Adaptive Computing Revs Up Moab

By Tiffany Trader

March 20, 2012

Adaptive Computing recently released a new version of Moab 7.0, both the HPC Suite (basic and enterprise editions) and also the Cloud Suite. While the workload management vendor has made important enhancements to its portfolio, what’s even more interesting is how these offerings fit into an increasingly cloud-based IT environment.

adaptation of photo from Flickr user - maveric2003I sat down with Robert Clyde, who took over as CEO of Adaptive Computing in July 2011, and Chad Harrington, Adaptive’s vice president of marketing, to discuss the latest product launch and suss out their cloud strategy. The company, which was founded in 2001 as Cluster Resources, appears to be headed in the right direction. Currently in “a high-growth mode,” they’ve made a big hiring push and have raised over $20 million dollars. The duo explains the impetus for all the forward-movement: so they have everything they need to drive Moab into the future.

Moab refers to Adaptive Computing’s propriety workload management technology, the engine inside all of its offerings. The company has a long history of managing HPC workloads with some impressive stats to its credit. Moab is used by 40% of the top 10 supercomputing systems, nearly 40% of the top 25 and 33% of the top 100 systems based on TOP500 rankings.

Adaptive Computing rearchitected the offerings with a major focus on ease-of-use and the extreme scalability requirements of the coming decade. The CEO note an eye toward not only double-digit petascale systems, but also exascale systems. The software has to keep up, he says.

Adaptive is seeing a lot of its growth in the enterprise HPC market, specifically in the number of manufacturing and oil and gas customers. As the academic market is relatively fixed, going after the bigger enterprise HPC space makes sense from a business perspective, but requires a renewed focus on ease-of-use. Clyde notes that academic users can hire grad students to do the customization, but commercial players expect a higher degree of usability and simplicity. To meet this requirement, Adaptive has added:

§ Simplified job submission & management.
§ New Moab Web Services for easier integration.
§ Updated self-service portal and admin dashboard.
§ Greater usage budgeting and accounting flexibility.
§ Additional database support.

Now we’re talking (cloud)

cloud graphicClyde explains they’ve seen a significant uptick in acceptance of cloud by the HPC community. He points out that at the November 2011 SC event, it seemed like everyone wanted to talk about cloud, whereas previously it was practically a bad word. But this isn’t the cloud as it’s often conceived:

“We’re not talking about cloud like perhaps an enterprise software company is looking at; this a not a heavily-virtualized cloud. What we’re really talking about is cloud bursting, in part, but perhaps even more important is the idea of getting those resources so they’re more fungible, and rapidly re-provisioning and changing them as the needs change within that space from bare metal. This is different from the kind of cloud you’d hear, say, Gartner talking about but equally important.”

TORQUE versus Moab

TORQUE is an open source resource manager that is maintained by Adaptive. It runs on all the nodes; starts the jobs and watches them. Moab, as the scheduler or workload manager, only runs on the head node. While customers need both the resource manager and workload manager, Moab is not tied to TORQUE; customers are free to choose other resource managers, including competing offerings. However, Adaptive is confident that TORQUE is the most scalable resource manager available, and Harrington cites their many top-level system implementations as proof of this claim.

The recently-released TORQUE 4.0 was all about scalability. The company took TORQUE 4.0 and integrated it with Moab 7.0 to obtain a new level of scalability and a new architectural framework that lays the groundwork for future growth. The architectural change takes advantage of distributed communications. The previous version of TORQUE would have to talk to every node to report job status, or get rollup information to start jobs, now there is a communication hierarchy that fans out in a tree exponentially.

Harrington notes that although the sequential process works very well up to thousands of nodes, for tens of thousands of nodes and beyond, the distributed approach is necessary. According to the company, the change was made in response to customer feedback.

Enabling NCSA’s community cloud

Last month, Adaptive announced that it had signed on to help power NCSA’s Private Sector Program, which leases time on their computers in a cloud-like fashion to some of the biggest names in the industry, household names like Boeing, BP, Caterpillar, John Deere, Nokia Siemens Networks, Procter & Gamble and Rolls-Royce.

The NCSA program allows industry partners to tap into the center’s advanced computing resources and expertise to help them innovate and compete. NCSA makes two of their systems available to the PSP industry partners: the iForge system, a 153-teraflop system, which was designed specifically for industrial use, as well as Ember, an Altix UV shared memory system with 1,536 cores and 8 TB RAM.

According to the formal announcement, the “program brings the promise of HPC to a broad segment of the market and enables businesses to tap into all the benefits HPC has to offer as well as having access to a wealth of knowledge within the HPC community.”

But what the announcement doesn’t tell you is that NCSA’s PSP actually delivers its supercomputing resources as a service to its customers, which makes it a community cloud.

As part of its involvement with NCSA’s PSP, Adaptive provides cloud-like capabilities to the PSP customers who are running Moab on their on-site computing resources. The cloud bursting solution works like this. If the company is running Moab on their site and they subscribe to the PSP, Moab will schedule the jobs where it makes the most sense. Since it costs money to use the NCSA machines, Moab will first attempt to schedule jobs locally, but if the job is too big or the system is already being utilized, Moab will schedule part of the job or all of the job to run remotely in NCSA’s community cloud.

Harrington defines the “community cloud” in this case as a set of shared compute resources that are elastic and available over the Internet, but restricted to a closed group of users, unlike a public cloud, which is open to anyone.

Says Harrington: “With Moab running on both sides, in NCSA’s cloud as well as in, say, Boeing or Caterpillar’s side, we can make intelligent scheduling decisions between them, and this allows them to really achieve HPC in the cloud in the sense that they can make smart decisions about whether it should run locally or whether it should run remotely in NCSA’s environment. And it also simplifies workload management when Moab is running on both sides.”

While PSP customers are not mandated to use Moab on their local machines, in that case they will only be able to run jobs locally or run jobs in the cloud, they won’t be able to take advantage of the Moab’s cloud bursting abilities. They can run jobs on runtime, but then they are basically stuck. But if someone like Boeing or Caterpillar were to run Moab on both sides, then Moab can dynamically manage their workloads.

In addition to being excited about this partnership, Harrington and Clyde feel strongly that this type of cloud model makes sense for the HPC market. It’s not a virtualized cloud, but still meets many of the hallmarks of cloud, such as elasticity of resources and scalability. The reason they don’t virtualize in this instance is that it wouldn’t provide any benefit.

Says Harrington: “In the enterprise cloud space, the resources required are much less than the size of the machine so you can actually pack onto a single node and it makes sense but with most HPC jobs, the resources required are bigger than a single machine, so you don’t want to pay that tax for additional overhead.”

What about HPC cloud?

The Adaptive CEO offers up an important distinction between the two offerings. When it comes to running HPC workloads, even in the cloud, their Moab HPC suite will be the go-to product. With an emphasis on flexibility and automation, Moab’s private HPC cloud solution intelligently reprovisions machines depending on the needs of the workload. The Cloud suite, it should be noted, is mainly for running enterprise IT applications in a private or hybrid cloud.

The main differentiator for the enterprise IT side is the amount of virtualization they are likely to have and the concept of many workloads running all the time, i.e., never running to completion. For HPC apps running in the cloud, customers will most likely want to use the enterprise edition (as opposed to the basic edition) for the additional support capabilities that it provides. Since the resources in this case are fungible, that is, always moving around and being used for different things, flexible accounting tools, such as Moab Accounting Manager, are a necessity. “Otherwise there’s almost no hope of keeping track of budgeting,” notes Clyde.

What’s the difference?

Adaptive Computing’s two product lines – Moab HPC Suite and Moab Cloud Suite – both have the same Moab engine, but separate supporting code. As was pointed out previously, Moab Cloud suite is geared toward enterprise IT, and most often used in a private or hybrid cloud setup. The accounting modules and dashboards are essentially the same with some tweaks, but the service catalogue is unique to the cloud product. It allows the IT department to create a catalogue of services, for example a “website service,” which lets the user setup a website by simply selecting the service and setting a few parameters.

The main area where the cloud product diverges from the HPC offering is in the workload manager. The HPC solution relies on the TORQUE manager, which is all about batch job management. In cloud, it’s less about batch jobs and more about the services, which run on an ongoing basis, so the Moab Cloud suite relies on an open source provisioning manager, called EXCAT, which was started by IBM. EXCAT integrates with VMWare, KVM, and with other virtualization managers, and it can also provision bare metal hardware. Despite having different workload managers, Harrington reiterates that the core technical component, Moab, remains the same.

These recent advancements mean Moab Cloud is a complete, end-to-end offering.

“In the past, we had our intelligence engine, but we didn’t have these other pieces,” says Harringon. “We didn’t have provisioning, we didn’t have our own services catalogue, we didn’t have our own built-in database, we didn’t have our own built-in monitoring. Now we have all that. So if you’re an enterprise cloud user, and want to stand up a cloud, we have the full stack.”

HPC roots extend to cloud

Clyde cites the company’s deep HPC background as the reason why the company has been successful meeting the needs of the enterprise community. He makes the point that many of their enterprise cloud customers are surprised at some of the things Moab is capable of, for example, the concept of reservations, scheduling reservations, and scheduling maintenance windows, and being able to suspend and resume workloads.

“As we talk to them, we’ve been able to say, ‘We solved these problems long ago in the HPC space.'” Clyde suggests that other cloud providers think cloud means you just virtualize everything and “nothing could be further from the truth at large enterprise cloud,” says Clyde. While virtualization is important, bare metal is still critical and they’re going to have workloads that do require scheduling and suspend/resume, the CEO tells me.

“You have to have all those ingredients, or you really don’t solve those complex problems,” notes Clyde with some passion. “That’s what I love about the background that HPC has given us. Much like on the large end of HPC that we do a great job at, we’re seeing the same thing in the enterprise cloud space – we’re well-placed to handle the large, complex environments.”

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!

What’s New in HPC Research: September (Part 1)

September 18, 2018

In this new bimonthly feature, HPCwire will highlight newly published research in the high-performance computing community and related domains. From exascale to quantum computing, the details are here. Check back every Read more…

By Oliver Peckham

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and development. Among other things it would establish a National Quantu Read more…

By John Russell

Nvidia Accelerates AI Inference in the Datacenter with T4 GPU

September 14, 2018

Nvidia is upping its game for AI inference in the datacenter with a new platform consisting of an inference accelerator chip--the new Turing-based Tesla T4 GPU--and a refresh of its inference server software packaged as Read more…

By George Leopold

HPE Extreme Performance Solutions

Introducing the First Integrated System Management Software for HPC Clusters from HPE

How do you manage your complex, growing cluster environments? Answer that big challenge with the new HPC cluster management solution: HPE Performance Cluster Manager. Read more…

IBM Accelerated Insights

A Crystal Ball for HPC

People are notoriously bad at predicting the future.  This very much includes experts. In the Forbes article “Why Most Predictions Are So Bad” Philip Tetlock discusses the largest and best-known test of the accuracy of expert predictions which show that any experts would do better if they make random guesses. Read more…

NSF Highlights Expanded Efforts for Broadening Participation in Computing

September 13, 2018

Today, the Directorate of Computer and Information Science and Engineering (CISE) of the NSF released a letter highlighting the expansion of its broadening participation in computing efforts. The letter was penned by Jam Read more…

By Staff

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

Nvidia Accelerates AI Inference in the Datacenter with T4 GPU

September 14, 2018

Nvidia is upping its game for AI inference in the datacenter with a new platform consisting of an inference accelerator chip--the new Turing-based Tesla T4 GPU- Read more…

By George Leopold

DeepSense Combines HPC and AI to Bolster Canada’s Ocean Economy

September 13, 2018

We often hear scientists say that we know less than 10 percent of the life of the oceans. This week, IBM and a group of Canadian industry and government partner Read more…

By Tiffany Trader

Rigetti (and Others) Pursuit of Quantum Advantage

September 11, 2018

Remember ‘quantum supremacy’, the much-touted but little-loved idea that the age of quantum computing would be signaled when quantum computers could tackle Read more…

By John Russell

How FPGAs Accelerate Financial Services Workloads

September 11, 2018

While FSI companies are unlikely, for competitive reasons, to disclose their FPGA strategies, James Reinders offers insights into the case for FPGAs as accelerators for FSI by discussing performance, power, size, latency, jitter and inline processing. Read more…

By James Reinders

Update from Gregory Kurtzer on Singularity’s Push into FS and the Enterprise

September 11, 2018

Container technology is hardly new but it has undergone rapid evolution in the HPC space in recent years to accommodate traditional science workloads and HPC systems requirements. While Docker containers continue to dominate in the enterprise, other variants are becoming important and one alternative with distinctly HPC roots – Singularity – is making an enterprise push targeting advanced scale workload inclusive of HPC. Read more…

By John Russell

At HPC on Wall Street: AI-as-a-Service Accelerates AI Journeys

September 10, 2018

AIaaS – artificial intelligence-as-a-service – is the technology discipline that eases enterprise entry into the mysteries of the AI journey while lowering Read more…

By Doug Black

No Go for GloFo at 7nm; and the Fujitsu A64FX post-K CPU

September 5, 2018

It’s been a news worthy couple of weeks in the semiconductor and HPC industry. There were several HPC relevant disclosures at Hot Chips 2018 to whet appetites Read more…

By Dairsie Latimer

TACC Wins Next NSF-funded Major Supercomputer

July 30, 2018

The Texas Advanced Computing Center (TACC) has won the next NSF-funded big supercomputer beating out rivals including the National Center for Supercomputing Ap Read more…

By John Russell

IBM at Hot Chips: What’s Next for Power

August 23, 2018

With processor, memory and networking technologies all racing to fill in for an ailing Moore’s law, the era of the heterogeneous datacenter is well underway, Read more…

By Tiffany Trader

Requiem for a Phi: Knights Landing Discontinued

July 25, 2018

On Monday, Intel made public its end of life strategy for the Knights Landing "KNL" Phi product set. The announcement makes official what has already been wide Read more…

By Tiffany Trader

CERN Project Sees Orders-of-Magnitude Speedup with AI Approach

August 14, 2018

An award-winning effort at CERN has demonstrated potential to significantly change how the physics based modeling and simulation communities view machine learni Read more…

By Rob Farber

ORNL Summit Supercomputer Is Officially Here

June 8, 2018

Oak Ridge National Laboratory (ORNL) together with IBM and Nvidia celebrated the official unveiling of the Department of Energy (DOE) Summit supercomputer toda Read more…

By Tiffany Trader

New Deep Learning Algorithm Solves Rubik’s Cube

July 25, 2018

Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and archite Read more…

By John Russell

AMD’s EPYC Road to Redemption in Six Slides

June 21, 2018

A year ago AMD returned to the server market with its EPYC processor line. The earth didn’t tremble but folks took notice. People remember the Opteron fondly Read more…

By John Russell

MLPerf – Will New Machine Learning Benchmark Help Propel AI Forward?

May 2, 2018

Let the AI benchmarking wars begin. Today, a diverse group from academia and industry – Google, Baidu, Intel, AMD, Harvard, and Stanford among them – releas Read more…

By John Russell

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17

Altair

AMD @ SC17

AMD

ASRock Rack @ SC17

ASRock Rack

CEJN @ SC17

CEJN

DDN Storage @ SC17

DDN Storage

Huawei @ SC17

Huawei

IBM @ SC17

IBM

IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17

Intel

Lenovo @ SC17

Lenovo

Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17

Microsoft

Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17

Supericro

Tyan @ SC17

Tyan

Univa @ SC17

Univa

Pattern Computer – Startup Claims Breakthrough in ‘Pattern Discovery’ Technology

May 23, 2018

If it weren’t for the heavy-hitter technology team behind start-up Pattern Computer, which emerged from stealth today in a live-streamed event from San Franci Read more…

By John Russell

Sandia to Take Delivery of World’s Largest Arm System

June 18, 2018

While the enterprise remains circumspect on prospects for Arm servers in the datacenter, the leadership HPC community is taking a bolder, brighter view of the x86 server CPU alternative. Amongst current and planned Arm HPC installations – i.e., the innovative Mont-Blanc project, led by Bull/Atos, the 'Isambard’ Cray XC50 going into the University of Bristol, and commitments from both Japan and France among others -- HPE is announcing that it will be supply the United States National Nuclear Security Administration (NNSA) with a 2.3 petaflops peak Arm-based system, named Astra. Read more…

By Tiffany Trader

D-Wave Breaks New Ground in Quantum Simulation

July 16, 2018

Last Friday D-Wave scientists and colleagues published work in Science which they say represents the first fulfillment of Richard Feynman’s 1982 notion that Read more…

By John Russell

Intel Pledges First Commercial Nervana Product ‘Spring Crest’ in 2019

May 24, 2018

At its AI developer conference in San Francisco yesterday, Intel embraced a holistic approach to AI and showed off a broad AI portfolio that includes Xeon processors, Movidius technologies, FPGAs and Intel’s Nervana Neural Network Processors (NNPs), based on the technology it acquired in 2016. Read more…

By Tiffany Trader

Intel Announces Cooper Lake, Advances AI Strategy

August 9, 2018

Intel's chief datacenter exec Navin Shenoy kicked off the company's Data-Centric Innovation Summit Wednesday, the day-long program devoted to Intel's datacenter Read more…

By Tiffany Trader

TACC’s ‘Frontera’ Supercomputer Expands Horizon for Extreme-Scale Science

August 29, 2018

The National Science Foundation and the Texas Advanced Computing Center announced today that a new system, called Frontera, will overtake Stampede 2 as the fast Read more…

By Tiffany Trader

GPUs Power Five of World’s Top Seven Supercomputers

June 25, 2018

The top 10 echelon of the newly minted Top500 list boasts three powerful new systems with one common engine: the Nvidia Volta V100 general-purpose graphics proc Read more…

By Tiffany Trader

The Machine Learning Hype Cycle and HPC

June 14, 2018

Like many other HPC professionals I’m following the hype cycle around machine learning/deep learning with interest. I subscribe to the view that we’re probably approaching the ‘peak of inflated expectation’ but not quite yet starting the descent into the ‘trough of disillusionment. This still raises the probability that... Read more…

By Dairsie Latimer

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This