Tuning InfiniBand Interconnects Using Congestion Control

By Adam Dorsey

July 26, 2017

InfiniBand is among the most common and well-known cluster interconnect technologies. However, the complexities of an InfiniBand (IB) network can frustrate the most experienced cluster administrators. Maintaining a balanced fabric topology, dealing with underperforming hosts and links, and chasing potential improvements keeps all of us on our toes. Sometimes, though, a little research and experimentation can find unexpected performance and stability gains.

For example, consider a 1,300-node cluster using Intel TrueScale IB for job communication and a Panasas ActiveStor filesystem for storage. Panasas only communicates to clients via Ethernet and not IB, so a group of Mellanox switches act as gateways from the Panasas Ethernet to the TrueScale IB.

Every system has bottlenecks; in our case, the links to and from these IB/Ethernet gateways showed congestion due to the large amount of disk traffic. This adversely affects the whole cluster — jobs can’t get the data they need, and the increased congestion interferes with other IB traffic as well.

Fortunately, InfiniBand provides a congestion control mechanism that can help mitigate the effects of severe congestion on the fabric. We were able to implement this feature to save the expense and trouble of adding additional IB/Ethernet gateways.

What Is InfiniBand Congestion Control?

InfiniBand is intended to be a lossless fabric. IB switches won’t drop packets for flow control unless they absolutely have to, usually in cases of hardware failure or malformed packets. Instead of dropping packets and retransmitting, like Ethernet does, InfiniBand uses a system of credits to perform flow control.

Communication occurs between IB endpoints, which in turn are issued credits based on the amount of buffer space the receiving device has. If the credit cost of the data to be transmitted is less than the credits remaining on the receiving device, the data is transmitted. Otherwise, the transmitting device holds on to the data until the receiving device has sufficient credits free.

This method of flow control works well for normal loads on well-balanced, non-oversubscribed IB fabrics. However, if the fabric is unbalanced or oversubscribed or just heavily loaded, some links may be oversaturated with traffic beyond the ability of the credit mechanism to help.

Congestion can be observed by checking the IB error counters. When an IB device attempts to transmit data but the receiving device cannot receive data due to congestion, the PortXmitWait counter is incremented. If the congestion is so bad that the data cannot be transmitted before the time-to-live on the packet expires, the packet is discarded and the PortXmitDiscards counter is incremented. If you’re seeing high values of PortXmitWait and PortXmitDiscards counters, enabling congestion control may help manage congestion on your InfiniBand fabric.

How Does InfiniBand Congestion Control Work?

When an IB switch detects congestion on a link, it enables a special bit, called the Forward Explicit Congestion Notification (FECN) bit, which informs the destination device that congestion has been detected on the link. When the destination receives a packet marked with the FECN bit, the destination device notifies the sending device of the congestion via a Backwards Explicit Congestion Notification bit (BECN.)

When the source receives the BECN bit notification from the destination, the sending (source) device begins to throttle the amount of data it sends to the destination. The mechanism it uses is the credits system – by reducing the credits available to the destination, the size and rate of the packets are effectively decreased. The sending device may also add a delay between packets to provide the destination device time to catch up on data.

Over time, the source device increases credits for the destination device, gradually increasing the amount of packets sent. If the destination device continues to receive FECN packets from its switch, it again transmits BECN packets to the source device and the throttling is increased again. Without the reception of BECN packets from the destination device, the source device eventually returns to normal packet transmission. This balancing act is managed by congestion control parameters which require tuning for each environment.

After enabling InfiniBand congestion control and proper tuning, we realized a 15 percent improvement in our Panasas file system benchmark testing. PortXmitDiscards counters were completely clear, and PortXmitWait counters were significantly smaller, indicating that congestion control was doing its job.

Given that no additional hardware or other costs were required to achieve these results, a speed increase of 15 percent plus increased stability of the IB fabric was a nice result.

How Can I Enable InfiniBand Congestion Control?

Congestion control must be enabled on all IB devices and hosts, as well as on the IB subnet manager. This process includes turning on congestion control and setting a congestion control key on each device, as well as tuning the congestion control tables and parameters on each host and switch.

After congestion control is enabled on each IB device, the OpenSM configuration file must be modified to tune the subnet manager’s congestion control manager. Please note that mistuned parameters will either wreak havoc on a fabric or be completely ineffectual, so be careful – and do plenty of testing on a safe “test” system. Never attempt this on a live or production system.

Enabling InfiniBand congestion control had an immediate positive effect on our IB fabric. If you are suffering from issues with fabric congestion, enabling congestion control may provide the similar relief for your fabric as well, without the cost of adding additional hardware.

About the Author

Adam Dorsey is a systems administrator and site lead for RedLine Performance Solutions.

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!

HPC in Life Sciences Part 1: CPU Choices, Rise of Data Lakes, Networking Challenges, and More

February 21, 2019

For the past few years HPCwire and leaders of BioTeam, a research computing consultancy specializing in life sciences, have convened to examine the state of HPC (and now AI) use in life sciences. Without HPC writ large, modern life sciences research would quickly grind to a halt. It’s true most life sciences research computing... Read more…

By John Russell

Arm Unveils Neoverse N1 Platform with up to 128-Cores

February 20, 2019

Following on its Neoverse roadmap announcement last October, Arm today revealed its next-gen Neoverse microarchitecture with compute and throughput-optimized silicon designs catered toward general-purpose cloud computing Read more…

By Tiffany Trader

The Internet of Criminal Things—Trust in the Gods but Verify!

February 20, 2019

“Are we under attack?” asked Professor Elmarie Biermann of the Cyber Security Institute during the recent South African Centre for High Performance Computing’s (CHPC) National Conference in Cape Town. A quick show Read more…

By Elizabeth Leake, STEM-Trek

HPE Extreme Performance Solutions

HPE and Intel® Omni-Path Architecture: How to Power a Cloud

Learn how HPE and Intel® Omni-Path Architecture provide critical infrastructure for leading Nordic HPC provider’s HPCFLOW cloud service.

powercloud_blog.jpgFor decades, HPE has been at the forefront of high-performance computing, and we’ve powered some of the fastest and most robust supercomputers in the world. Read more…

IBM Accelerated Insights

The Perils of Becoming Trapped in the Cloud

Terms like ‘open systems’ have been bandied about for decades. While modern computer systems are relatively open compared to their predecessors, there are still plenty of opportunities to become locked into proprietary interfaces. Read more…

Machine Learning Takes Heat for Science’s Reproducibility Crisis

February 19, 2019

Scientists are raising red flags about the accuracy and reproducibility of conclusions drawn by machine learning frameworks. Among the remedies are developing new ML systems that can question their own predictions, show Read more…

By George Leopold

HPC in Life Sciences Part 1: CPU Choices, Rise of Data Lakes, Networking Challenges, and More

February 21, 2019

For the past few years HPCwire and leaders of BioTeam, a research computing consultancy specializing in life sciences, have convened to examine the state of HPC (and now AI) use in life sciences. Without HPC writ large, modern life sciences research would quickly grind to a halt. It’s true most life sciences research computing... Read more…

By John Russell

Arm Unveils Neoverse N1 Platform with up to 128-Cores

February 20, 2019

Following on its Neoverse roadmap announcement last October, Arm today revealed its next-gen Neoverse microarchitecture with compute and throughput-optimized si Read more…

By Tiffany Trader

Insights from Optimized Codes on Cineca’s Marconi

February 15, 2019

What can you do with 381,392 CPU cores? For Cineca, it means enabling computational scientists to expand a large part of the world’s body of knowledge from the nanoscale to the astronomic, from calculating quantum effects in new materials to supporting bioinformatics for advanced healthcare research to screening millions of possible chemical combinations to attack a deadly virus. Read more…

By Ken Strandberg

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o Read more…

By Tiffany Trader

UC Berkeley Paper Heralds Rise of Serverless Computing in the Cloud – Do You Agree?

February 13, 2019

Almost exactly ten years to the day from publishing of their widely-read, seminal paper on cloud computing, UC Berkeley researchers have issued another ambitious examination of cloud computing - Cloud Programming Simplified: A Berkeley View on Serverless Computing. The new work heralds the rise of ‘serverless computing’ as the next dominant phase of cloud computing. Read more…

By John Russell

Iowa ‘Grows Its Own’ to Fill the HPC Workforce Pipeline

February 13, 2019

The global workforce that supports advanced computing, scientific software and high-speed research networks is relatively small when you stop to consider the magnitude of the transformative discoveries it empowers. Technical conferences provide a forum where specialists convene to learn about the latest innovations and schedule face-time with colleagues from other institutions. Read more…

By Elizabeth Leake, STEM-Trek

Trump Signs Executive Order Launching U.S. AI Initiative

February 11, 2019

U.S. President Donald Trump issued an Executive Order (EO) today launching a U.S Artificial Intelligence Initiative. The new initiative - Maintaining American L Read more…

By John Russell

Celebrating Women in Science: Meet Four Women Leading the Way in HPC

February 11, 2019

One only needs to look around at virtually any CS/tech conference to realize that women are underrepresented, and that holds true of HPC. SC hosts over 13,000 H Read more…

By AJ Lauer

Quantum Computing Will Never Work

November 27, 2018

Amid the gush of money and enthusiastic predictions being thrown at quantum computing comes a proposed cold shower in the form of an essay by physicist Mikhail Read more…

By John Russell

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

The Case Against ‘The Case Against Quantum Computing’

January 9, 2019

It’s not easy to be a physicist. Richard Feynman (basically the Jimi Hendrix of physicists) once said: “The first principle is that you must not fool yourse Read more…

By Ben Criger

AMD Sets Up for Epyc Epoch

November 16, 2018

It’s been a good two weeks, AMD’s Gary Silcott and Andy Parma told me on the last day of SC18 in Dallas at the restaurant where we met to discuss their show news and recent successes. Heck, it’s been a good year. Read more…

By Tiffany Trader

Intel Reportedly in $6B Bid for Mellanox

January 30, 2019

The latest rumors and reports around an acquisition of Mellanox focus on Intel, which has reportedly offered a $6 billion bid for the high performance interconn Read more…

By Doug Black

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o 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

Looking for Light Reading? NSF-backed ‘Comic Books’ Tackle Quantum Computing

January 28, 2019

Still baffled by quantum computing? How about turning to comic books (graphic novels for the well-read among you) for some clarity and a little humor on QC. The Read more…

By John Russell

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
NVIDIA @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

Deep500: ETH Researchers Introduce New Deep Learning Benchmark for HPC

February 5, 2019

ETH researchers have developed a new deep learning benchmarking environment – Deep500 – they say is “the first distributed and reproducible benchmarking s Read more…

By John Russell

IBM Quantum Update: Q System One Launch, New Collaborators, and QC Center Plans

January 10, 2019

IBM made three significant quantum computing announcements at CES this week. One was introduction of IBM Q System One; it’s really the integration of IBM’s Read more…

By John Russell

IBM Bets $2B Seeking 1000X AI Hardware Performance Boost

February 7, 2019

For now, AI systems are mostly machine learning-based and “narrow” – powerful as they are by today's standards, they're limited to performing a few, narro Read more…

By Doug Black

HPC Reflections and (Mostly Hopeful) Predictions

December 19, 2018

So much ‘spaghetti’ gets tossed on walls by the technology community (vendors and researchers) to see what sticks that it is often difficult to peer through Read more…

By John Russell

Nvidia’s Jensen Huang 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, product photos, and even a beautiful image of supernovae... Read more…

By John Russell

The Deep500 – Researchers Tackle an HPC Benchmark for Deep Learning

January 7, 2019

How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer Read more…

By John Russell

Intel Confirms 48-Core Cascade Lake-AP for 2019

November 4, 2018

As part of the run-up to SC18, taking place in Dallas next week (Nov. 11-16), Intel is doling out info on its next-gen Cascade Lake family of Xeon processors, specifically the “Advanced Processor” version (Cascade Lake-AP), architected for high-performance computing, artificial intelligence and infrastructure-as-a-service workloads. Read more…

By Tiffany Trader

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