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A US supercomputer with 8,000 Intel Xeon CPUs and 300TB of RAM is being auctioned — 160th most powerful computer in the world has some maintenance issues though and will cost thousands per day to run

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The Cheyenne supercomputer, based at the NCAR-Wyoming Supercomputing Center (NWSC) in Cheyenne, Wyoming, was ranked as the 20th most powerful computer in the world in 2016 – but now it’s up for sale through the US General Services Administration (GSA).

By November 2023, the 5.34-petaflops system’s ranking had slipped to 160th in the world, but it’s still a monster, able to carry out 5.34 quadrillion calculations per second. It has been put to a number of noteworthy purposes in the past, including studying weather phenomena and predicting natural disasters.

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The Cheyenne Supercomputer is going for a fraction of its list price at auction right now

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If you’ve been thinking about picking up a new supercomputer but were waiting on a good price, now might be a good time to put in your bid. Right now, the US government, via GSA Auctions, is auctioning off the Cheyenne Supercomputer to the highest bidder with three days remaining. While we haven’t tested this one ourselves, we assume its 145,152 CPU cores will easily out-perform our current top pick for a laptop. You also won’t need to upgrade the memory anytime soon, as there’s a full 313,344GB of RAM currently installed, and the storage capacity tallies up to around 36 petabytes. No need to delete files to make room for new games or other media downloads.

GSA Auctions

Grab one of the world’s most powerful supercomputers for far below list price during the US Government auction. 

$28,000 at GSA Auctions

The deal was spotted by Ars Technica, who also point out that the fiber optic and CAT5/6 cabling are not included in the sale. While the price the government paid for the supercomputer has not been disclosed, it’s safe to assume the cost was well into the millions, considering the price tags of other supercomputers. As of this writing, the bidding has reached $28,085, though the reserve has not yet been met. There are still three days to go and there’s currently no deposit required to place a bid.

The reason for such a hefty discount (other than the fact that Cheyenne has been decommissioned) could be faulty quick disconnects causing water spray and the fact that approximately one percent of nodes have “experienced failure” and “will remain unrepaired.” One other caveat to note before you start making room in your arena-sized climate-controlled garage is that shipping is not included. As GSA Auctions notes on the details page, “moving this system necessitates the engagement of a professional moving company” and that “the purchaser assumes responsibility for transferring the racks from the facility onto trucks.”

But where else will you find such steep savings on a machine that can carry out 5.34 quadrillion calculations per second? Cheyenne is also surprisingly energy-efficient, consuming 25 percent less energy per computation than its predecessor, Yellowstone. The massive supercomputer helped researchers understand the rapid intensification of hurricanes, how wildfires impact air quality, and simulated years of climate functions to predict outcomes decades in advance. It should definitely provide you with enough processing power for extreme multitasking at work while handling even the most demanding games after hours.

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Lenovo unveils first all-AMD AI ‘supercomputer’ flanked with up to 1.5TB of HBM memory and promises drop-in support for the future AMD EPYC CPU — new ThinkSystem has dual EPYC CPUs and 8 Instinct MI300X GPUs

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Lenovo has taken the wraps off its ThinkSystem SR685a V3 server, which it says is an optimal solution for both enterprise private on-prem AI as well as for public AI cloud service providers.

Crafted in tandem with AMD, the server has been specifically engineered to handle the demanding compute needs associated with GenAI and Large Language Models. With fast acceleration, large memory capacity and I/O bandwidth, the new powerhouse can manage sizable data sets used in industries from healthcare and energy to financial services and climate science.

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Want to see what an Exaflop supercomputer looks like (and how it is cooled)? Check out this video of Aurora, the world’s second most powerful HPC ever

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Few people will ever get to see inside a supercomputer for real, but it is possible to take a virtual tour. Nvidia previously opened the doors to Eos, one of the world’s fastest supercomputers, and now Department of Energy’s Argon National Laboratory has prepared a short 5-minute video guiding viewers through Aurora, its exascale supercomputer.

Aurora is already one of the fastest supercomputers in the world. HPC Wire ranked it number #2 in its top 500 list in November 2023. But that ranking was achieved with just “half of Aurora running the HPL benchmark”.

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Intel, NVIDIA Supercomputer Centers double AI processing power

Intel, NVIDIA & Ohio Supercomputer Center double AI processing power

The Ohio Supercomputer Center (OSC) has recently unveiled a new high-performance computing (HPC) cluster named Cardinal, which is poised to significantly enhance AI processing power for artificial intelligence (AI) research and education. Developed in partnership with industry giants Intel, Dell Technologies, and Nvidia, Cardinal represents a major step forward in the computational resources available to researchers and educators in Ohio.

Cardinal’s introduction is a response to the growing need for advanced computing power in AI, which spans a variety of fields such as scientific research, engineering, and biomedical studies. The new system is set to more than double the processing power and capacity of OSC’s previous system, the Owens Cluster, which has been operational since 2016.

  • 756 Max Series CPU 9470 processors, which will provide 39,312 total CPU cores.
  • 128 gigabytes (GB) HBM2e and 512 GB of DDR5 memory per node.

New HPC Cluster

The heart of Cardinal boasts 756 Intel Xeon CPU Max Series 9470 processors, which together provide a staggering 39,312 CPU cores. This formidable processing capability is further enhanced by each node’s 128 GB of cutting-edge HBM2E memory and 512 GB of DDR5 memory, ensuring that even the most demanding HPC and AI tasks are handled with efficiency.

The backbone of the Cardinal cluster is formed by Dell PowerEdge servers, which are known for their high performance and reliability. The system’s architecture has been carefully optimized to manage workloads effectively, which is essential for the successful integration of AI into research and industry.

Cardinal’s software environment is designed with user-friendliness in mind, supporting traditional x86 programming models to facilitate easy adoption. The cluster includes thirty-two nodes that are equipped with Nvidia H100 Tensor Core GPUs, each with 1 TB of memory and 400 Gbps NVIDIA Quantum-2 InfiniBand networking, enabling exceptionally fast data transfer speeds. Additionally, sixteen nodes are specifically designed for large symmetric multiprocessing (SMP) jobs, featuring 104 cores and 2 TB of DDR5 memory each.

The strategic choice of Intel’s Xeon CPU Max Series processors ensures that Cardinal is compatible with popular AI frameworks and libraries, allowing users to leverage the latest technology to advance their AI research without significant alterations to their existing workflows.

With the launch of the Cardinal HPC cluster, Intel, Dell, Nvidia, and the OSC demonstrate their commitment to advancing the frontiers of research and education. Cardinal’s state-of-the-art hardware and software capabilities position it to support a broader range of use cases and foster innovation across various industries by enhancing AI capabilities. Here are some other articles you may find of interest on the subject of supercomputers.

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65 ExaFLOP AI Supercomputer being built by AWS and NVIDIA

65 ExaFLOP AI Supercomputer being built by AWS and NVIDIA

As the artificial intelligence explosion continues the demand for more advanced artificial intelligence (AI) infrastructure continues to grow. In response to this need, Amazon Web Services (AWS) and NVIDIA have expanded their strategic collaboration to provide enhanced AI infrastructure and services by building a new powerful AI Supercomputer capable of providing 65 ExaFLOPs  of processing power.

This partnership aims to integrate the latest technologies from both companies to drive AI innovation to new heights. One of the key aspects of this collaboration is AWS becoming the first cloud provider to offer NVIDIA GH200 Grace Hopper Superchips. These superchips come equipped with multi-node NVLink technology, a significant step forward in AI computing. The GH200 Grace Hopper Superchips present up to 20 TB of shared memory, a feature that can power terabyte-scale workloads, a capability that was previously unattainable in the cloud.

New AI Supercomputer under construction

In addition to hardware advancements, the partnership extends to cloud services. NVIDIA and AWS are set to host NVIDIA DGX Cloud, NVIDIA’s AI-training-as-a-service platform, on AWS. This service will feature the GH200 NVL32, providing developers with the largest shared memory in a single instance. This collaboration will allow developers to access multi-node supercomputing for training complex AI models swiftly, thereby streamlining the AI development process.

65 ExaFLOP of processing power

The partnership between AWS and NVIDIA also extends to the ambitious Project Ceiba. This project aims to design the world’s fastest GPU-powered AI supercomputer. AWS will host this supercomputer, which will primarily serve NVIDIA’s research and development team. The integration of the Project Ceiba supercomputer with AWS services will provide NVIDIA with a comprehensive set of AWS capabilities for research and development, potentially leading to significant advancements in AI technology. Here are some other articles you may find of interest on the subject of AI supercomputers :

Summary of collaboration

  • AWS will be the first cloud provider to bring NVIDIA GH200 Grace Hopper Superchips with new multi-node NVLink technology to the cloud. The NVIDIA GH200 NVL32 multi-node platform connects 32 Grace Hopper Superchips with NVIDIA NVLink and NVSwitch technologies into one instance. The platform will be available on Amazon Elastic Compute Cloud (Amazon EC2) instances connected with Amazon’s powerful networking (EFA), supported by advanced virtualization (AWS Nitro System), and hyper-scale clustering (Amazon EC2 UltraClusters), enabling joint customers to scale to thousands of GH200 Superchips.
  • NVIDIA and AWS will collaborate to host NVIDIA DGX Cloud—NVIDIA’s AI-training-as-a-service—on AWS. It will be the first DGX Cloud featuring GH200 NVL32, providing developers the largest shared memory in a single instance. DGX Cloud on AWS will accelerate training of cutting-edge generative AI and large language models that can reach beyond 1 trillion parameters.
  • NVIDIA and AWS are partnering on Project Ceiba to design the world’s fastest GPU-powered AI supercomputer—an at-scale system with GH200 NVL32 and Amazon EFA interconnect hosted by AWS for NVIDIA’s own research and development team. This first-of-its-kind supercomputer—featuring 16,384 NVIDIA GH200 Superchips and capable of processing 65 exaflops of AI—will be used by NVIDIA to propel its next wave of generative AI innovation.
  • AWS will introduce three additional new Amazon EC2 instances: P5e instances, powered by NVIDIA H200 Tensor Core GPUs, for large-scale and cutting-edge generative AI and HPC workloads, and G6 and G6e instances, powered by NVIDIA L4 GPUs and NVIDIA L40S GPUs, respectively, for a wide set of applications such as AI fine-tuning, inference, graphics and video workloads. G6e instances are particularly suitable for developing 3D workflows, digital twins and other applications using NVIDIA Omniverse, a platform for connecting and building generative AI-enabled 3D applications.
  • “AWS and NVIDIA have collaborated for more than 13 years, beginning with the world’s first GPU cloud instance. Today, we offer the widest range of NVIDIA GPU solutions for workloads including graphics, gaming, high performance computing, machine learning, and now, generative AI,” said Adam Selipsky, CEO at AWS. “We continue to innovate with NVIDIA to make AWS the best place to run GPUs, combining next-gen NVIDIA Grace Hopper Superchips with AWS’s EFA powerful networking, EC2 UltraClusters’ hyper-scale clustering, and Nitro’s advanced virtualization capabilities.”

Amazon NVIDIA partner

To further bolster its AI offerings, AWS is set to introduce three new Amazon EC2 instances powered by NVIDIA GPUs. These include the P5e instances, powered by NVIDIA H200 Tensor Core GPUs, and the G6 and G6e instances, powered by NVIDIA L4 GPUs and NVIDIA L40S GPUs, respectively. These new instances will enable customers to build, train, and deploy their cutting-edge models on AWS, thereby expanding the possibilities for AI development.

AWS NVIDIA DGX Cloud hosting

Furthermore, AWS will host the NVIDIA DGX Cloud powered by the GH200 NVL32 NVLink infrastructure. This service will provide enterprises with fast access to multi-node supercomputing capabilities, enabling them to train complex AI models efficiently.

To boost generative AI development, NVIDIA has announced software on AWS, including the NVIDIA NeMo Retriever microservice and NVIDIA BioNeMo. These tools will provide developers with the resources they need to explore new frontiers in AI development.

The expanded collaboration between AWS and NVIDIA represents a significant step forward in AI innovation. By integrating their respective technologies, these companies are set to provide advanced infrastructure, software, and services for generative AI innovations. The partnership will not only enhance the capabilities of AI developers but also pave the way for new advancements in AI technology. As the collaboration continues to evolve, the possibilities for AI development could reach unprecedented levels.

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University of Cambridge Dawn Phase 1 Supercomputer powers-up

Intel Dell Technologies and University of Cambridge Dawn Supercomputer

In a major milestone for the UK’s technological capabilities, Dell Technologies, Intel, and the University of Cambridge have announced the deployment of the Dawn Phase 1 supercomputer, currently the fastest AI supercomputer in the country. This groundbreaking machine, designed to combine artificial intelligence (AI) and high-performance computing (HPC), is expected to address global challenges and bolster the UK’s position as a technology leader.

Dawn Phase 1 is more than just a supercomputer; it’s a crucial component of the recently launched UK AI Research Resource (AIRR). The AIRR is a national facility designed to investigate the feasibility of AI-related systems and architectures, and Dawn Phase 1 will play a pivotal role in this exploration. The deployment of this supercomputer not only represents a significant technological achievement but also brings the UK closer to the exascale computing threshold, equivalent to a quintillion floating point operations per second.

The supercomputer is currently operational at the Cambridge Open Zettascale Lab, where it utilises Dell PowerEdge XE9640 servers and the Intel Data Center GPU Max Series accelerator. This state-of-the-art technology, combined with the supercomputer’s liquid cooling system, makes it uniquely suited for handling AI and HPC workloads.

The deployment of Dawn Phase 1 is the result of a strategic co-design partnership between Dell Technologies, Intel, the University of Cambridge, and UK Research and Innovation. This collaboration is a testament to the importance of partnerships and investments in technology for the UK’s AI growth potential. It’s a clear demonstration of how innovative collaborations can lead to technological breakthroughs.

One of the most exciting aspects of Dawn Phase 1 is its potential applications across a wide range of sectors. The supercomputer is poised to support large workloads in academic research and industrial domains, including healthcare, engineering, green fusion energy, climate modelling, and frontier science. This broad application potential underscores the transformative power of AI and HPC when harnessed effectively.

Looking ahead, a Phase 2 supercomputer, expected to deliver ten times the performance of Dawn Phase 1, is planned for 2024. This next phase of development will further strengthen the UK’s technological capabilities and its position as a global leader in AI and HPC.

Other articles you may find of interest on the subject of supercomputers :

In addition to the upcoming Phase 2, the integration of Dawn Phase 1 and the Isambard AI supercomputer will form the AIRR. This integration will create a national facility designed to help researchers maximise the potential of AI, further enhancing the UK’s AI research capabilities.

The construction of Dawn Phase 1 is based on Dell PowerEdge XE9640 servers with liquid cooling technology. Each server combines two 4th Gen Intel Xeon Scalable processors and four Intel Data Center GPU Max accelerators. This powerful combination of hardware is complemented by an AI- and simulation-optimised cloud supercomputing software environment provided by Scientific OpenStack from UK SME StackHPC.

While the technical details and performance numbers for Dawn Phase 1 will be released in mid-November at the Supercomputing 23 (SC23) conference in Denver, Colorado, it’s clear that this supercomputer represents a significant leap forward for the UK’s AI capabilities. By harnessing the power of AI and HPC, Dawn Phase 1 has the potential to drive transformative change across a range of sectors and place the UK at the forefront of global technological innovation.

Dawn Phase 1 Supercomputer 2023

The Dawn Supercomputer at the University of Cambridge is distinct from the one at Lawrence Livermore National Laboratory. This particular Dawn Supercomputer is a part of the Cambridge Service for Data Driven Discovery (CSD3), a state-of-the-art data analytics supercomputing facility. It caters to a wide range of computational and data-intensive research across various disciplines.

CSD3 is notable for its focus on supporting research that requires handling and analysis of large datasets, high-performance computing (HPC), and machine learning. The facility is designed to be highly flexible and scalable, meeting the needs of different research communities. It’s a collaborative project, involving not just the University of Cambridge but also partners from the wider research community.

The Dawn Supercomputer specifically, within this context, is known for its high-performance capabilities, particularly suited for tasks involving data analytics, artificial intelligence, and machine learning. Its architecture, combining traditional CPU-based computing with more recent GPU-based approaches, makes it well-suited for a variety of computational tasks. This includes scientific simulations, data processing, and the training of complex machine learning models.

The integration of the Dawn Supercomputer into CSD3 represents the University of Cambridge’s commitment to advancing research in data-intensive fields. It provides researchers with the necessary computational tools to tackle some of the most challenging and important questions in science and technology today.

A previous supercomputer also called Dawn was a high-performance computing system hosted at the Lawrence Livermore National Laboratory (LLNL) in the United States. It served as a precursor and testing platform for the more advanced Sequoia supercomputer, part of the IBM Blue Gene series of supercomputers. Dawn was operational in the late 2000s and early 2010s.

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