Penguin Adds HPC On-Demand Service

By Michael Feldman

August 12, 2009

Linux cluster maker Penguin Computing hopped on the HPC-in-a-cloud bandwagon this week with the announcement of its HPC on-demand service. Called Penguin On Demand (POD), the service consists of an HPC compute infrastructure whose capacity can be rented on a pay-as-you-go basis or through a monthly subscription.

As it exists today, the POD infrastructure consists of 1200 Xeon cores spread over a number of clusters at a single facility. Penguin offers a choice of GigE or DDR InfiniBand interconnects and the option to tap into NVIDIA Tesla GPU computing hardware. By cloud standards the number of cores is tiny. But since Penguin also sells systems for a living, it would be relatively easy for them to scale up the infrastructure rather quickly if customer demand warranted additional capacity.

According to Penguin, the on-demand facility has sufficient bandwidth to allow the transfer of reasonably large data files directly to POD over the Internet. The company also offer a “disk caddy” service that allows the transfer of 1 TB+ files overnight. The disks are provided as part of the service and are actually owned by the customer and are returned to them once the data has been transferred to POD storage.

The software stack consists of CentOS, a community-supported OS based on Red Hat Enterprise Linux, as well as the company’s Scyld ClusterWare cluster management software. “Scyld enables us to rapidly provision a set of compute nodes for our customers based on their demand — so we can scale up and scale down efficiently,” says Penguin Computing CEO Charles Wuischpard.

Penguin is aiming the POD at a variety of HPC verticals. According to Wuischpard, the initial interest came from the life sciences sector, but they have recently seen interest from a number of Fortune 500 manufacturing companies and some smaller hedge funds firms.

Users with in-house Penguin systems can get access to the POD service via the Scyld software suite. Since Scyld ClusterWare includes TORQUE and offers a scheduling package called TaskMaster, policies in the scheduling software can be set such that when a particular threshold is reached, jobs submitted on the local resource are automatically redirected to the POD system.

Unlike generic cloud computing set-ups like Amazon’s EC2, user applications run directly on the compute nodes without virtualization in order to maximize performance. “POD is geared strictly towards applications that thrive in an HPC environment and would otherwise be starved for performance on a virtualized cloud computing environment,” explains Wuischpard.

In that sense, it’s not really a cloud in the classic sense (if there is such a thing), but rather a dedicated infrastructure built for on-demand HPC. In fact, the model used by Penguin is the same as most HPC on-demand offerings, such as IBM’s Computing On Demand service and R Systems’ dedicated hosting service. Thus far, a virtualized purpose-built HPC cloud with elastic capacity has yet to appear.

At the hardware level, the biggest criticism of general-purpose clouds is that they lack low latency interconnects so important to tightly-coupled MPI applications. As pointed at recently by Ian Foster, for short running HPC applications this may not be much of an issue. But for codes expected to execute for hours, days, or even longer, fast server-to-server communication is all but mandatory. Since at least some of the POD hardware includes InfiniBand-equipped servers, the service offers this natural advantage.

Setting up a POD account requires some initial hand-holding with Penguin technical staff. They will help set up the compute environment, explain the account management features, and answer any questions. After that, the POD service can be accessed via SSH to run user applications directly. If a customer requires more assistance, Penguin techies are available (via their Customer Portal) to help with issues that might come up or to help users squeeze more performance from user codes.

According to Penguin, their on-demand service is priced to provide a significant improvement in price-performance for HPC applications when compared to running on traditional cloud computing offerings. (The implication is that you will pay more per CPU-hour than for, say, EC2, but better performance will more than offset the price premium.) “Users pay only for the core hours that they use,” says Wuischpard. “Monthly contracts are available, which provide for a reduction in the average cost per core hour. And yes, we do have the concept of ‘roll-over’ hours!”

At this point, Penguin is not offering SLAs or QoS guarantees in the general offering. But, according to Wuischpard, these could be implemented if a customer has such a requirement. He says they do guarantee that if a job fails because of a POD hardware failure, then it can be rerun at no cost.

From a business point of view, the OEM-as-cloud-provider will be an interesting model to follow. If margins continue to shrink on commodity-based clusters, selling compute on-demand services may offer a natural way to tap into new revenue streams. As pointed out by many cloud gazers, the largest compute utility today is essentially being run out of the back of a bookstore. Renting CPU cycles from a system vendor would seem at least as reasonable.

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

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

Leading Solution Providers

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

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