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 industy updates delivered to you every week!

US Exascale Computing Update with Paul Messina

December 8, 2016

Around the world, efforts are ramping up to cross the next major computing threshold with machines that are 50-100x more performant than today’s fastest number crunchers.  Read more…

By Tiffany Trader

Weekly Twitter Roundup (Dec. 8, 2016)

December 8, 2016

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

Qualcomm Targets Intel Datacenter Dominance with 10nm ARM-based Server Chip

December 8, 2016

Claiming no less than a reshaping of the future of Intel-dominated datacenter computing, Qualcomm Technologies, the market leader in smartphone chips, announced the forthcoming availability of what it says is the world’s first 10nm processor for servers, based on ARM Holding’s chip designs. Read more…

By Doug Black

Which Schools Produce the Top Coders in the World?

December 8, 2016

Ever wonder which universities worldwide produce the best coders? The answers may surprise you, at least as judged by the results of a competition posted yesterday on the HackerRank blog. Read more…

By John Russell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. The pilots, supported in part by DOE exascale funding, not only seek to do good by advancing cancer research and therapy but also to advance deep learning capabilities and infrastructure with an eye towards eventual use on exascale machines. Read more…

By John Russell

DDN Enables 50TB/Day Trans-Pacific Data Transfer for Yahoo Japan

December 6, 2016

Transferring data from one data center to another in search of lower regional energy costs isn’t a new concept, but Yahoo Japan is putting the idea into transcontinental effect with a system that transfers 50TB of data a day from Japan to the U.S., where electricity costs a quarter of the rates in Japan. Read more…

By Doug Black

Infographic Highlights Career of Admiral Grace Murray Hopper

December 5, 2016

Dr. Grace Murray Hopper (December 9, 1906 – January 1, 1992) was an early pioneer of computer science and one of the most famous women achievers in a field dominated by men. Read more…

By Staff

Ganthier, Turkel on the Dell EMC Road Ahead

December 5, 2016

Who is Dell EMC and why should you care? Glad you asked is Jim Ganthier’s quick response. Ganthier is SVP for validated solutions and high performance computing for the new (even bigger) technology giant Dell EMC following Dell’s acquisition of EMC in September. In this case, says Ganthier, the blending of the two companies is a 1+1 = 5 proposition. Not bad math if you can pull it off. Read more…

By John Russell

US Exascale Computing Update with Paul Messina

December 8, 2016

Around the world, efforts are ramping up to cross the next major computing threshold with machines that are 50-100x more performant than today’s fastest number crunchers.  Read more…

By Tiffany Trader

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. The pilots, supported in part by DOE exascale funding, not only seek to do good by advancing cancer research and therapy but also to advance deep learning capabilities and infrastructure with an eye towards eventual use on exascale machines. Read more…

By John Russell

Ganthier, Turkel on the Dell EMC Road Ahead

December 5, 2016

Who is Dell EMC and why should you care? Glad you asked is Jim Ganthier’s quick response. Ganthier is SVP for validated solutions and high performance computing for the new (even bigger) technology giant Dell EMC following Dell’s acquisition of EMC in September. In this case, says Ganthier, the blending of the two companies is a 1+1 = 5 proposition. Not bad math if you can pull it off. Read more…

By John Russell

AWS Launches Massive 100 Petabyte ‘Sneakernet’

December 1, 2016

Amazon Web Services now offers a way to move data into its cloud by the truckload. Read more…

By Tiffany Trader

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Seagate-led SAGE Project Delivers Update on Exascale Goals

November 29, 2016

Roughly a year and a half after its launch, the SAGE exascale storage project led by Seagate has delivered a substantive interim report – Data Storage for Extreme Scale. Read more…

By John Russell

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

HPE-SGI to Tackle Exascale and Enterprise Targets

November 22, 2016

At first blush, and maybe second blush too, Hewlett Packard Enterprise’s (HPE) purchase of SGI seems like an unambiguous win-win. SGI’s advanced shared memory technology, its popular UV product line (Hanna), deep vertical market expertise, and services-led go-to-market capability all give HPE a leg up in its drive to remake itself. Bear in mind HPE came into existence just a year ago with the split of Hewlett-Packard. The computer landscape, including HPC, is shifting with still unclear consequences. One wonders who’s next on the deal block following Dell’s recent merger with EMC. Read more…

By John Russell

Why 2016 Is the Most Important Year in HPC in Over Two Decades

August 23, 2016

In 1994, two NASA employees connected 16 commodity workstations together using a standard Ethernet LAN and installed open-source message passing software that allowed their number-crunching scientific application to run on the whole “cluster” of machines as if it were a single entity. Read more…

By Vincent Natoli, Stone Ridge Technology

IBM Advances Against x86 with Power9

August 30, 2016

After offering OpenPower Summit attendees a limited preview in April, IBM is unveiling further details of its next-gen CPU, Power9, which the tech mainstay is counting on to regain market share ceded to rival Intel. Read more…

By Tiffany Trader

AWS Beats Azure to K80 General Availability

September 30, 2016

Amazon Web Services has seeded its cloud with Nvidia Tesla K80 GPUs to meet the growing demand for accelerated computing across an increasingly-diverse range of workloads. The P2 instance family is a welcome addition for compute- and data-focused users who were growing frustrated with the performance limitations of Amazon's G2 instances, which are backed by three-year-old Nvidia GRID K520 graphics cards. Read more…

By Tiffany Trader

Think Fast – Is Neuromorphic Computing Set to Leap Forward?

August 15, 2016

Steadily advancing neuromorphic computing technology has created high expectations for this fundamentally different approach to computing. Read more…

By John Russell

The Exascale Computing Project Awards $39.8M to 22 Projects

September 7, 2016

The Department of Energy’s Exascale Computing Project (ECP) hit an important milestone today with the announcement of its first round of funding, moving the nation closer to its goal of reaching capable exascale computing by 2023. Read more…

By Tiffany Trader

ARM Unveils Scalable Vector Extension for HPC at Hot Chips

August 22, 2016

ARM and Fujitsu today announced a scalable vector extension (SVE) to the ARMv8-A architecture intended to enhance ARM capabilities in HPC workloads. Fujitsu is the lead silicon partner in the effort (so far) and will use ARM with SVE technology in its post K computer, Japan’s next flagship supercomputer planned for the 2020 timeframe. This is an important incremental step for ARM, which seeks to push more aggressively into mainstream and HPC server markets. Read more…

By John Russell

IBM Debuts Power8 Chip with NVLink and Three New Systems

September 8, 2016

Not long after revealing more details about its next-gen Power9 chip due in 2017, IBM today rolled out three new Power8-based Linux servers and a new version of its Power8 chip featuring Nvidia’s NVLink interconnect. Read more…

By John Russell

Vectors: How the Old Became New Again in Supercomputing

September 26, 2016

Vector instructions, once a powerful performance innovation of supercomputing in the 1970s and 1980s became an obsolete technology in the 1990s. But like the mythical phoenix bird, vector instructions have arisen from the ashes. Here is the history of a technology that went from new to old then back to new. Read more…

By Lynd Stringer

Leading Solution Providers

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

Intel Launches Silicon Photonics Chip, Previews Next-Gen Phi for AI

August 18, 2016

At the Intel Developer Forum, held in San Francisco this week, Intel Senior Vice President and General Manager Diane Bryant announced the launch of Intel's Silicon Photonics product line and teased a brand-new Phi product, codenamed "Knights Mill," aimed at machine learning workloads. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Dell EMC Engineers Strategy to Democratize HPC

September 29, 2016

The freshly minted Dell EMC division of Dell Technologies is on a mission to take HPC mainstream with a strategy that hinges on engineered solutions, beginning with a focus on three industry verticals: manufacturing, research and life sciences. "Unlike traditional HPC where everybody bought parts, assembled parts and ran the workloads and did iterative engineering, we want folks to focus on time to innovation and let us worry about the infrastructure," said Jim Ganthier, senior vice president, validated solutions organization at Dell EMC Converged Platforms Solution Division. Read more…

By Tiffany Trader

Beyond von Neumann, Neuromorphic Computing Steadily Advances

March 21, 2016

Neuromorphic computing – brain inspired computing – has long been a tantalizing goal. The human brain does with around 20 watts what supercomputers do with megawatts. And power consumption isn’t the only difference. Fundamentally, brains ‘think differently’ than the von Neumann architecture-based computers. While neuromorphic computing progress has been intriguing, it has still not proven very practical. Read more…

By John Russell

Container App ‘Singularity’ Eases Scientific Computing

October 20, 2016

HPC container platform Singularity is just six months out from its 1.0 release but already is making inroads across the HPC research landscape. It's in use at Lawrence Berkeley National Laboratory (LBNL), where Singularity founder Gregory Kurtzer has worked in the High Performance Computing Services (HPCS) group for 16 years. Read more…

By Tiffany Trader

Micron, Intel Prepare to Launch 3D XPoint Memory

August 16, 2016

Micron Technology used last week’s Flash Memory Summit to roll out its new line of 3D XPoint memory technology jointly developed with Intel while demonstrating the technology in solid-state drives. Micron claimed its Quantx line delivers PCI Express (PCIe) SSD performance with read latencies at less than 10 microseconds and writes at less than 20 microseconds. Read more…

By George Leopold

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This