The Grid-Cloud Connection (Pt. I): Compare and Contrast

By Derrick Harris

October 8, 2008

Grid computing. Cloud computing. Are there any IT paradigms that have garnered more hype and more skepticism without most people even knowing what they mean? Probably not, but maybe that is because the terms themselves have no real meanings to most IT consumers, just connotations.

And connotations can be scary. Burned to some degree by the existing confusion surrounding grid computing, many grid vendors have drastically cut the term from their marketing strategies. Learning from what might be perceived as mistakes, these vendors are not so quick to latch onto cloud computing. However, many of their new directions could easily fall under the cloud umbrella, and those in the know readily acknowledge that grid technologies underlie the cloud.

So, what’s a middleware vendor to do?

First, Compare

Within the Data Center Business Division at Univa UD, messaging around grid computing has been all but eliminated as the division attempts to build traction for its Reliance datacenter orchestration product (from which the company also has nixed the Grid MP middleware component). What division general manager Alex Brown calls the “traffic cop or brains of the operation,” Reliance combines application awareness, closed-loop orchestration and SLA automation to deliver optimal application performance, and Univa UD customers and prospects view it as a key part of their cloud or utility infrastructures.

Although no one is talking about grid computing, Univa UD’s Gordon Jackson says the company’s experiences with grid and large-scale distributing processing management feed directly into its success with Reliance, especially as it relates to resource management and distribution. Jackson is the technical director of the Data Center Business Division former virtualization evangelist at DataSynapse.

Brown agrees that a real cloud-like solution requires a significant understanding of grid concepts. “However, because people thought of grid as so specialized, it got a lot of baggage,” he explains. “So while a lot of the core technology is very relevant, a lot of the terminology and a lot of the old processes are not. In fact, they hinder the adoption of the technology for cloud.”

Ivan Casanova, vice president of product marketing at the aforementioned DataSynapse sees a connection, too, calling grid computing the starting point for cloud computing — “a proof point for shared and dynamic infrastructure.” A big part of cloud computing is the ability to scale based on demand, and grid computing middleware is a great method for doing so, he says. (Casanova also notes that SOA is the architectural model for cloud computing, and DataSynapse has customers deploying SOAs and using the company’s GridServer product to scale those services.)

On the data grid front, Oracle’s Cameron Purdy, vice president of Fusion Middleware, says, “Data grid technology … is almost essential in any transactional processing or other data-intensive system that would be deployed into a cloud environment. I can’t imagine how you would run a data-intensive application across any number of servers in that type of environment without the ability to share and coordinate access to and operate and react to changes and events occurring to that information.”

According to Platform Computing Chairman and CEO Songnian Zhou, his customers definitely see the grid-cloud connection as they move from HPC-focused enterprise grids to general-purpose, often virtualized, shared-services platforms. “They may not call it cloud, they may not call it on-demand datacenter, but they clearly are doing it,” he says.

The transition from grid to cloud, at least internally, Zhou says, is really a matter of evolution: the architectures and goals are the same, but the scope is different. As users move from HPC workloads to more generic workloads, they add components like J2EE middleware and hypervisors to enable more dynamic applications and increase mobility. “The tools and containers need to be brought to the plate, but [in terms of] fundamental architecture and approach, I don’t see much of a difference between grid and the cloud or on-demand or dynamic datacenter,” he says. “It’s a continuous evolution and expansion … away from the siloed client servers.”

Univa UD’s Jackson also sees this move happening. Even in HPC, he believes, grid is ripe to become a platform for serving multiple applications and classes of users. “[A]s soon as you start applying the intelligence to differentiate between the platinum customer and the bronze customer, or the applications … and services I need to execute on behalf of those customers, then I think you’ve taken your grid and you’ve turned it into a utility infrastructure,” he says. Moving discrete grids into one big, intelligent resource pool means the most bang for the buck for the corporation, he added.

Paul Strong, distinguished engineer at eBay Research Labs and active Open Grid Forum participant, isn’t even sure we should draw the distinction between so-called internal clouds and service-oriented grids. In either case, users are leveraging shared infrastructures and virtualization to achieve high utilization and application flexibility based on changes in workloads and business needs. Essentially, Strong says, users are solving the same problems with the same core technologies.

This is true even for eBay’s infrastructure, which Strong has explained as a grid for years. There are many “cloudy” aspects to eBay’s infrastructure, he says, including a heavily virtualized database architecture to allow for massive scalability, and global service delivery backed up by SLAs, continuous availability and security. “By some definition of the word,” he acknowledges, “I would say we’ve been doing aspects of cloud computing for a while.”

Second, Contrast

There are, however, differences between the grid and the cloud, especially, but not exclusively, where external cloud services are involved. Univa UD’s Brown makes a marked distinction between the two paradigms. For him, grid computing (on the enterprise front, at least) takes place inside the firewall. Apparently, Univa UD also notices grid computing’s HPC connotation, as the company has moved its Grid MP middleware to its HPC division, leaving (as noted above) the datacenter division to focus on Reliance and its automation capabilities.

A similar mindset seems to be present at Platform. Although not formally in place, Zhou says the company is moving toward two distinct foci — HPC and the datacenter. Regardless of the technological similarities, customers see grid computing being part of the former and cloud computing (to whatever degree the term arises) being part of the latter. As the datacenter division takes shape, Zhou says, “We will not emphasize grid much because for datacenters, I think, grid is foreign. It has too much connotation, it is tainted from the HPC or research and government space, and it’s too complex.”

At DataSynapse, the difference is very application-focused. Casanova believes grid addresses a specific class of applications, which have been successfully optimized using the company’s GridServer product. When customers wanted to run a more general class of applications on a shared, dynamic infrastructure, the result was DataSynapse’s FabricServer product. Going forward, both are part of the company’s greater application-focused cloud-like strategy.

“I don’t think people started out envisioning grid computing to be this seamless model where all these enterprise services or different types of applications were running in a cloud, they were universally accessible, they were technology-agnostic,” says Casanova. “I think they started that conversation around ‘I really need to scale up this application from a performance perspective, and I want to leverage commodity hardware and systems I already own to help me [experience] an order of magnitude improvement [in how] this important application executes.'” The cloud movement inside organizations, he adds, really has been driven by what they see Internet companies like Amazon doing with their infrastructures.

Further illustrating the fundamental differences between the paradigms, Casanova cites capabilities that must be added to grid solutions if they are to be repackaged and sold as cloud solutions: automated provisioning, horizontal scalability and visibility into utilization. For corporate users, he says, utilization insight helps them define policies to further automate and maximize resource usage. For cloud service providers, he says, usage data becomes the foundation for their chargeback models.

eBay’s Strong views grids and external clouds “less in terms of technology and more in terms of the way we think differently about business.” With cloud computing, he says, all a company needs to do is codify its one differentiating idea. The company can obtain everything else — infrastructure, non-critical business services, etc. — from the cloud.

Grid computing, Strong explains, was about building and optimizing infrastructure to run certain types of workloads. Cloud computing complements and advances that notion, but also helps companies move away from the “nitty-gritty” aspects, he says. It’s more about flexibly delivering services within an organization (internal cloud) or flexibly receiving commodity services (external cloud). “I think clouds take us to that next conceptual step of moving beyond … the weeds, where a lot of the grid work was, to [asking] ‘How do we move this closer to the business and deliver the right value for the business?'” Strong says. “The set of underlying technologies are, in essence, the same, but the discussion has changed.”


Up next: The second half of our look at the nexus of grid computing and cloud computing will focus on the future dynamic datacenter-oriented strategies of these old-guard grid computing vendors. We’ll look at how, if at all, they plan to leverage cloud computing hype as a marketing term, and how the idea of cloud computing actually relates to what they’re doing.

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!

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

Nvidia Appoints Andy Grant as EMEA Director of Supercomputing, Higher Education, and AI

March 22, 2024

Nvidia recently appointed Andy Grant as Director, Supercomputing, Higher Education, and AI for Europe, the Middle East, and Africa (EMEA). With over 25 years of high-performance computing (HPC) experience, Grant brings a Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

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

March 18, 2024

Nvidia's latest and fastest GPU, codenamed 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…

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…

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…

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…

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…

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…

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

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…

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…

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…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire