The Last Mile of Virtualization

By Wolfgang Gentzsch

May 3, 2012

A review of eXludus’ new micro-virtualization technology for multicore environments

In a previous article (We Need More than Multicore), I discussed the evolution of multicore processors, and the dramatic effect this processor shift can have on compute cluster performance. Clearly, leveraging a lot of cores will require that many concurrent tasks – as opposed to a single massively parallel task – run safely and predictably within a system. These concurrent tasks will range from serial to multi-threaded to parallel tasks, and all will need to share the same system resources in a productive and reliable manner.

The question becomes how to do this in operating systems (OS) environments that were not designed with multicore architectures in mind. For example, Linux, which has become the pervasive operating OS for servers, is based on time slicing, which is somewhat analogous to suboptimal round-robin server farm dispatch. But it has limitations when running many concurrent tasks that access shared processors and memory. As the number of competing tasks increases, the likelihood of interference between tasks rises exponentially.

The operating system has limited tools that identify escalating resource access problems or proactive defenses to resolve such problems. With these inherent limitations, users often realize reduced system performance and/or reliability. Nor can the OS manage work prioritization between tasks very well, so the established workload management priorities are largely lost when a mix of jobs from different queues are dispatched to a compute node. In summary, the major issues with today’s multicore systems include:

  • For most applications, users are only able to leverage the capabilities of ALL cores (and thus experience high overall utilization) by running many iterations concurrently. The challenge then becomes a balancing act. Even slightly too much work, in terms of physical memory oversubscription (as little as 5 percent), leads to performance degradation and reliability problems. Too little work gets done and valuable resources sit idle.

  • It is manually impossible to continuously balance work against resources, as the use of these resources fluctuates during an application’s execution. And user memory hints, to the extent they are accurate, have to express the high-water usage even though an application may use much less than the high-water mark for a significant percentage of the time.
  • With multi-application/multi-tenant systems, it is difficult or even impossible to meet varying service level agreements (SLAs). Users and applications may not get the level of resources expected, committed, or paid for, and performance levels may vary widely from one iteration to the next.
  • With many concurrently running applications, all work becomes largely equal in the kernel, so high-value tasks can be slowed down by low-value tasks. Under standard Linux it is difficult or even impossible to set varying priority levels for the various executing applications.
  • Full server virtualization is too heavy-handed for running high performance applications. While legacy virtualization may allow you to segment a system in an attempt to improve system utilization, the added utilization rate may be offset in large part by the hypervisor overhead. Legacy server virtualization is useful for multi-OS requirements, but if the organization just needs to run millions of jobs under the same (Linux) OS then overhead, administration, and costs are too high.  

Multicore optimization specialist eXludus Technologies believes it has the answer. The company recently announced the industry’s first micro-virtualization solution. This software creates lightweight micro-containers that encapsulate one or more applications, and are based upon defined application or project policies. These containers have embedded resource allocation intelligence that applies predictive queuing algorithms in order to optimize allocation of micro-resources, such as cores and memory. And it does so in real time.

With negligible system and administrative overhead, the eXludus solution expands the use case for virtualization, making it suitable for performance-sensitive environments (most notably, HPC) that have previously avoided virtualization because of overhead concerns.

The software promises to extract up to 70 percent more throughput from the same resources, while acting as a safety net to avoid resource over-subscription that is detrimental to system performance. Since the micro-containers run within an OS, the eXludus software can be deployed separately from or together with existing server and storage virtualization solutions.

By applying virtualization underneath the OS, a number of benefits are exposed. For example, although it’s easy to load a system, the challenge is achieving maximum utilization while avoiding resource oversubscription, which leads to performance reduction and system instability. Using a lightweight framework, micro-virtualization automates the process of optimizing resources, safely allowing system utilization to be increased. In more detail, micro-virtualization is designed to:

  • Achieve more application processing power per system, aids server consolidation, resulting in fewer systems needed for given workload, and reduces data center power demands (system power, cooling, and space).

  • Maintain kernel level task priorities so that resources are steered to high-value work.
  • Ensure SLA can be met though simple and easy to define policies.

The support of SLAs is particularly important. Multi-tenancy invariably grows with core counts, either via cloud-like unrelated users or within the enterprise, where various departments or projects end up sharing systems to a greater degree. These multi-tenants pay in some manner, either directly or via budget contribution, so they demand to get what they pay for. Therefore, consistent and predictable results are important, i.e., a user can’t complete processing in X time on one iteration and 2X on the next iteration.

Micro-virtualization provides mechanisms that ensure that specific applications, users, and projects receive the CPU and memory resources that have been paid for or committed to. Specifically, administrators can declare CPU and memory percentages that guarantee resource levels.

Within the kernel, multi-tenant/multi-user/multi-project work falls subject to equal OS time-slice behavior. That’s true even though the work, which ranges from high-cost applications to open-source, is not all equal.  Users can easily run into situations where high-value work is slowed by low-value work. Micro-virtualization provides tools that allow for discrete task prioritization that can predictably steer resource allocations.

Within an enterprise there may be many iterations of an application running, but each iteration may have unique value. Consider a chip-design environment where multiple next-gen processors are under development. The soon-to-be-released processor has more enterprise value than a design to be completed in three years. Micro-virtualization easily accommodates resource steering to the high value work, even to the extent that work can be flagged as having exclusive access to system resources — think of a chip tape-out that needs last minute fixes, or rendering where a movie is about to be released and maximum performance is required.

The eXludus solution also promises to open up HPC to virtualization. Legacy server virtualization has not been very successful in these situations as the heavyweight hypervisor approach has high overhead costs. Micro-virtualization is truly lightweight, in the range of 1 to 2 percent overhead, whereas full server virtualization may entail an 18 to 20 penalty in these scenarios. And where full virtualization complexity is administratively cumbersome, micro-virtualization is simple and literally can be deployed within hours.  

A current limitation of eXludus micro-virtualization is that all work must be run within a single OS environment, in this case Linux. And the solution does not yield an easily predictable or consistent performance gain. Throughput increases are a function of the workload, which users may find difficult to comprehend.

In aggregate though, micro-virtualization as a means to effectively segment multicore systems and extract maximum efficiencies appears to be an idea whose time has come. Service efficiency is improved and resources are more accurately steered to the highest value tasks in support of business objectives.

—–

Wolfgang Gentzsch is an independent HPC consultant for cluster, grid, and cloud computing, technologies and a member of the Board of Directors for eXludus Technologies.

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!

AWS Embraces FPGAs, ‘Elastic’ GPUs

December 2, 2016

A new instance type rolled out this week by Amazon Web Services is based on customizable field programmable gate arrays that promise to strike a balance between performance and cost as emerging workloads create requirements often unmet by general-purpose processors. Read more…

By George Leopold

AWS Launches Massive 100 Petabyte ‘Sneakernet’

December 1, 2016

Amazon Web Services now offers a way to move data into its cloud by the truckload. Read more…

By Tiffany Trader

Weekly Twitter Roundup (Dec. 1, 2016)

December 1, 2016

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

HPC Career Notes (Dec. 2016)

December 1, 2016

In this monthly feature, we’ll keep you up-to-date on the latest career developments for individuals in the high performance computing community. Read more…

By Thomas Ayres

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

IBM and NSF Computing Pioneer Erich Bloch Dies at 91

November 30, 2016

Erich Bloch, a computational pioneer whose competitive zeal and commercial bent helped transform the National Science Foundation while he was its director, died last Friday at age 91. Bloch was a productive force to be reckoned. During his long stint at IBM prior to joining NSF Bloch spearheaded development of the “Stretch” supercomputer and IBM’s phenomenally successful System/360. Read more…

By John Russell

Pioneering Programmers Awarded Presidential Medal of Freedom

November 30, 2016

In an awards ceremony on November 22, President Barack Obama recognized 21 recipients with the Presidential Medal of Freedom, the Nation’s highest civilian honor. Read more…

By Tiffany Trader

Seagate-led SAGE Project Delivers Update on Exascale Goals

November 29, 2016

Roughly a year and a half after its launch, the SAGE exascale storage project led by Seagate has delivered a substantive interim report – Data Storage for Extreme Scale. Read more…

By John Russell

AWS Launches Massive 100 Petabyte ‘Sneakernet’

December 1, 2016

Amazon Web Services now offers a way to move data into its cloud by the truckload. Read more…

By Tiffany Trader

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Seagate-led SAGE Project Delivers Update on Exascale Goals

November 29, 2016

Roughly a year and a half after its launch, the SAGE exascale storage project led by Seagate has delivered a substantive interim report – Data Storage for Extreme Scale. Read more…

By John Russell

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

HPE-SGI to Tackle Exascale and Enterprise Targets

November 22, 2016

At first blush, and maybe second blush too, Hewlett Packard Enterprise’s (HPE) purchase of SGI seems like an unambiguous win-win. SGI’s advanced shared memory technology, its popular UV product line (Hanna), deep vertical market expertise, and services-led go-to-market capability all give HPE a leg up in its drive to remake itself. Bear in mind HPE came into existence just a year ago with the split of Hewlett-Packard. The computer landscape, including HPC, is shifting with still unclear consequences. One wonders who’s next on the deal block following Dell’s recent merger with EMC. Read more…

By John Russell

Intel Details AI Hardware Strategy for Post-GPU Age

November 21, 2016

Last week at SC16, Intel revealed its product roadmap for embedding its processors with key capabilities and attributes needed to take artificial intelligence (AI) to the next level. Read more…

By Alex Woodie

SC Says Farewell to Salt Lake City, See You in Denver

November 18, 2016

After an intense four-day flurry of activity (and a cold snap that brought some actual snow flurries), the SC16 show floor closed yesterday (Thursday) and the always-extensive technical program wound down today. Read more…

By Tiffany Trader

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

Why 2016 Is the Most Important Year in HPC in Over Two Decades

August 23, 2016

In 1994, two NASA employees connected 16 commodity workstations together using a standard Ethernet LAN and installed open-source message passing software that allowed their number-crunching scientific application to run on the whole “cluster” of machines as if it were a single entity. Read more…

By Vincent Natoli, Stone Ridge Technology

IBM Advances Against x86 with Power9

August 30, 2016

After offering OpenPower Summit attendees a limited preview in April, IBM is unveiling further details of its next-gen CPU, Power9, which the tech mainstay is counting on to regain market share ceded to rival Intel. Read more…

By Tiffany Trader

AWS Beats Azure to K80 General Availability

September 30, 2016

Amazon Web Services has seeded its cloud with Nvidia Tesla K80 GPUs to meet the growing demand for accelerated computing across an increasingly-diverse range of workloads. The P2 instance family is a welcome addition for compute- and data-focused users who were growing frustrated with the performance limitations of Amazon's G2 instances, which are backed by three-year-old Nvidia GRID K520 graphics cards. Read more…

By Tiffany Trader

Think Fast – Is Neuromorphic Computing Set to Leap Forward?

August 15, 2016

Steadily advancing neuromorphic computing technology has created high expectations for this fundamentally different approach to computing. Read more…

By John Russell

The Exascale Computing Project Awards $39.8M to 22 Projects

September 7, 2016

The Department of Energy’s Exascale Computing Project (ECP) hit an important milestone today with the announcement of its first round of funding, moving the nation closer to its goal of reaching capable exascale computing by 2023. Read more…

By Tiffany Trader

HPE Gobbles SGI for Larger Slice of $11B HPC Pie

August 11, 2016

Hewlett Packard Enterprise (HPE) announced today that it will acquire rival HPC server maker SGI for $7.75 per share, or about $275 million, inclusive of cash and debt. The deal ends the seven-year reprieve that kept the SGI banner flying after Rackable Systems purchased the bankrupt Silicon Graphics Inc. for $25 million in 2009 and assumed the SGI brand. Bringing SGI into its fold bolsters HPE's high-performance computing and data analytics capabilities and expands its position... Read more…

By Tiffany Trader

ARM Unveils Scalable Vector Extension for HPC at Hot Chips

August 22, 2016

ARM and Fujitsu today announced a scalable vector extension (SVE) to the ARMv8-A architecture intended to enhance ARM capabilities in HPC workloads. Fujitsu is the lead silicon partner in the effort (so far) and will use ARM with SVE technology in its post K computer, Japan’s next flagship supercomputer planned for the 2020 timeframe. This is an important incremental step for ARM, which seeks to push more aggressively into mainstream and HPC server markets. Read more…

By John Russell

IBM Debuts Power8 Chip with NVLink and Three New Systems

September 8, 2016

Not long after revealing more details about its next-gen Power9 chip due in 2017, IBM today rolled out three new Power8-based Linux servers and a new version of its Power8 chip featuring Nvidia’s NVLink interconnect. Read more…

By John Russell

Leading Solution Providers

Vectors: How the Old Became New Again in Supercomputing

September 26, 2016

Vector instructions, once a powerful performance innovation of supercomputing in the 1970s and 1980s became an obsolete technology in the 1990s. But like the mythical phoenix bird, vector instructions have arisen from the ashes. Here is the history of a technology that went from new to old then back to new. Read more…

By Lynd Stringer

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

Intel Launches Silicon Photonics Chip, Previews Next-Gen Phi for AI

August 18, 2016

At the Intel Developer Forum, held in San Francisco this week, Intel Senior Vice President and General Manager Diane Bryant announced the launch of Intel's Silicon Photonics product line and teased a brand-new Phi product, codenamed "Knights Mill," aimed at machine learning workloads. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Beyond von Neumann, Neuromorphic Computing Steadily Advances

March 21, 2016

Neuromorphic computing – brain inspired computing – has long been a tantalizing goal. The human brain does with around 20 watts what supercomputers do with megawatts. And power consumption isn’t the only difference. Fundamentally, brains ‘think differently’ than the von Neumann architecture-based computers. While neuromorphic computing progress has been intriguing, it has still not proven very practical. Read more…

By John Russell

Dell EMC Engineers Strategy to Democratize HPC

September 29, 2016

The freshly minted Dell EMC division of Dell Technologies is on a mission to take HPC mainstream with a strategy that hinges on engineered solutions, beginning with a focus on three industry verticals: manufacturing, research and life sciences. "Unlike traditional HPC where everybody bought parts, assembled parts and ran the workloads and did iterative engineering, we want folks to focus on time to innovation and let us worry about the infrastructure," said Jim Ganthier, senior vice president, validated solutions organization at Dell EMC Converged Platforms Solution Division. Read more…

By Tiffany Trader

Container App ‘Singularity’ Eases Scientific Computing

October 20, 2016

HPC container platform Singularity is just six months out from its 1.0 release but already is making inroads across the HPC research landscape. It's in use at Lawrence Berkeley National Laboratory (LBNL), where Singularity founder Gregory Kurtzer has worked in the High Performance Computing Services (HPCS) group for 16 years. Read more…

By Tiffany Trader

Micron, Intel Prepare to Launch 3D XPoint Memory

August 16, 2016

Micron Technology used last week’s Flash Memory Summit to roll out its new line of 3D XPoint memory technology jointly developed with Intel while demonstrating the technology in solid-state drives. Micron claimed its Quantx line delivers PCI Express (PCIe) SSD performance with read latencies at less than 10 microseconds and writes at less than 20 microseconds. Read more…

By George Leopold

  • arrow
  • Click Here for More Headlines
  • arrow
Share This