The Enemies of Interoperability

By Nicole Hemsoth

February 2, 2011

Each week, new insights from the world of interoperability and cloud standards bubble forth, yet despite the constant chatter, there are still dramatic hurdles that must be overcome before interoperability becomes a reality.

Among some of the voices advocating for a change in how cloud computing standards might evolve into workable, sustaining solutions recently was John Considine, former Director of the Platform Products Group at Sun (which he entered following the company’s acquisition of Pirus Networks). Considine is the founder and CTO behind Boston-based CloudSwitch.

In a recent opinion piece, Considine stated that although cloud’s end users desire genuine interoperability–to be able to find the most suitable cloud offering for their needs without being burdened by the concern that the cloud they choose might lock them in later—the current state of offerings makes this impossible in the near term.

Ideally, if we lived in a world of true interoperability, a customer would be able to pick a cloud provider for a particular workload and then, if she decided to move on or the general needs altered, it would be possible to seamlessly move that workload back to the company datacenter or into any number of other cloud environments—all without a major undertaking, which is what such a shift would likely cause.

In Considine’s view, the true enemies of interoperability are as follows:

  • There are many types of requirements from end users feeding into the cloud definition; customers are looking for architectures in the cloud that match their application configurations, performance requirements, geographic locations, and security concerns.  They want specific infrastructure capabilities (think SANs, network gear, and hypervisors) because these are existing enterprise standards, and look for specific flavors of architecture/topologies/OS that most closely match what they already have.
  • This range of customer requirements creates opportunities for cloud providers to differentiate based on features and services that let them serve specific market segments better than their competitors – think security, performance, specialties (like government or medical), or even different hypervisors (for compatibility with in-house platforms), networking architectures, and pricing models.
  • The competition among cloud providers in turn leads to intense “land grabs” by technology vendors in the cloud market. This includes the big guys like VMware, Microsoft, and Citrix as well as startups like Eucalyptus, Cloud.com, and Nimbula.  It also includes most of the networking players and many of the IT ops providers. Each of these vendors has a different view on how cloud infrastructure should be built and managed (using their solutions and core components), and these differences alter the design of the cloud as well as the attributes of the cloud that the end users can control. 

Considine’s more recent experiences with CloudSwitch provide him with something of a unique point of view in that he works with both enterprises and the cloud providers in bridging the needs of both. He provided some context for one of the largest enemies of interoperability, which is rooted in architecture, stating:

“What we’ve seen is that the cloud providers—the people providing the core infrastructure, at least in the IaaS sphere—have to make choices on their architectures…If someone builds a cloud they have to pick everything from hypervisors, storage, servers, storage networking and the core network, but those choices are always informed by the design center, which dictates who and what market they want to go after and what they want to provide to with their cloud offering.

He gives some context to this idea, noting that in the early days of cloud computing, the architectures were structured according to the dominant needs of the time. Thus, in the case of Amazon, the design center’s goals were to structure clouds around Web 2.0 concepts since customers were driven by web-facing applications and an associated architecture to support them.

“Invariably they were driven toward highly stateless architecture; storage was not very important because the driving factors were really read-only. They were trying to optimize for the public facing website networking capabilities so that architecture became the basis of those clouds…As you can imagine that decision in terms of equipment and architecture was not a good match for backoffice applications or even potentially HPC.

So you see, the cloud providers have to make these decisions and it kind of permeates everything they do; when you start talking about formats for machine images or network options or even applications (in the early days in Amazon there was no persistent storage so if you shut down your instance or it crashed, everything was gone) you see how this is not a good fit for enterprise applications.”

In short, the decisions that cloud providers make dictates the kinds of workloads they can support, but with this differentiation rooted in the design center—the hub of these decisions based on what markets they want to chase—comes even further divergence from any goal of convergence.

“Image formats, storage and how you manage it, pricing and SLA agreements, quality of service—these all have different parameters because the fundamental architectures are different. So instead of cloud providers trying to drive to a common architecture they’re actually driven to an uncommon architecture; an unshared vision of how the cloud should be built.”

Near the end of our chat, we discussed the issue of possible solutions, or at least hopeful signs of progress in the right direction for interoperability. Perhaps not surprisingly, his answer was rather bleak.

He stated that while he doesn’t see anything hopeful on the horizon, there are some interesting projects that do show some sparks of progress in the right direction, including OpenStack, which is the open source collaboration that is being promoted by Rackspace. Again, despite the designation of “open” and NASA involvement, the primary vendor behind the push is one of the world’s largest hosting companies, which does change the nature of the offering to some extent.
 

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!

Data Vortex Users Contemplate the Future of Supercomputing

October 19, 2017

Last month (Sept. 11-12), HPC networking company Data Vortex held its inaugural users group at Pacific Northwest National Laboratory (PNNL) bringing together about 30 participants from industry, government and academia t Read more…

By Tiffany Trader

AI Self-Training Goes Forward at Google DeepMind

October 19, 2017

DeepMind, Google’s AI research organization, announced today in a blog that AlphaGo Zero, the latest evolution of AlphaGo (the first computer program to defeat a Go world champion) trained itself within three days to play Go at a superhuman level (i.e., better than any human) – and to beat the old version of AlphaGo – without leveraging human expertise, data or training. Read more…

By Doug Black

Researchers Scale COSMO Climate Code to 4888 GPUs on Piz Daint

October 17, 2017

Effective global climate simulation, sorely needed to anticipate and cope with global warming, has long been computationally challenging. Two of the major obstacles are the needed resolution and prolonged time to compute Read more…

By John Russell

HPE Extreme Performance Solutions

Transforming Genomic Analytics with HPC-Accelerated Insights

Advancements in the field of genomics are revolutionizing our understanding of human biology, rapidly accelerating the discovery and treatment of genetic diseases, and dramatically improving human health. Read more…

Student Cluster Competition Coverage New Home

October 16, 2017

Hello computer sports fans! This is the first of many (many!) articles covering the world-wide phenomenon of Student Cluster Competitions. Finally, the Student Cluster Competition coverage has come to its natural home: H Read more…

By Dan Olds

Data Vortex Users Contemplate the Future of Supercomputing

October 19, 2017

Last month (Sept. 11-12), HPC networking company Data Vortex held its inaugural users group at Pacific Northwest National Laboratory (PNNL) bringing together ab Read more…

By Tiffany Trader

AI Self-Training Goes Forward at Google DeepMind

October 19, 2017

DeepMind, Google’s AI research organization, announced today in a blog that AlphaGo Zero, the latest evolution of AlphaGo (the first computer program to defeat a Go world champion) trained itself within three days to play Go at a superhuman level (i.e., better than any human) – and to beat the old version of AlphaGo – without leveraging human expertise, data or training. Read more…

By Doug Black

Student Cluster Competition Coverage New Home

October 16, 2017

Hello computer sports fans! This is the first of many (many!) articles covering the world-wide phenomenon of Student Cluster Competitions. Finally, the Student Read more…

By Dan Olds

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Fujitsu Tapped to Build 37-Petaflops ABCI System for AIST

October 10, 2017

Fujitsu announced today it will build the long-planned AI Bridging Cloud Infrastructure (ABCI) which is set to become the fastest supercomputer system in Japan Read more…

By John Russell

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Intel Debuts Programmable Acceleration Card

October 5, 2017

With a view toward supporting complex, data-intensive applications, such as AI inference, video streaming analytics, database acceleration and genomics, Intel i Read more…

By Doug Black

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Leading Solution Providers

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

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