List of Microsoft Azure High Performance Computing (HPC) Customers
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Since 2010, our global team of researchers has been studying Microsoft Azure High Performance Computing (HPC) customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Microsoft Azure High Performance Computing (HPC) for Cognitive Computing from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Microsoft Azure High Performance Computing (HPC) for Cognitive Computing include: BASF, a Germany based Life Sciences organisation with 111408 employees and revenues of $75.74 billion, Johnson Matthey, a United Kingdom based Oil, Gas and Chemicals organisation with 11685 employees and revenues of $16.71 billion, Pacific Northwest National Laboratory, a United States based Government organisation with 6400 employees and revenues of $1.64 billion, University of Bath, a United Kingdom based Education organisation with 3367 employees and revenues of $256.0 million and many others.
Contact us if you need a completed and verified list of companies using Microsoft Azure High Performance Computing (HPC), including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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BASF | Life Sciences | 111408 | $75.7B | Germany | Microsoft | Microsoft Azure High Performance Computing (HPC) | Cognitive Computing | 2023 | n/a |
In 2023 BASF implemented Microsoft Azure High Performance Computing (HPC) to accelerate materials and chemistry R&D in Germany, a deployment Microsoft lists as leveraging Azure Quantum Elements within a Cognitive Computing context. The engagement centers on applying cloud-scale compute to chemistry and materials simulation workloads, aligning BASF Microsoft Azure High Performance Computing (HPC) Cognitive Computing with laboratory and modelling functions in R&D.
The implementation uses Azure HPC to provision scalable compute capacity and orchestration for large simulation batches, while Azure Quantum Elements supplies AI-driven tooling for materials screening and validation. Functional capabilities inferred from the announcement include high-throughput screening workflows, simulation orchestration, and AI-assisted candidate ranking, aligning compute provisioning with model inference and validation pipelines.
Operational scope focuses on BASF’s materials and chemistry research groups in Germany, embedding Cognitive Computing into research workflows to prioritize experiments and accelerate candidate evaluation. Governance implications include shifting simulation scheduling and experiment prioritization into cloud-based pipelines and instituting model-driven screening processes for R&D decisioning, with the explicit objective of faster materials screening and simulation workflows as stated by Microsoft.
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Johnson Matthey | Oil, Gas and Chemicals | 11685 | $16.7B | United Kingdom | Microsoft | Microsoft Azure High Performance Computing (HPC) | Cognitive Computing | 2023 | n/a |
In 2023, Johnson Matthey deployed Microsoft Azure High Performance Computing (HPC) under the Cognitive Computing category to accelerate computational chemistry and materials R&D for hydrogen fuel cell catalysts in the United Kingdom. The initiative targeted high-throughput quantum chemistry workloads to shorten simulation timelines and increase experiment iteration velocity.
The implementation combined Microsoft Azure High Performance Computing (HPC) with Azure Quantum Elements to run quantum chemistry calculations at scale, using parallel compute clusters, workload orchestration, and quantum simulation tooling to handle large ensembles of molecular simulations. Configuration emphasis was on scalable batch processing and high-performance node allocation to reduce end-to-end simulation queuing and runtime for core computational chemistry pipelines.
Johnson Matthey partnered directly with Microsoft Azure Quantum as the platform provider to host and operate the workloads, with operational coverage centered on materials and computational chemistry teams within R&D focused on hydrogen fuel cell catalysts. The deployment was oriented around in-region cloud compute for research workloads and integration with existing R&D data pipelines and simulation inputs.
The announcement reports a two-fold acceleration in quantum chemistry calculations and a reduction in scaled workload turnaround from about six months to roughly a week, outcomes that materially shortened R&D cycles for catalyst discovery and testing.
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Pacific Northwest National Laboratory | Government | 6400 | $1.6B | United States | Microsoft | Microsoft Azure High Performance Computing (HPC) | Cognitive Computing | 2024 | n/a |
In 2024, Pacific Northwest National Laboratory implemented Microsoft Azure High Performance Computing (HPC) in collaboration with Microsoft to accelerate materials discovery for battery technology, under the Cognitive Computing category. The deployment used Azure Quantum Elements to combine AI-driven screening with Azure HPC compute for end-to-end candidate generation and validation across PNNL research projects in the United States.
The implementation integrated AI-accelerated screening pipelines with HPC validation workflows using Microsoft Azure High Performance Computing (HPC). Functional capabilities included high-throughput candidate scoring, model-driven down-selection, orchestration of large batch simulations, and physics-based validation runs on Azure HPC resources.
Integrations centered on Azure Quantum Elements' AI stack feeding prioritized shortlists into PNNL experimental workflows, enabling a computational to laboratory handoff. Operational coverage targeted materials discovery for battery electrolytes and linked computational chemistry models with materials science and synthesis teams within PNNL's US-based research operations.
Governance established iterative AI screening, human expert review, and rapid lab validation cycles to compress R&D timelines. The collaboration screened approximately 32.6 million candidate materials, narrowed them to a short list of high-potential electrolytes in days, and PNNL synthesized and validated the chosen candidate, demonstrating major R&D acceleration.
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Education | 3367 | $256M | United Kingdom | Microsoft | Microsoft Azure High Performance Computing (HPC) | Cognitive Computing | 2022 | n/a |
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