HP Enterprise introduces two new supercomputers to power AI, ML enterprise tasks

Hewlett Packard Enterprise (HPE), on Wednesday, announced two new supercomputer lineups for enterprises to use in their data centre operations. The supercomputers are aimed at large enterprises, which require vast computing power to process data for real-time analytics using artificial intelligence (AI), machine learning (ML) and associated technologies. The first of the new lineup, powered by US chipmaker AMD’s ‘Epyc’ range of processors, will be available starting December 5, and will target markets such as real-time automotive safety, sustainability research and development (R&D), drug research in pharmaceuticals, and real-time decision-making in the financial sector. 

The company’s ‘Cray’ lineup of enterprise supercomputers will seek to rival offerings from IBM, Nvidia and Dell, among others, to offer supercomputing power to enterprise data centres. 

Multiple industry reports have cited increasing demand for supercomputers among enterprises globally. According to a September report from US-based AI and computing sector market researcher ReportLinker, the global enterprise supercomputer market is tipped to be valued at above $21 billion by FY26 — growing at a rate of 19.1% annually from March this year. 

HPE’s latest offerings, under its ‘Cray EX’ and ‘Cray XD’ lineups, will likely aim to capture a share of this growth pace. Alongside the enterprise hardware, the company also unveiled a software platform to help enterprises train proprietary machine learning algorithms depending on their sector’s requirements. Called the Machine Learning Development Environment, HPE claims that the software platform will be able to reduce the training time required for such ML algorithms down to “days”. 

HPE’s new supercomputer offerings are compatible with both Intel’s Xeon and AMD’s Epyc range of processors. 

Trish Damkroger, chief product officer for high-performance computing, AI and labs at HPE, said that the company’s latest products are in line with “a new frontier with the exascale era, which is represented by massive data growth that requires advanced modeling, simulation, analytics, and AI-at-scale capabilities to realise outcomes and accelerate innovation.”