Trinity Wrestles with Knights Landing Programming Challenge with COE

By John Kirkley

July 5, 2016

Seventy-one years ago, on July 16, 1945, an incredible explosion lit up the New Mexico night sky. This was the Trinity Test, the world’s first nuclear detonation, and it marked the beginning of the Nuclear Age. It also ushered in the age of supercomputers, which essentially began with weapons science at Los Alamos National Laboratory (LANL).

Now a new Trinity, a next generation Cray XC supercomputer is about to take center stage to help the national security labs achieve their primary mission – to provide the nation with a safe, secure and effective nuclear deterrent. When Trinity is completely installed this year it is expected to be the fastest supercomputer in the U.S. and the second or third fastest in the world. The Trinity project is managed and operated by LANL and Sandia National Laboratories under the Alliance for Computing at Extreme Scale partnership.

Three of the people playing key roles—Manuel Vigil (LANL), the Trinity project co-director, Rob Hoekstra, manager of scalable architecture at Sandia, and LANL scientist Hai Ah Nam who is leading the project’s Center of Excellence (COE)—recently discussed some of the challenges in making Trinity a reality, including transitioning from their existing supercomputer, Cielo, which has been the labs front line system since 2013. With the introduction of the Intel Xeon Phi processor (Knights Landing) as part of the Trinity system, a major challenge for the applications community is transitioning codes to the new architecture.

The Cray installation team is preparing a row of 12 cabinets (out of 60 total) for connection to the water cooling infrastructure at Los Alamos National Laboratory. (Photo courtesy LANL)
The Cray installation team is preparing a row of 12 cabinets (out of 60 total) for connection to the water cooling infrastructure at Los Alamos National Laboratory. (Photo courtesy LANL)

We knew that with Knights Landing we were dealing with a completely new architecture – a new way of doing business – and we had to provide some help with code modification to move forward,” explained Vigil. “This means not only modernizing current codes, but also informing the new codes for applications that LLNL, Sandia and LANL will be building in the future. We have many million lines of code in our code base. So our primary challenge is the code transition to the new architecture, with the knowledge that a huge investment in time and energy will be required.

We have established a Center of Excellence (COE),” Vigil continued, “that consists of internal people – mostly software developers and scientists – along with representatives from Cray and Intel, the two primary vendors. Through the COE, Intel and Cray have been directly helping our teams to improve and modernize our codes to take full advantage of the architecture. The Trinity COE is only an initial investment for helping to transition a small number of codes. But the hope is that it will lay the groundwork and provide lessons learned for the rest of the massive amounts of code that need to be transitioned to work with new technologies.”

Right now we primarily rely on MPI (Message Passing Interface) for parallelism and scalability of our codes,” Hoekstra said. “We view the Trinity architecture, which is based on the new Knights Landing processors, as a real challenge to MPI. In fact, we have to move from MPI to on-node or shared memory models, along with threading and greater vectorization of the code.” The new architecture is a challenge to MPI because the team will have to learn how to do more threading and to better address vectorization.

Hoekstra continued, “Knights Landing features a two-tier high bandwidth memory that is actually in the same package as the processors instead of being on the board but outside the package. This results in a factor of 5 improvement in memory bandwidth performance that we want take advantage of – it has the potential to significantly accelerate parts of our code. But first we have to learn how we can best utilize this new hardware to the greatest advantage for our codes.”

Paul Peltz, LANL HPC Scalable Systems Engineer, slides one of the Knights Landing boards into one of the first Trinity supercomputer’s cabinets. (Photo courtesy LANL)
Paul Peltz, LANL HPC Scalable Systems Engineer, slides one of the Knights Landing boards into one of the first Trinity supercomputer’s cabinets. (Photo courtesy LANL)

“We are talking about millions of lines of code,” said Nam. “We expect our code transition efforts to take at least five years. One of the advantages of the COE is that we are able to start the process close to a year before the Trinity platform hits the floor.”

To gain understanding of the next-generation architecture of the system, each of the National Nuclear Security Administration (NNSA) labs selected codes that would help them get a handle on the challenges associated with memory, threading, vectorization and rewriting code.

“We realized that with the COE we could not address of all of the codes at Los Alamos, Sandia and LLNL,” Nam added. “What we are doing is initially targeting key codes at each of the labs to illustrate the process and gather lessons learned for other developers who will be involved now and in the future. The COE is used to demonstrate what can be accomplished and identify the biggest challenges that must be overcome.

“The other thing I’d like to emphasize is that the COE for Trinity is also working with the other national labs and their version of the Center targeting other systems. The idea is to address code modernization considering all future platforms – not just specifically for Trinity, because that would be a mistake.”

The COE for Trinity began gaining traction in May 2015. This included not only putting in place resources from Cray, Intel and the labs, but also initiating various kinds of collaborative code explorations such as Cray-led deep dives focused on large scale performance and Intel-led discovery sessions focused on on-node performance for both the Haswell and Intel Xeon Phi processors.

Vigil said they were also able to install some early versions of the Trinity type Intel Knights Landing processors (aka “White Boxes”) at each of the labs – Los Alamos, Lawrence Livermore, and Sandia National Labs, to help gain hands-on experience to learn how the high bandwidth memory and the high degree of parallelism would impact the codes and their performance.

“The major challenge associated with bringing a supercomputer on line is the unknown” Nam said. “You can speculate about what the processor is going to do, on what capabilities the memory will provide and the functionality, performance and stability of the software and platform ecosystem – but you don’t really know. So the COE is an on-going collaborative process where you are exploring the unknown with your vendor partners who have a lot of experience and have a better understanding of how their product is going to work. They don’t understand your exact use cases and other science requirements, so the COE enables us to expose our concerns and have a willing partner to address the issues.

“This joint exploration into the unknown early on is really important; we can get a jump on efficiently using the system over its lifetime. It’s really helpful to unravel the major problems early in the process.”

In addition to the discovery sessions, the COE also had a Dungeon session with Cray and Intel. For the Dungeon session they sent code team members to Intel where they spent a week of 11 to 12 hour days working closely with Intel tools, compiler and application experts and a representative from Cray. They spent time using and learning Intel’s tools and in turn Intel and Cray learned about the complexity in the multiphysics codes from the coding teams. This real time feedback from compiler, tools and performance experts provided opportunity to improve code efficiency and to try out early vendor hardware and software in order to identify issues early in vendor provided tools.

“Profiling tools can be complex in the wealth of features and output they provide in analyzing a code,” Nam noted. “The Intel analysis suite is both powerful and daunting. The Dungeon sessions bring the Intel experts to work closely with code developers in an intense multi-day working session to use the tools to identify bottlenecks through profiling and implement possible fixes.”

Nam continued, “We made progress in a really intense environment where we looked at the key issues in our code and explored how to improve its performance on Trinity’s advanced architecture, which is far more powerful than anything we have worked with before.

“This is an exciting time,” Nam concluded. “We realize we’re just not modernizing for Trinity, but also making strategic decisions to prepare for upcoming systems including future exascale machines.”

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, and this day of contemplation is meant to provide all of us Read more…

Intel Announces Hala Point – World’s Largest Neuromorphic System for Sustainable AI

April 22, 2024

As we find ourselves on the brink of a technological revolution, the need for efficient and sustainable computing solutions has never been more critical.  A computer system that can mimic the way humans process and s Read more…

Empowering High-Performance Computing for Artificial Intelligence

April 19, 2024

Artificial intelligence (AI) presents some of the most challenging demands in information technology, especially concerning computing power and data movement. As a result of these challenges, high-performance computing Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

2024 Winter Classic: Texas Two Step

April 18, 2024

Texas Tech University. Their middle name is ‘tech’, so it’s no surprise that they’ve been fielding not one, but two teams in the last three Winter Classic cluster competitions. Their teams, dubbed Matador and Red Read more…

2024 Winter Classic: The Return of Team Fayetteville

April 18, 2024

Hailing from Fayetteville, NC, Fayetteville State University stayed under the radar in their first Winter Classic competition in 2022. Solid students for sure, but not a lot of HPC experience. All good. They didn’t Read more…

AI Saves the Planet this Earth Day

April 22, 2024

Earth Day was originally conceived as a day of reflection. Our planet’s life-sustaining properties are unlike any other celestial body that we’ve observed, Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Leading Solution Providers

Contributors

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

Intel’s Xeon General Manager Talks about Server Chips 

January 2, 2024

Intel is talking data-center growth and is done digging graves for its dead enterprise products, including GPUs, storage, and networking products, which fell to Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire