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!

A Beginner’s Guide to the ASC19 Finals

April 22, 2019

Three thousand watts. That's how much power the competitors in the 2019 ASC Student Supercomputer Challenge here in Dalian, China, have to work with. Everybody would like more juice to run compute-intensive HPC simulatio Read more…

By Alex Woodie

Is Data Science the Fourth Pillar of the Scientific Method?

April 18, 2019

Nvidia CEO Jensen Huang revived a decade-old debate last month when he said that modern data science (AI plus HPC) has become the fourth pillar of the scientific method. While some disagree with the notion that statistic Read more…

By Alex Woodie

At ASF 2019: The Virtuous Circle of Big Data, AI and HPC

April 18, 2019

We've entered a new phase in IT -- in the world, really -- where the combination of big data, artificial intelligence, and high performance computing is pushing the bounds of what's possible in business and science, in w Read more…

By Alex Woodie with Doug Black and Tiffany Trader

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

Bridging HPC and Cloud Native Development with Kubernetes

The HPC community has historically developed its own specialized software stack including schedulers, filesystems, developer tools, container technologies tuned for performance and large-scale on-premises deployments. Read more…

Google Open Sources TensorFlow Version of MorphNet DL Tool

April 18, 2019

Designing optimum deep neural networks remains a non-trivial exercise. “Given the large search space of possible architectures, designing a network from scratch for your specific application can be prohibitively expens Read more…

By John Russell

A Beginner’s Guide to the ASC19 Finals

April 22, 2019

Three thousand watts. That's how much power the competitors in the 2019 ASC Student Supercomputer Challenge here in Dalian, China, have to work with. Everybody Read more…

By Alex Woodie

At ASF 2019: The Virtuous Circle of Big Data, AI and HPC

April 18, 2019

We've entered a new phase in IT -- in the world, really -- where the combination of big data, artificial intelligence, and high performance computing is pushing Read more…

By Alex Woodie with Doug Black and Tiffany Trader

Interview with 2019 Person to Watch Michela Taufer

April 18, 2019

Today, as part of our ongoing HPCwire People to Watch focus series, we are highlighting our interview with 2019 Person to Watch Michela Taufer. Michela -- the Read more…

By HPCwire Editorial Team

Intel Gold U-Series SKUs Reveal Single Socket Intentions

April 18, 2019

Intel plans to jump into the single socket market with a portion of its just announced Cascade Lake microprocessor line according to one media report. This isn Read more…

By John Russell

BSC Researchers Shrink Floating Point Formats to Accelerate Deep Neural Network Training

April 15, 2019

Sometimes calculating solutions as precisely as a computer can wastes more CPU resources than is necessary. A case in point is with deep learning. In early stag Read more…

By Ken Strandberg

Intel Extends FPGA Ecosystem with 10nm Agilex

April 11, 2019

The insatiable appetite for higher throughput and lower latency – particularly where edge analytics and AI, network functions, or for a range of datacenter ac Read more…

By Doug Black

Nvidia Doubles Down on Medical AI

April 9, 2019

Nvidia is collaborating with medical groups to push GPU-powered AI tools into clinical settings, including radiology and drug discovery. The GPU leader said Monday it will collaborate with the American College of Radiology (ACR) to provide clinicians with its Clara AI tool kit. The partnership would allow radiologists to leverage AI techniques for diagnostic imaging using their own clinical data. Read more…

By George Leopold

Digging into MLPerf Benchmark Suite to Inform AI Infrastructure Decisions

April 9, 2019

With machine learning and deep learning storming into the datacenter, the new challenge is optimizing infrastructure choices to support diverse ML and DL workfl Read more…

By John Russell

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

Why Nvidia Bought Mellanox: ‘Future Datacenters Will Be…Like High Performance Computers’

March 14, 2019

“Future datacenters of all kinds will be built like high performance computers,” said Nvidia CEO Jensen Huang during a phone briefing on Monday after Nvidia revealed scooping up the high performance networking company Mellanox for $6.9 billion. Read more…

By Tiffany Trader

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

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

It’s Official: Aurora on Track to Be First US Exascale Computer in 2021

March 18, 2019

The U.S. Department of Energy along with Intel and Cray confirmed today that an Intel/Cray supercomputer, "Aurora," capable of sustained performance of one exaf 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

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

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

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

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

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

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

Intel Launches Cascade Lake Xeons with Up to 56 Cores

April 2, 2019

At Intel's Data-Centric Innovation Day in San Francisco (April 2), the company unveiled its second-generation Xeon Scalable (Cascade Lake) family and debuted it Read more…

By Tiffany Trader

France to Deploy AI-Focused Supercomputer: Jean Zay

January 22, 2019

HPE announced today that it won the contract to build a supercomputer that will drive France’s AI and HPC efforts. The computer will be part of GENCI, the Fre Read more…

By Tiffany Trader

Oil and Gas Supercloud Clears Out Remaining Knights Landing Inventory: All 38,000 Wafers

March 13, 2019

The McCloud HPC service being built by Australia’s DownUnder GeoSolutions (DUG) outside Houston is set to become the largest oil and gas cloud in the world th Read more…

By Tiffany Trader

Intel Extends FPGA Ecosystem with 10nm Agilex

April 11, 2019

The insatiable appetite for higher throughput and lower latency – particularly where edge analytics and AI, network functions, or for a range of datacenter ac Read more…

By Doug Black

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

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