb/CKS (later marchFIRST) and WaveBend Solutions (now Hitachi Consulting).

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