The Grid-Cloud Connection (Pt. II): Spare the Hype

By Derrick Harris

October 10, 2008

As we saw in the first installment, there is no denying the connection between grid computing and cloud computing.  The question going forward, however, is twofold: (1) How has the evolution from the former to the latter influenced the capabilities of dynamic datacenter solutions; and (2) How tightly are these companies willing to latch onto the cloud computing bandwagon?

The brief answer? The advent of cloud computing has drastically affected the product offerings and solutions by grid computing veterans. Everything is about flexibility, mobility, virtualization and, overall, being on-demand. As for the second prong, well, that’s not such an affirmative answer. After seeing how quickly a nebulous term can lose favor among the user community, vendors are (wisely, it would seem) betting on the delivery model but not necessarily the terminology.

Cloud, Utility, Whatever

Univa UD’s plan with its Reliance product is to help customers take advantage of their existing infrastructures by providing, among other things, application awareness, quality-of-service guarantees and automated SLAs. As noted earlier, its datacenter automation strategy no longer includes United Devices’ staple Grid MP middleware. Far from a rip-and-replace situation, the company is partnering with other vendors to ensure that previous datacenter investments are not wasted but, instead, optimized.

Univa UD is marketing Reliance as an appliance for both in-house use and for service providers looking to build their cloud or utility infrastructures. According to Alex Brown, general manager of Univa UD’s Data Center Business Division, the company has customers using it in both scenarios. A large telecom provider, he says, is using Reliance as a piece of its utility services model. The provider already has invested huge sums of money in its utility infrastructure, and Reliance will work alongside Opsware and SMART to provide maximum flexibility. On the internal side, Brown points to a customer looking to get rid of departmental resources by morphing its current infrastructure into a service-oriented one. Because it is relatively easy to make this switch in-house, Brown says products like Reliance could be called — if you you’re down with the cloud lingo — a “cloud in a box.”

Of course, not everybody is down with calling everything “cloud computing” — including Brown. Although he certainly sees Reliance as a cloud-enabling appliance, he recognizes that preferred labels differ from customer to customer, and there is no need to alienate. “I’ve been trying to avoid, necessarily, labeling us with that term [cloud computing], because at the end of the day, what Reliance will enable some people are going to call cloud, [while] others are going to call it something else — grid or utility or whatever.” However, (at the risk of “splitting hairs”) he adds that “cloud” tends to be more application-specific, whereas “utility” connotes a shared infrastructure.

Another reason for Univa UD to be careful about applying the cloud label is the fact that Reliance is not a cloud. Gordon Jackson, technical director for the company’s Data Center Business Division, notes that Reliance simply enables cloud services, it does not provide cloud services. For example, he says, Reliance could provide the intelligence for Amazon’s cloud infrastructure, but certainly would not be considered the cloud in that situation. People are started to get the nuance between these two roles, he says, but there still is some confusion, so there is no need to slap on the cloud label — at least “until the 20-odd definitions of cloud out there result in one or two concrete, or more concrete, definitions.”

Additionally, both Jackson and Brown agree that most organizations — including Univa UD’s customers — will get comfortable with internal service delivery before they start accessing services externally, so there is no need to add to the confusion between whether an internal cloud really is a cloud.  Whatever you call it, Brown says, the technology will become ubiquitous because the economics are just too compelling, and that — not a buzzword — is what Univa UD is banking on.

Let’s Just Call it all ‘Dynamic Application Service Management’

DataSynapse is a little more welcoming of the cloud computing buzz than are some of its competitors, but that doesn’t mean it expects the term to last forever.  With that in mind, says Ivan Casanova, vice president of product marketing, the company has developed its own term to encompass the whole cloud/utility computing landscape: Dynamic Application Service Management (DASM).

Casanova says the company is thinking about cloud and utility computing from two perspectives: cloud computing for the corporate datacenter and infrastructure for external cloud providers (for which he says DataSynapse already has four or five customers). Cloud or utility, internal or external, DataSynapse is putting it all under the service-based DASM banner, which Casanova says is “all about providing automated provisioning of applications for the application development teams who are responsible for building the apps that run on these clouds, and providing infrastructure teams with automated and dynamic service level capabilities.”

The DASM vision isn’t just about hosting, serving and scaling applications, says Casanova, but rather about the entire application lifecycle. Thus, DASM encompasses the entire DataSynapse product portfolio, with GridServer handling scalability, FabricServer handling packacing, provisioning, etc., and VersaVision taking care of monitoring, management and the dashboard functionality. “As the mainstream IT press starts to evangelize cloud and utility models, which really is code for ‘shared and dynamic infrastructure,’ we already have products and technologies that have been proven in the marketplace to do that,” he says.

DataSynapse’s reputation for managing large-scale computing environments has some service providers coming to it, but Casanova says the company also is selling directly to them. According to Casanova, the sales pitch goes something like this: “We’re working with a number of your competitors, here’s the value that we provide, it’s intrinsic to what they’re doing, and we have very unique and compelling capabilities in this space. If you really, truly want to be a cloud provider to corporate IT shops in any way, shape or form, then you need this type of infrastructure.”

In terms of selling in-house, Casanova sees the cloud computing movement as a “big wave” that will help DataSynapse sell outside its financial services stronghold, but believes his company’s pedigree selling grids to demanding financial institutions is a major proof-point. On top of that, working with the service providers also serves as a touch-point for new customers, some of whom, like SMBs, DataSynapse never would target. “Being the ‘Intel Inside’ model of a cloud provider lets us touch a bunch of customers that maybe we don’t have the bandwidth or the focus to get to.”

As for the term “cloud computing,” Casanova doesn’t know how long its shelf life will be, but says that the movement from static to dynamic application development isn’t going anywhere.  That sea change is akin to what’s happening in the shift from physical to virtual environments, he analogizes, and today the terms just happen to be cloud and utility.

The Application Matters

While the basic tools to build cloud or utility infrastructures exist within Platform Computing current portfolio, CEO Songnian Zhou more integration work still is needed to create full-fledged cloud infrastructures. Platform’s Enterprise Grid Orchestrator (EGO) abstracts applications from resources and orchestrates delivery based on policy, and its VM Orchestrator (VMO) orchestrates workloads that can be hosted in virtual environments. VMO sits next to Platform’s LSF and Symphony products in the architecture, and all three are underpinned by EGO. This solution set allows for separate application classes with dynamic underlying resources, Zhou says, but further work is needed to enable J2EE or locally developed applications. The same holds true for use cases, ranging from self-service VM provisioning to “full-fledged, dynamic, policy-based orchestration,” where the infrastructure shifts resources as needed without user intervention. The architecture is the same, he points out, but the tools vary.

Platform is in discussions with various partners and customers, Zhou says, and hopes to have some real cloud-like infrastructures in place within the next six months. Within the next two or three years, the company hopes to have a set of products available to address broad customer needs.

The reason for the time between now and more general-purpose utility solutions, he says, is because the community seems to be ignoring a “great chasm” between two distinct types of applications: (1) the Web 2.0 applications that companies like Amazon and Google are running and that are the basis for their infrastructures; and (2) the large majority of enterprise applications that predate these infrastructures and won’t run well in them. “That’s where, in my opinion, the approach and paradigm of cloud [computing] — call it internal cloud, call it enterprise grid, call it whatever you want — applies,” says Zhou. Over time, the internal and external paradigms will combine, with companies like Platform helping enterprises bring more applications into the cloud internally, and new applications will run in external clouds.

“If you want me to be completely honest, in the classical definition of cloud, we don’t do that,” Zhou explains. “We didn’t build that Web 2.0 infrastructure that Google and Amazon did. In the classical, true cloud, that’s what they do for those applications.” On the contrary, he says, Platform is an enterprise application vendor, “but, clearly, the methodology and thinking and vision and paradigm do apply.”

One Zhou isn’t too keen on talking about, though, is the terminology of what Platform is doing. The company has customer talking about building internal clouds, he says, but Platform remains very results-oriented — due in part to fear of a grid hype replay. Right now, he added, CIOs are bending over backward trying to explain to their bosses why the external cloud computing they’ve heard so much about is not appropriate. Just as the term “grid computing” lost its luster, Zhou says he doesn’t want to go full force into cloud because “I know in a year or two it’s going to fade away.”

He also sees the same lesson shaping up in the transition from grid computing to cloud computing. Vendors need to be very pragmatic and make the solution about the customer’s applications, and customers need to look at all available paradigms and only make changes if they can ensure value. “The biggest risk we have is to hype it up and overpromise, then under-deliver and lose our credibility,” he says. “We all got hurt on that one.”

‘I Second that Stance’

Oracle has announced plans with Intel to allow for shared infrastructures — both internal and external — running Oracle products, and even has made some available via Amazon EC2. Cloud plans for its Coherence data grid solution are less clear, but that doesn’t mean Vice President of Fusion Middleware Cameron Purdy doesn’t have thoughts on the current push toward cloud computing. And his concerns echo those espoused by Platform’s Zhou.

“Like a lot of big shifts in our industry, I think, quite often, what ends up happening is quite different than what people initially expect to happen,” he explains. “I think it’s pretty safe to say that the first wave that you see is typically companies repositioning legacy products as the new thing, and I think cloud computing is no different. Long term, I think what will emerge will be far different than what people are discussing today.”

He adds that at the end of the day, it’s way more about delivering tangible business benefits than about delivering a catchy name. “[W]e’re either going to create additional value for our customers, or there will be no such market emerging in the long run.”

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from its predecessors, including the red-hot H100 and A100 GPUs. Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. While Nvidia may not spring to mind when thinking of the quant Read more…

2024 Winter Classic: Meet the HPE Mentors

March 18, 2024

The latest installment of the 2024 Winter Classic Studio Update Show features our interview with the HPE mentor team who introduced our student teams to the joys (and potential sorrows) of the HPL (LINPACK) and accompany Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the field was normalized for boys in 1969 when the Apollo 11 missi Read more…

Apple Buys DarwinAI Deepening its AI Push According to Report

March 14, 2024

Apple has purchased Canadian AI startup DarwinAI according to a Bloomberg report today. Apparently the deal was done early this year but still hasn’t been publicly announced according to the report. Apple is preparing Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimization algorithms to iteratively refine their parameters until Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimizat Read more…

PASQAL Issues Roadmap to 10,000 Qubits in 2026 and Fault Tolerance in 2028

March 13, 2024

Paris-based PASQAL, a developer of neutral atom-based quantum computers, yesterday issued a roadmap for delivering systems with 10,000 physical qubits in 2026 a Read more…

India Is an AI Powerhouse Waiting to Happen, but Challenges Await

March 12, 2024

The Indian government is pushing full speed ahead to make the country an attractive technology base, especially in the hot fields of AI and semiconductors, but Read more…

Charles Tahan Exits National Quantum Coordination Office

March 12, 2024

(March 1, 2024) My first official day at the White House Office of Science and Technology Policy (OSTP) was June 15, 2020, during the depths of the COVID-19 loc Read more…

AI Bias In the Spotlight On International Women’s Day

March 11, 2024

What impact does AI bias have on women and girls? What can people do to increase female participation in the AI field? These are some of the questions the tech Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Analyst Panel Says Take the Quantum Computing Plunge Now…

November 27, 2023

Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Training of 1-Trillion Parameter Scientific AI Begins

November 13, 2023

A US national lab has started training a massive AI brain that could ultimately become the must-have computing resource for scientific researchers. Argonne N Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire