LRZ Adds Mega AI System as It Stacks up on Future Computing Systems

By Agam Shah

May 25, 2022

The battle among high-performance computing hubs to stack up on cutting-edge computers for quicker time to science is getting steamy as new chip technologies become mainstream.

A European supercomputing hub near Munich, called the Leibniz Supercomputing Centre, is deploying Cerebras Systems’ CS-2 AI system as part of an internal initiative called Future Computing to assess alternative computing technologies to inject more speed into the region’s scientific research.

“The idea exactly is to explore these new technologies and see how they would fit with the scientists’ needs and whatever they actually require to do their breakthrough research,” said Dieter Kranzlmüller, director of the supercomputing center, which is also known as Leibniz-Rechenzentrum, or LRZ.

LRZ is thinking less about HPC systems and AI systems, but more in “terms of the character realization of the workflows and the work to be done and what makes sense for the architectures,” said Laura Schulz, LRZ’s head of strategy. She added the CS-2 AI system will be part of wider supercomputing backbone that will be available to researchers in the Bavarian region.

“We’ve got multiple GPUs, we have FPGAs, we have a variety of CPUs, we have prototypes, engineering samples, a really nice assembly, and so we attempt to keep this moving forward,” Shulz said.

LRZ is one of three top supercomputing centers in Germany, with the others being Jülich Supercomputing Centre, which hosts the world’s eight-fastest supercomputer called JUWELS as rated by the Top500 list, and High-Performance Computing Center in Stuttgart, which hosts the 43rd ranked Hazel Hen supercomputer.

The CS-2’s Wafer Scale Engine 2 chip has 850,000 cores and 40GB of memory. The chip is the size of a wafer, and with 2.6 trillion transistors, it is considered the world’s largest chip. The CS-2 is being hooked up with HPE’s Superdome Flex, which can be characterized as staging hardware for CS-2 to perform faster calculations on complex data sets.

Large AI models require huge datasets, and the HPE server has a large shared memory compute which allows the system to very quickly handle pre- and post-processing tasks during the training process. This is enabled by a large number of I/O slots with high-bandwidth connectivity so there are no bottlenecks in data transfers to the CS-2.

An entire dataset can be kept in the Superdome Flex and served to the deep learning and training processes happening on the CS-2, which involves a lot of data movement, said Arti Garg, HPE’s chief strategist for AI.

“The HPE servers are solving a different problem. They are feeding the data into the CS-2. Large models require huge datasets. The datasets are processed and sent to the CS-2 by the HPE system,” said Andrew Feldman, CEO of Cerebras Systems, in an email exchange.

The HPE server simplifies the orchestration, and helps in convergence and accuracy when training AI models. The CS-2 has the ability to run multiple machine learning models simultaneously.

As data sets become larger, the conventional computing approaches to AI are taking longer to deliver results, and that’s where new types of accelerated systems like CS-2 fit in, said Andy Hock, vice president of product management at Cerebras Systems.

He gave an example of the natural language processing, with models growing so large that the compute requirements grew over 1,800 times in a span of two years. The BERT model had 110 million parameters in 2018, and the most recent GPT-3 – which is considered a spin-off of BERT – reached 175 billion parameters in 2020.

“We don’t see this trend waning. We’ve seen the introduction of larger models since then, in the trillion-parameter range, and expect in the near future, that state-of-the-art models may be in the multi-trillion parameter range,” Hock said.

The CS-2 cores are identical and fully programmable, and are optimized for the type of machine-learning compute operations that are common on both large-scale AI and HPC workloads.

Hock said the CS-2 can be thought of as a massive sparse linear algebra accelerator because each core is directly connected to its four nearest neighbors across the entire device via a high-bandwidth low-latency interconnect. The data flow traffic pattern between the cores is fully programmable at compile time.

The interconnect transfers data at 220 petabytes per second, and the WSE-2 retains parameters of neural networks on the chip as it is being executing, which speeds up computation. The hooks for the multi-billion parameter models are stored in the MemoryX technology that Cerebras announced last year, which handles neural networks with up to 120 trillion parameters.

Cerebras Systems weight streaming execution mode

“The technology allows us to hold the parameters off chip, but achieve the performance as if they were on chip. By disaggregating compute and memory, MemoryX enables researchers to run models 100 times larger than today’s largest models on a single CS-2,” Cerebras’ Feldman said.

Developers can use standard ML frameworks approaches like TensorFlow and PyTorch to program for the CS-2. The compiler intercepts the program at compile time and translates the program into an executable that can run on CS-2 devices.

Cerebras also has a lower-level software development kit targeted at HPC users for projects ranging from signal processing to physics-based modeling and simulation.

“We’re continuing to improve on this stack release, to bring more and more features to bear to increase the range of applications that the users can work on,” Hock said.

Related

Wafer Scale to ‘Brain-Scale’ – Cerebras Touts Linear Scaling up to 192 CS-2 Systems

PSC’s Neocortex Upgrades to Cerebras CS-2 AI Systems

Cerebras Doubles AI Performance with Second-Gen 7nm Wafer Scale Engine

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!

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

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from its predecessors, including the red-hot H100 and A100 GPUs. Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. While Nvidia may not spring to mind when thinking of the quant Read more…

2024 Winter Classic: Meet the HPE Mentors

March 18, 2024

The latest installment of the 2024 Winter Classic Studio Update Show features our interview with the HPE mentor team who introduced our student teams to the joys (and potential sorrows) of the HPL (LINPACK) and accompany Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the field was normalized for boys in 1969 when the Apollo 11 missi Read more…

Apple Buys DarwinAI Deepening its AI Push According to Report

March 14, 2024

Apple has purchased Canadian AI startup DarwinAI according to a Bloomberg report today. Apparently the deal was done early this year but still hasn’t been publicly announced according to the report. Apple is preparing Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimization algorithms to iteratively refine their parameters until Read more…

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

March 18, 2024

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

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimizat Read more…

PASQAL Issues Roadmap to 10,000 Qubits in 2026 and Fault Tolerance in 2028

March 13, 2024

Paris-based PASQAL, a developer of neutral atom-based quantum computers, yesterday issued a roadmap for delivering systems with 10,000 physical qubits in 2026 a Read more…

India Is an AI Powerhouse Waiting to Happen, but Challenges Await

March 12, 2024

The Indian government is pushing full speed ahead to make the country an attractive technology base, especially in the hot fields of AI and semiconductors, but Read more…

Charles Tahan Exits National Quantum Coordination Office

March 12, 2024

(March 1, 2024) My first official day at the White House Office of Science and Technology Policy (OSTP) was June 15, 2020, during the depths of the COVID-19 loc Read more…

AI Bias In the Spotlight On International Women’s Day

March 11, 2024

What impact does AI bias have on women and girls? What can people do to increase female participation in the AI field? These are some of the questions the tech Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. 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…

Analyst Panel Says Take the Quantum Computing Plunge Now…

November 27, 2023

Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y 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…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a 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…

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…

Leading Solution Providers

Contributors

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…

Training of 1-Trillion Parameter Scientific AI Begins

November 13, 2023

A US national lab has started training a massive AI brain that could ultimately become the must-have computing resource for scientific researchers. Argonne N 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…

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…

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…

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…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer 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…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire