Kubernetes and HPC Applications in Hybrid Cloud Environments – Part II

By Daniel Gruber,Burak Yenier and Wolfgang Gentzsch, UberCloud

March 19, 2020

With the rise of cloud services, CIOs are recognizing that applications, middleware, and infrastructure running in various compute environments need a common management and operating model. Maintaining different application and middleware stacks on-premises and in cloud environments, by possibly using different specialized infrastructure and application management solutions for each cloud provider, adds lots of friction in dynamically allocating, using, and managing those resources.

Lack of a common management and operating model in hybrid cloud environments can cause:

  • Inhomogeneous, fragmented environments create additional complexity for managers, operators, and security.
  • Speed of innovation slows down due to hybrid environments without common management.
  • Cloud resources are hard to change or shutdown when dependent on a cloud provider’s specific services.
  • Workloads can’t be easily migrated back to on-premises environments when bound to specific cloud environment setups, and vice versa.

Kubernetes has become the de-facto standard container orchestrator as pointed out in a previous article. All major companies provide and build solutions on top of a standardized API which is available everywhere. CIOs are now looking into the applicability of Kubernetes for HPC in hybrid-cloud as it offers a common management and operating model for every environment.

Kubernetes: A Common Management and Operating Model for Hybrid Cloud

Kubernetes facilitates the use and administration of countless containers running on fleets of servers. It is the new standard platform for hybrid environments supported by many IT vendors and cloud providers. CIOs can now allocate a fully configured and supported container orchestrator as base for all of their application workloads.

Kubernetes, unlike proprietary infrastructure solutions, provides portability, ease of administration, high availability, integrability, and monitoring capabilities. When managing resources on Kubernetes CIOs are no longer bound to a specific infrastructure. They can offer their users the same set of functionalities, be it on-premises or in any cloud, using the same application stack. Users are not even aware that their applications are running on Kubernetes, nor on which infrastructure they are running: in their own data centers or at a specific cloud provider, like Google, Microsoft, or Amazon.

Reducing complexity in hybrid cloud environments by using a standardized software stack like Kubernetes comes with many advantages: improvements made for one platform can be made automatically available on other platforms; deployment and operational aspects can be simplified; and security audits are easier and rigorously to execute.

Kubernetes and HPC

Kubernetes is the de facto platform for AI and ML already. However, when it comes to traditional HPC, some challenges remain. There is still a set of features built into HPC workload managers not yet available in Kubernetes. We discussed the major differences already previously in our HPCwire Part I article. Major gaps of Kubernetes for HPC currently are: native support for distributed memory jobs, namely MPI applications, and a missing job queueing system compatible with existing HPC applications.

Kubernetes has built-in high availability on many layers. However, for HPC jobs, it is not enough to restart a single container that failed because the whole distributed job itself might have failed already. In this case, automatic rescheduling of the entire distributed memory job is required. This is something Kubernetes doesn’t handle.

Beside these challenges, Kubernetes comes with many benefits for HPC: for example, the environment for the engineer and for the containerized HPC application is always the same, be it on-premises or running in a cloud-based environment; and the capability to quickly change from one infrastructure to another allows the HPC team to align with their company’s cloud roadmap. The freedom to move workloads between infrastructures based on a common API – the Kubernetes API – is what becomes valuable.

Containerized HPC Applications on Kubernetes

Over the past five years, dozens of HPC applications have been containerized, be it commercial, like ANSYS, COMSOL, STAR-CCM+, or open source packages like OpenFOAM and GROMACS, along with HPC cluster schedulers like Univa Grid Engine and Slurm. Thanks to container technology, a constant stream of updates and improvements is provided which can be promptly and seamlessly updated by customers. Additionally, the container images allow users to go back at any time to a previous application version so that they always can reproduce their previous results.

Example HPC Application Cluster Architecture running on Managed Kubernetes.

In the meantime, many container environments have been implemented by using infrastructure and configuration management tools like Terraform and Puppet or by building cloud specific HPC integrations into existing portals. But with the advent of Kubernetes, container environments became easier to maintain and are much more dynamic. Rolling out a cluster, rescaling the worker nodes, using a constant set of preemptible instances, and high availability are driven by controllers which continuously drive the cluster to the desired state. Thus, major HPC gaps of Kubernetes have been closed. This way, today, distributed memory/MPI jobs can be supported in any Kubernetes environment, which provides a built-in HPC workload manager integration running inside HPC containers. That allows traditional HPC applications to run without any changes. Also, GPU and non-GPU enabled applications based on Ansys and COMSOL have been launched successfully, through a high-performance, GPU enabled desktop running inside a pod. Once logged in to the desktop the engineer can start submitting batch jobs or single MPI applications which are distributed across a set of pods allocated on multiple nodes.

Conclusions

Kubernetes not only supports microservice based enterprise applications, but also self-service engineering HPC applications. In summary, as this research has shown, the key advantages of using Kubernetes as a foundation for running containerized engineering applications are:

  • Unified application stack available on virtually any infrastructure
  • True hybrid cloud usage scenarios for engineering workload. For the engineers it is transparent where the application runs, be it on-premises or in the cloud
  • which leads to providing the best performance for running engineering applications by allocating always the newest and fastest machines available in the cloud
  • Building and resizing a self-contained HPC application and compute cluster as self-service for the engineer which is only limited by cloud quotas and budget per time period
  • Robust management stack, supported by many Cloud providers
  • Optimizing costs by only paying for what is used. No idle resources which need to be allocated before they are going to be used.
  • High security through self-contained dedicated compute clusters
  • Minimal operational overhead by self-provisioning and disposable components for which updates are simple destroy and re-create commands
  • Kubernetes based workload is easier to integrate in widely adopted continuous integration and deployment solutions (like Tekton, Concourse, or future versions of Jenkins)

In this research, container-based HPC application environments have been implemented on top of Kubernetes (e.g. on Google GCP and Amazon AWS) and also used as self-service test environments which can be deployed from scratch by HPC application specialists, not operators. It has also been used in CI/CD pipelines to automatically build test environments which run tests against existing container solutions and shut down the infrastructure afterwards. In customer environments, the IT group benefits from an easier to maintain system using a supported, managed Kubernetes which can ramp up, resized and deleted computing resources within minutes.

About the Authors

Daniel Gruber, Burak Yenier, and Wolfgang Gentzsch are with UberCloud, a company that started in 2013 with developing HPC container technology and containerized engineering applications, to facilitate access and use of engineering HPC workload in a shared on-premise or on-demand cloud environment. In this article and the part-one article published on HPCwire last September, they describe their experiences during the last 12 months using UberCloud HPC containers on Kubernetes.

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!

University of Chicago Researchers Generate First Computational Model of Entire SARS-CoV-2 Virus

January 15, 2021

Over the course of the last year, many detailed computational models of SARS-CoV-2 have been produced with the help of supercomputers, but those models have largely focused on critical elements of the virus, such as its Read more…

By Oliver Peckham

Pat Gelsinger Returns to Intel as CEO

January 14, 2021

The Intel board of directors has appointed a new CEO. Intel alum Pat Gelsinger is leaving his post as CEO of VMware to rejoin the company that he parted ways with 11 years ago. Gelsinger will succeed Bob Swan, who will remain CEO until Feb. 15. Gelsinger previously spent 30 years... Read more…

By Tiffany Trader

Roar Supercomputer to Support Naval Aircraft Research

January 14, 2021

One might not think “aircraft” when picturing the U.S. Navy, but the military branch actually has thousands of aircraft currently in service – and now, supercomputing will help future naval aircraft operate faster, Read more…

By Staff report

DOE and NOAA Extend Computing Partnership, Plan for New Supercomputer

January 14, 2021

The National Climate-Computing Research Center (NCRC), hosted by Oak Ridge National Laboratory (ORNL), has been supporting the climate research of the National Oceanic and Atmospheric Administration (NOAA) for the last 1 Read more…

By Oliver Peckham

Using Micro-Combs, Researchers Demonstrate World’s Fastest Optical Neuromorphic Processor for AI

January 13, 2021

Neuromorphic computing, which uses chips that mimic the behavior of the human brain using virtual “neurons,” is growing in popularity thanks to high-profile efforts from Intel and others. Now, a team of researchers l Read more…

By Oliver Peckham

AWS Solution Channel

Now Available – Amazon EC2 C6gn Instances with 100 Gbps Networking

Amazon EC2 C6gn instances powered by AWS Graviton2 processors are now available!

Compared to C6g instances, this new instance type provides 4x higher network bandwidth, 4x higher packet processing performance, and 2x higher EBS bandwidth. Read more…

Intel® HPC + AI Pavilion

Intel Keynote Address

Intel is the foundation of HPC – from the workstation to the cloud to the backbone of the Top500. At SC20, Intel’s Trish Damkroger, VP and GM of high performance computing, addresses the audience to show how Intel and its partners are building the future of HPC today, through hardware and software technologies that accelerate the broad deployment of advanced HPC systems. Read more…

Honing In on AI, US Launches National Artificial Intelligence Initiative Office

January 13, 2021

To drive American leadership in the field of AI into the future, the National Artificial Intelligence Initiative Office has been launched by the White House Office of Science and Technology Policy (OSTP). The new agen Read more…

By Todd R. Weiss

Pat Gelsinger Returns to Intel as CEO

January 14, 2021

The Intel board of directors has appointed a new CEO. Intel alum Pat Gelsinger is leaving his post as CEO of VMware to rejoin the company that he parted ways with 11 years ago. Gelsinger will succeed Bob Swan, who will remain CEO until Feb. 15. Gelsinger previously spent 30 years... Read more…

By Tiffany Trader

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

By John Russell

Intel ‘Ice Lake’ Server Chips in Production, Set for Volume Ramp This Quarter

January 12, 2021

Intel Corp. used this week’s virtual CES 2021 event to reassert its dominance of the datacenter with the formal roll out of its next-generation server chip, the 10nm Xeon Scalable processor that targets AI and HPC workloads. The third-generation “Ice Lake” family... Read more…

By George Leopold

Researchers Say It Won’t Be Possible to Control Superintelligent AI

January 11, 2021

Worries about out-of-control AI aren’t new. Many prominent figures have suggested caution when unleashing AI. One quote that keeps cropping up is (roughly) th Read more…

By John Russell

AMD Files Patent on New GPU Chiplet Approach

January 5, 2021

Advanced Micro Devices is accelerating the GPU chiplet race with the release of a U.S. patent application for a device that incorporates high-bandwidth intercon Read more…

By George Leopold

Programming the Soon-to-Be World’s Fastest Supercomputer, Frontier

January 5, 2021

What’s it like designing an app for the world’s fastest supercomputer, set to come online in the United States in 2021? The University of Delaware’s Sunita Chandrasekaran is leading an elite international team in just that task. Chandrasekaran, assistant professor of computer and information sciences, recently was named... Read more…

By Tracey Bryant

Intel Touts Optane Performance, Teases Next-gen “Crow Pass”

January 5, 2021

Competition to leverage new memory and storage hardware with new or improved software to create better storage/memory schemes has steadily gathered steam during Read more…

By John Russell

Farewell 2020: Bleak, Yes. But a Lot of Good Happened Too

December 30, 2020

Here on the cusp of the new year, the catchphrase ‘2020 hindsight’ has a distinctly different feel. Good riddance, yes. But also proof of science’s power Read more…

By John Russell

Esperanto Unveils ML Chip with Nearly 1,100 RISC-V Cores

December 8, 2020

At the RISC-V Summit today, Art Swift, CEO of Esperanto Technologies, announced a new, RISC-V based chip aimed at machine learning and containing nearly 1,100 low-power cores based on the open-source RISC-V architecture. Esperanto Technologies, headquartered in... Read more…

By Oliver Peckham

Azure Scaled to Record 86,400 Cores for Molecular Dynamics

November 20, 2020

A new record for HPC scaling on the public cloud has been achieved on Microsoft Azure. Led by Dr. Jer-Ming Chia, the cloud provider partnered with the Beckman I Read more…

By Oliver Peckham

NICS Unleashes ‘Kraken’ Supercomputer

April 4, 2008

A Cray XT4 supercomputer, dubbed Kraken, is scheduled to come online in mid-summer at the National Institute for Computational Sciences (NICS). The soon-to-be petascale system, and the resulting NICS organization, are the result of an NSF Track II award of $65 million to the University of Tennessee and its partners to provide next-generation supercomputing for the nation's science community. Read more…

Is the Nvidia A100 GPU Performance Worth a Hardware Upgrade?

October 16, 2020

Over the last decade, accelerators have seen an increasing rate of adoption in high-performance computing (HPC) platforms, and in the June 2020 Top500 list, eig Read more…

By Hartwig Anzt, Ahmad Abdelfattah and Jack Dongarra

Aurora’s Troubles Move Frontier into Pole Exascale Position

October 1, 2020

Intel’s 7nm node delay has raised questions about the status of the Aurora supercomputer that was scheduled to be stood up at Argonne National Laboratory next year. Aurora was in the running to be the United States’ first exascale supercomputer although it was on a contemporaneous timeline with... Read more…

By Tiffany Trader

Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?

January 13, 2021

The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…

By John Russell

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

By Doug Black

Programming the Soon-to-Be World’s Fastest Supercomputer, Frontier

January 5, 2021

What’s it like designing an app for the world’s fastest supercomputer, set to come online in the United States in 2021? The University of Delaware’s Sunita Chandrasekaran is leading an elite international team in just that task. Chandrasekaran, assistant professor of computer and information sciences, recently was named... Read more…

By Tracey Bryant

Leading Solution Providers

Contributors

Top500: Fugaku Keeps Crown, Nvidia’s Selene Climbs to #5

November 16, 2020

With the publication of the 56th Top500 list today from SC20's virtual proceedings, Japan's Fugaku supercomputer – now fully deployed – notches another win, Read more…

By Tiffany Trader

Texas A&M Announces Flagship ‘Grace’ Supercomputer

November 9, 2020

Texas A&M University has announced its next flagship system: Grace. The new supercomputer, named for legendary programming pioneer Grace Hopper, is replacing the Ada system (itself named for mathematician Ada Lovelace) as the primary workhorse for Texas A&M’s High Performance Research Computing (HPRC). Read more…

By Oliver Peckham

At Oak Ridge, ‘End of Life’ Sometimes Isn’t

October 31, 2020

Sometimes, the old dog actually does go live on a farm. HPC systems are often cursed with short lifespans, as they are continually supplanted by the latest and Read more…

By Oliver Peckham

Nvidia and EuroHPC Team for Four Supercomputers, Including Massive ‘Leonardo’ System

October 15, 2020

The EuroHPC Joint Undertaking (JU) serves as Europe’s concerted supercomputing play, currently comprising 32 member states and billions of euros in funding. I Read more…

By Oliver Peckham

Gordon Bell Special Prize Goes to Massive SARS-CoV-2 Simulations

November 19, 2020

2020 has proven a harrowing year – but it has produced remarkable heroes. To that end, this year, the Association for Computing Machinery (ACM) introduced the Read more…

By Oliver Peckham

Nvidia-Arm Deal a Boon for RISC-V?

October 26, 2020

The $40 billion blockbuster acquisition deal that will bring chipmaker Arm into the Nvidia corporate family could provide a boost for the competing RISC-V architecture. As regulators in the U.S., China and the European Union begin scrutinizing the impact of the blockbuster deal on semiconductor industry competition and innovation, the deal has at the very least... Read more…

By George Leopold

Intel Xe-HP GPU Deployed for Aurora Exascale Development

November 17, 2020

At SC20, Intel announced that it is making its Xe-HP high performance discrete GPUs available to early access developers. Notably, the new chips have been deplo Read more…

By Tiffany Trader

HPE, AMD and EuroHPC Partner for Pre-Exascale LUMI Supercomputer

October 21, 2020

Not even a week after Nvidia announced that it would be providing hardware for the first four of the eight planned EuroHPC systems, HPE and AMD are announcing a Read more…

By Oliver Peckham

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