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Hewlett Packard (HPE) to Build Hunter & Herder Supercomputers

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Hewlett Packard Enterprise (HPE - Free Report) has struck a deal with the University of Stuttgart to build two supercomputers, namely Hunter and Herder, for the university’s High-Performance Computing Center. HPE will assist the center in moving toward exascale computing.

The first supercomputer, Hunter, will begin operating by 2025, taking the place of the university’s present supercomputer, Hawk. This primary ramp-up will take the users a step toward a Herder, an exascale system that will provide a significant expansion of Germany’s high-performance computing capabilities. Herder will be installed by 2027.

Hunter will be built on HPE Cray EX4000 supercomputer design, with the latest Cray ClusterStor storage system, HPE Cray Programming Environment and four HPE Slingshot interconnects in each of its 136 nodes. Hunter will feature an AMD Instinct MI300A accelerated processing unit that, along with its other specifications, will help it reach the peak performance of 39 petaFLOPS. However, Hunter is only the transitional computer to the Herder that will be able to reach up to the speeds of around one quintillion FLOPS.

Funded by the Gauss Centre for Supercomputing, the German Federal Ministry of Education and Research and the State of Baden-Württemberg's Ministry of Science, Research and Arts, the Supercomputers will be used in research areas like engineering, applied sciences, climate change, public administration and other essential business cases.

The German Supercomputer contract that HPE has received now follows two other contracts from the UK and France this year. In November 2023, the UK Government invested £225 million in a national AI Research Resource with the University of Bristol to build the UK's fastest supercomputer. Before that, in October 2023, Hewlett Packard Enterprise delivered an AI supercomputer for France-based CRIANN to fast-track scientific research.

Besides its Supercomputing clientele, HPE is making strides in its Cloud segment with HPE GreenLake. This year has also witnessed the adoption of GreenLake by notable organizations such as Inedys, Fastweb (an Italian Telecom Operator), Istanbul Water and Sewerage Administration, Dubai Islamic Bank, Wihuri Group, Ashok Leyland, DSolution (a Swedish service provider) and Toppan Forms.

Zacks Rank and Stocks to Consider

HPE International currently carries a Zacks Rank #3 (Hold). Shares of the company have climbed 5.9% year to date.

Some better-ranked stocks from the broader technology sector are MongoDB (MDB - Free Report) , Datadog (DDOG - Free Report) and Gitlab (GTLB - Free Report) , each carrying Zacks Rank #2 (Buy) at present. You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.

The Zacks Consensus Estimate for MongoDB's fourth-quarter 2024 earnings has been revised upward by 10 cents to 46 cents per share in the past 30 days. For fiscal 2024, earnings estimates have been revised by 56 cents northward to $2.90 per share in the past 30 days.

MDB’s earnings beat the Zacks Consensus Estimate in each of the preceding four quarters, the average surprise being 277.91%. MDB shares have climbed 108.3% year to date.

The Zacks Consensus Estimate for Datadog's fourth-quarter 2023 earnings climbed upward by 9 cents to 43 cents in the past 60 days. For fiscal 2023, DDOG’s earnings estimates have been revised 2 cents northward to 1.53 cents per share in the past 30 days.

Datadog’s earnings beat the Zacks Consensus Estimate in each of the trailing four quarters, the average surprise being 28.61%. DDOG shares have risen 67.4% year to date.

The Zacks Consensus Estimate for Gitlab’s fourth-quarter fiscal 2024 earnings has been revised northward by 9 cents to 8 cents per share in the past 30 days. For fiscal 2024, earnings estimates have been revised upward by 20 cents to 13 cents per share in the past 30 days.

Gitlab’s earnings beat the Zacks Consensus Estimate in each of the trailing four quarters, the average surprise being 317.62%. GTLB shares have climbed 40.2% year to date.

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