Defining Scalable OS Requirements for Exascale and Beyond

By Robert W. Wisniewski, Chief Software Architect for Extreme Scale Computing, Intel

October 5, 2015

Over the past couple of decades two primary trends have driven system software for supercomputers to become significantly more complex. First, hardware has become more complex. Massive inter-node parallelism (100,000+ nodes), increasingly large intra-node parallelism (100+ hardware threads), wider vector units, accelerators, coprocessors, etc., have required that system software play a larger role in delivering the performance available from this new hardware. Second, applications have changed. Historically, extreme-scale high-performance computing (HPC) applications were stand-alone executables that were bulk synchronous, spatially and statically partitioned, and required minimal system services.

As the community moves towards exascale, applications are being integrated into workflows, require big data and analytics, are incorporating asynchronous capabilities, and demand an increasingly rich set of libraries, runtimes, and system services. As part of providing comprehensive system services, the compute node operating system is being integrated into the control system, which is sometimes referred to as the global operating system. While providing a complete set of system services is important, this article focuses on the challenges and needs of the Operating System (OS) on the compute node. Figure 1 shows the “left to right” model typical in HPC systems, the control system, and the node-local OS. We describe how these trends are changing the requirements and hence design of the HPC compute node OS, and describe promising directions for how these challenges will be met for exascale computing.

Wisniewski Figure1_9.29.15Background:
In addition to the above challenges, the compute node OS, hereafter just OS, must address an additional challenge. There has been a debate in the software community about whether a revolutionary or an evolutionary approach is needed to achieve exascale. We contend both are critical, and that the real challenge for system software to get to exascale and beyond is figuring out how to incorporate and support existing computation paradigms in an evolutionary manner while simultaneously supporting new revolutionary paradigms. The OS must provide this capability as well.

Historically, two designs have been used for operating systems. One is to start with a Full-Weight Kernel (FWK), typically Linux[i], and remove features so that it will scale up across more cores and out across a large cluster. Another approach is to start with a new, Light-Weight Kernel (LWK) and add functionality to provide a familiar API, typically Linux.

Linux, or more specifically the Linux API, including glibc and the Linux environment (/proc and /sys) is important for supporting the evolutionary aspect and for addressing the described complexity needs. There is a set of classical needs that are interrelated and must be met, including low noise, high performance, scalability for capability computing, and allowing user-space access to performance critical hardware, e.g., the network. There is a set of emerging needs that include the ability to handle asynchrony, manage power locally and globally, handle re- liability, provide for over commit of software threads, and interact effectively with runtimes. The classical needs allow applications to achieve high performance while the emerging needs provide for higher productivity and support of new programming and execution models.

A key requirement for an exascale OS kernel is nimbleness, the ability to be modified quickly and efficiently to support new hardware and to provide targeted capabilities for the HPC libraries, runtimes, and applications. This is opposite of the requirement for a general purpose OS, whose success is based on broad-based use with known interfaces. High-end HPC systems, those that will first achieve exascale and beyond, push the edge of technology out of necessity and introduce new hardware capabilities that need to be utilized effectively by high-end HPC software. As an example, a decade ago, large pages were integrated into CNK, Blue Gene’s LWK in about six months while large page support in major distributions of Linux took significantly longer and remains an on-going effort. The reason is CNK’s limited application domain allowed many simplifying assumptions. New hardware technology will be required to achieve exascale computing, and applications will need to aggressively exploit the new technology. Thus, what is needed, is an approach that while preserving the capability to support the existing interfaces (evolutionary) provides targeted and effective use of the new hardware (revolutionary) in a rapid and targeted manner (nimbleness).

The historical approaches of adding features to an LWK or trimming an FWK have additional weaknesses when trying to simultaneously support revolutionary and evolutionary models while trying to achieve high performance in an increasingly complex and rich environment. LWKs have been shown to exhibit low noise that allows high scalability. They also have been able to target the specific needs of HPC applications allowing higher performance. As the community moves to exascale, the need to leverage specific hardware and tailor the OS service to application needs, will become more important.

Three classes of approaches are emerging to overcome these weaknesses.

  1. The first is to continue to use Linux as the base and containers to limit the interference between multiple applications thereby allowing the different applications (often a classical HPC and an emerging one, e.g., analytics or visualization) to share a node’s resources while trying to minimize the effect on the classical HPC application. Containers provide a virtual environment in Linux that provide the appearance of isolated OS instances. In the Linux community there is considerable excitement and work involving containers and HPC may be able to leverage this broader base of activity. The challenge with the container approach is that Linux remains underneath and any fundamental challenge with Linux itself remains.
  1. The second approach is virtualization. A virtualized platform on which either an LWK or a Linux kernel can run provides high performance or the features of a more general purpose OS. It is important to ensure that the cost of virtualization, especially for the LWK, is kept to a bare minimum. This approach in isolation presents problems for simultaneous use of the LWK and FWK by the application, but could be combined with the approach below.
  1. The third approach is to run multiple kernels simultaneously on a node. This has been an area of intense effort in the last several years and many efforts including McKernel, FusedOS, Nix, Tesselation, Popcorn Linux, and mOS are exploring this path. We will describe mOS as an example. The vision is to run an LWK on the majority of the cores to achieve high performance and scalability, while running Linux on one or a small number of cores to provide Linux compatibility. From the application’s perspective it achieves the performance of an LWK but appears to be Linux.

Wisniewski. Figure2_9.29.15Figure 2 depicts the fully generalized mOS architecture for the research direction we are exploring in the multiple kernels space. While the figure depicts the full generality, we expect most instantiations to run a single application on a single LWK. A standard HPC Linux runs on a given core(s); an LWK(s )runs on the rest of the cores. On any given LWK, one or more applications may run. As mentioned, the expected scenario is to run Linux on one core, and one application on one LWK on the rest of the cores. When the application makes a system call, it is routed to the OS Node (via arrow 1b) if it is a file I/O operation, or to the LWK on the core that made the call (via arrow 1a). The LWK will handle performance critical calls. If it is a call that is not implemented by the LWK, then the LWK will transfer the call to Linux (via arrow 2) to be serviced. Linux will service the call and return to the LWK, which in turn returns back to user space on the original core. With this methodology, the application achieves the high performance and scalability offered by an LWK while providing the Linux environment. We have worked out an architecture for mOS and have early prototype code that is allowing us to confirm several of the architecture decisions we made.

System software for exascale systems is of necessity becoming more complex. The compute node OS, and how it supports the compute node runtimes and interacts with the global control system, will play a critical role in allowing us to achieve exascale and beyond. To be evolutionary and revolutionary simultaneously, the OS must meet the classical and emerging HPC requirements. A promising direction that several groups are exploring to address these needs is running multiple operating system kernels on a node simultaneously. While significant challenges remain and innovative work is still needed on the OS front there is confidence in being able to get the community well beyond exascale computing.

Author Bio:
Dr. Robert W. Wisniewski is an ACM Distinguished Scientist and the Chief Software Architect for Extreme Scale Computing and a Senior Principal Engineer at Intel Corporation. He has published over 60 papers in the area of high performance computing, computer systems, and system performance, and has filed over 50 patents. Before coming to Intel, he was the chief software architect for Blue Gene Research and manager of the Blue Gene and Exascale Research Software Team at the IBM T.J. Watson Research Facility, where he was an IBM Master Inventor and lead the software effort on Blue Gene/Q, which was the fastest machine in the world on the June 2012 Top 500 list, and occupied 4 of the top 10 positions. Prior to working on Blue Gene, he worked on the K42 Scalable Operating System project targeted at scalable next generation servers and the DARPA HPCS project on Continuous Program Optimization that utilizes integrated performance data to automatically improve application and system performance.  Before joining IBM Research, and after receiving a Ph.D. in Computer Science from the University of Rochester, Robert worked at Silicon Graphics on high-end parallel OS development, parallel real-time systems, and real-time performance monitoring.

[i] Linux® is the registered trademark of Linus Torvalds in the U.S. and other countries.

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!

Russian and American Scientists Achieve 50% Increase in Data Transmission Speed

September 20, 2018

As high-performance computing becomes increasingly data-intensive and the demand for shorter turnaround times grows, data transfer speed becomes an ever more important bottleneck. Now, in an article published in IEEE Tra Read more…

By Oliver Peckham

IBM to Brand Rescale’s HPC-in-Cloud Platform

September 20, 2018

HPC (or big compute)-in-the-cloud platform provider Rescale has formalized the work it’s been doing in partnership with public cloud vendors by announcing its Powered by Rescale program – with IBM as its first named Read more…

By Doug Black

Democratization of HPC Part 1: Simulation Sheds Light on Building Dispute

September 20, 2018

This is the first of three articles demonstrating the growing acceptance of High Performance Computing especially in new user communities and application areas. Major reasons for this trend are the ongoing improvements i Read more…

By Wolfgang Gentzsch

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

Clouds Over the Ocean – a Healthcare Perspective

Advances in precision medicine, genomics, and imaging; the widespread adoption of electronic health records; and the proliferation of medical Internet of Things (IoT) and mobile devices are resulting in an explosion of structured and unstructured healthcare-related data. Read more…

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 Gordon Bell Prize used Summit in their work. That’s impres 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

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

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

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

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17


AMD @ SC17


ASRock Rack @ SC17

ASRock Rack



DDN Storage @ SC17

DDN Storage

Huawei @ SC17


IBM @ SC17


IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17


Lenovo @ SC17


Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17


Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17


Tyan @ SC17


Univa @ SC17


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

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

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