Rethinking HPC Platforms for ‘Second Gen’ Applications

By John Russell

February 22, 2017

Just what constitutes HPC and how best to support it is a keen topic currently. A new paper posted last week on arXiv.org – Rethinking HPC Platforms: Challenges, Opportunities and Recommendations – by researchers from the University of Edinburgh and University of St. Andrews suggests the emergence of “second generation” HPC applications (and users) requires a new approach to supporting infrastructure that draws on container-like technology and services.

(Lead author Ole Weidner spoke with HPCwire after this article was first published and discussed further how it relates to other HPC container efforts. Please see the addendum at the end of the article for his additional comments.)

In the paper they describe a set of services, which they call ‘cHPC’ (container HPC), to accommodate these emerging HPC application requirements and indicate they plan to benchmark key applications as a next step. “Many of the emerging second generation HPC applications move beyond tightly-coupled, compute-centric methods and algorithms and embrace more heterogeneous, multi-component workflows, dynamic and ad-hoc computation and data-centric methodologies,” write authors Ole Weidner, Rosa Filgueira Vicente, Malcolm Atkinson, and Adam Barker.

“While diverging from the traditional HPC application profile, many of these applications still rely on the large number of tightly coupled cores, cutting-edge hardware and advanced interconnect topologies provided only by HPC clusters. Consequently, HPC platform providers often find themselves faced with requirements and requests that are so diverse and dynamic that they become increasingly difficult to fulfill efficiently within the current operational policies and platform models.”

It’s best to read the paper in full which examines in some detail the challenges and potential solutions. The authors single out three applications areas and report that as a group they have deep experience working with them:

  • Data Intensive Applications. Data-intensive applications require large volumes of data and devote a large fraction of their execution time to I/O and manipulation of data. Careful attention to data handling is necessary to achieve acceptable performance or completion. “They are frequently sensitive to local storage for intermediate results and reference data. It is also sensitive to the data-intensive frameworks and workflow systems available on the platform and to the proximity of data it uses.” Examples of large-scale, data-intensive HPC applications are seismic noise cross-correlation and misfit calculation as encountered, e.g. in the VERCE project.
  • Dynamic Applications. These fall into two broad categories: “applications for which we do not have full understanding of the runtime behavior and resource requirements prior to execution and (ii) applications which can change their runtime behavior and resource requirements during execution.” Two examples cited are: (a) applications that use ensemble Kalman-Filters for data assimilation in forecasting, (b) simulations that use adaptive mesh refinement (AMR) to refine the accuracy of their solutions.
  • Federated applications. “Based on the idea that federation fosters collaboration and allows scalability beyond a single platform, policies and funding schemes explicitly supporting the development of concepts and technology for HPC federations have been put into place. Larger federations of HPC platforms are XSEDE in the US, and the PRACE in the EU. Both platforms provide access to several TOP-500 ranked HPC clusters and an array of smaller and experimental platforms.”

“To explore the implementation options for our new platform model, we have developed cHPC, a set of operating-system level services and APIs that can run alongside and integrate with existing job via Linux containers (LXC) to pro- vide isolated, user-deployed application environment containers, application introspection and resource throttling via the cgroups kernel extension. The LXC runtime and software-defined networking are provided by Docker and run as OS services on the compute nodes,” say the authors. (see figure 2 from the papers shown here)

The authors note prominently in their discussion that many traditional HPC applications are still best served by traditional HPC environments for which they have been carefully coupled.

“It would be false to claim that current production HPC platforms fail to meet the requirements of their application communities. It would be equally wrong to claim that the existing platform model is a pervasive problem that generally stalls the innovation and productivity of HPC applications…[There are] significant classes of applications, often from the monolithic, tightly-coupled parallel realm, [that] have few concerns regarding the issues out-lined in this paper…They are the original tenants and drivers of HPC and have an effective social and technical symbiosis with their platform environments.

“However, it is equally important to understand that other classes of applications (that we call second generation applications) and their respective user communities share a less rosy perspective. These second generation applications are typically non-monolithic, dynamic in terms of their runtime behavior and resource requirements, or based on higher-level tools and frameworks that manage compute, data and communication. Some of them actively explore new compute and data handling paradigms, and operate in a larger, federated context that spans multiple, distributed HPC clusters.”

To qualify and quantify their assumptions, the authors report they are in the process of designing a survey that will be sent out to platform providers and application groups to verify current issues on a broader and larger scale. They write, “The main focus of our work will be on the further evaluation of our prototype system. We are working on a ‘bare metal’ deployment on HPC cluster hardware at EPCC. This will allow us to carry out detailed measurements and benchmarks to analyze the overhead and scalability of our approach. We will also engage with computational science groups working on second generation applications to explore their real-life application in the context of cHPC.”

Link to paper (Rethinking HPC Platforms: Challenges, Opportunities and Recommendations): https://arxiv.org/pdf/1702.05513.pdf

Addendum (3/1/17):

The authors are well aware of the many ongoing efforts to leverage container technology for HPC. Lead author Weidner told HPCwire, “I am familiar with the work on Singularity that Gregory Kurtzer and his peers at LBNL are doing. It is a prominent project with quite significant real-world uptake and definitely needs to be, along with a few others, added to the related work section in the next iteration of our paper.

“We can definitely observe that over the past year, operating-system level virtualization and containers have become more and more common place in HPC application and middleware stacks, especially in projects that rely on, or support what we call “second gen.” applications. Take Cornell’s BioHPC Lab (https://cbsu.tc.cornell.edu/lab/lab.aspx) for example, or NERSC’s Shifter (http://www.nersc.gov/users/software/using-shifter-and-docker/using-shifter-at-nersc/). I think with Singularity leading the way, the objective of most of these projects is to address what we refer to as the “centralized (software) deployment monopolies” and “application mobility” in our paper.

The scope for cHPC tries to be a bit broader, says Weidner. “First of all, unlike Singularity, cHPC is not production-grade software. It is a research prototype. Having said that, the vision of cHPC and the conceptual work we are doing around it is not just to encapsulate (end-)user applications but to incorporate more low-level HPC system components. Our aim is to develop blueprints for more “data-driven” HPC environments in which application adaptivity, elastic scalability and resilience strategies are supported explicitly by the platform.

“We believe that a data-driven HPC software stack is one of the critical, but still missing components to address the upcoming exascale application challenges in which real-time predictive operational analytics will play an important role to support resilience and efficiency at extreme scales. Containers are an excellent vehicle to research these new data-data driven system and application architectures without having to implement an entire HPC system from scratch. That’s why we have developed cHPC.”

Weidner and his colleagues are working on a paper in which we lay out a comprehensive framework for operational data management in HPC systems (“Data-Driven HPC”).

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!

Nvidia’s Jensen Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can do. Animated. Backstopped by a stream of data charts, produ Read more…

By John Russell

New Panasas High Performance Storage Straddles Commercial-Traditional HPC

November 13, 2018

High performance storage vendor Panasas has launched a new version of its ActiveStor product line this morning featuring what the company said is the industry’s first plug-and-play, portable parallel file system that d Read more…

By Doug Black

SC18 Student Cluster Competition – Revealing the Field

November 13, 2018

It’s November again and we’re almost ready for the kick-off of one of the greatest computer sports events in the world – the SC Student Cluster Competition. This is the twelfth time that teams of university undergr Read more…

By Dan Olds

HPE Extreme Performance Solutions

AI Can Be Scary. But Choosing the Wrong Partners Can Be Mortifying!

As you continue to dive deeper into AI, you will discover it is more than just deep learning. AI is an extremely complex set of machine learning, deep learning, reinforcement, and analytics algorithms with varying compute, storage, memory, and communications needs. Read more…

IBM Accelerated Insights

New Data Management Techniques for Intelligent Simulations

The trend in high performance supercomputer design has evolved – from providing maximum compute capability for complex scalable science applications, to capacity computing utilizing efficient, cost-effective computing power for solving a small number of large problems or a large number of small problems. Read more…

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Bailey Hutchison Convention Center and much of the surrounding Read more…

By Tiffany Trader

Nvidia’s Jensen Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can Read more…

By John Russell

New Panasas High Performance Storage Straddles Commercial-Traditional HPC

November 13, 2018

High performance storage vendor Panasas has launched a new version of its ActiveStor product line this morning featuring what the company said is the industry Read more…

By Doug Black

SC18 Student Cluster Competition – Revealing the Field

November 13, 2018

It’s November again and we’re almost ready for the kick-off of one of the greatest computer sports events in the world – the SC Student Cluster Competitio Read more…

By Dan Olds

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

OpenACC Talks Up Summit and Community Momentum at SC18

November 12, 2018

OpenACC – the directives-based parallel programing model for optimizing applications on heterogeneous architectures – is showcasing user traction and HPC im Read more…

By John Russell

How ASCI Revolutionized the World of High-Performance Computing and Advanced Modeling and Simulation

November 9, 2018

The 1993 Supercomputing Conference was held in Portland, Oregon. That conference and it’s show floor provided a good snapshot of the uncertainty that U.S. supercomputing was facing in the early 1990s. Many of the companies exhibiting that year would soon be gone, either bankrupt or acquired by somebody else. Read more…

By Alex R. Larzelere

At SC18: GM, Boeing, Deere, BP Talk Enterprise HPC Strategies

November 9, 2018

SC18 in Dallas (Nov.11-16) will feature an impressive series of sessions focused on the enterprise HPC deployments at some of the largest industrial companies: Read more…

By Doug Black

SC 30th Anniversary Perennials 1988-2018

November 8, 2018

Many conferences try, fewer succeed. Thirty years ago, no one knew if the first SC would also be the last. Thirty years later, we know it’s the biggest annual Read more…

By Doug Black & Tiffany Trader

Cray Unveils Shasta, Lands NERSC-9 Contract

October 30, 2018

Cray revealed today the details of its next-gen supercomputing architecture, Shasta, selected to be the next flagship system at NERSC. We've known of the code-name "Shasta" since the Argonne slice of the CORAL project was announced in 2015 and although the details of that plan have changed considerably, Cray didn't slow down its timeline for Shasta. Read more…

By Tiffany Trader

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

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

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

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

Leading Solution Providers

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

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

HPE No. 1, IBM Surges, in ‘Bucking Bronco’ High Performance Server Market

September 27, 2018

Riding healthy U.S. and global economies, strong demand for AI-capable hardware and other tailwind trends, the high performance computing server market jumped 28 percent in the second quarter 2018 to $3.7 billion, up from $2.9 billion for the same period last year, according to industry analyst firm Hyperion Research. Read more…

By Doug Black

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

Germany Celebrates Launch of Two Fastest Supercomputers

September 26, 2018

The new high-performance computer SuperMUC-NG at the Leibniz Supercomputing Center (LRZ) in Garching is the fastest computer in Germany and one of the fastest i Read more…

By Tiffany Trader

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon 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

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

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