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Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Michelin, an e2open customer evaluated Oracle Transportation Management

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

List of Microsoft Azure High Performance Computing (HPC) Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
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.
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.
Pacific Northwest National Laboratory (PNNL) Government 6400 $2.3B 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.
University of Bath Education 3367 $256M United Kingdom Microsoft Microsoft Azure High Performance Computing (HPC) Cognitive Computing 2022 n/a
In 2022 University of Bath implemented Microsoft Azure High Performance Computing (HPC) in the Cognitive Computing category to establish Janus, a cloud-native supercomputing environment supporting chemistry, mathematics, engineering, physics and interdisciplinary research. The deployment is positioned as a phase one environment to build an Azure user base for research and teaching, and it complements Anatra, the university's single on-premises high-throughput computing cluster that is scheduled for decommissioning in a later phase. The initiative aligns University of Bath Microsoft Azure High Performance Computing (HPC) Cognitive Computing with academic research workflows and student curricula while underpinning a planned five year shift toward an almost fully cloud-based estate. The technical implementation uses a mix of 21 virtual machine instances including Azure Spot Virtual Machines, HB, HBv2, HBv3, and HC-series compute nodes alongside Fsv2, NCsv3, and NDv2 families to match workload profiles. Azure CycleCloud is used to automate, configure, and manage the Janus environment, while Azure NetApp Files, Azure Blob Storage, and Azure Disk Storage provide a tiered storage architecture with hot, warm, and temporary scratch options. Storage lifecycle management is an explicit operational objective, with University of Bath architects planning automation to move data between cheaper and more performant tiers to optimize cost and throughput for research datasets. Operational coverage spans faculty researchers and students across multiple departments, and several taught courses including scientific computing in mathematics and parallel computing in computer science have been migrated to the cloud. Janus supports common HPC workloads such as computational fluid dynamics, and the university ran an HPC cloud service pilot in 2020 supported by implementation partner Red Oak Consulting to validate cloud performance for these workloads. The environment is designed to let researchers provision clusters in hours and to supply a broad set of compute options tailored to specific experiments. Governance and rollout follow a staged, user adoption driven model, with the Janus phase one focused on building researcher confidence and funding models for cloud usage. University of Bath reports operational benefits such as faster turnaround and improved data safeguards, and cites that some workloads that would have taken years on local infrastructure can now be completed in months. The implementation narrative ties University of Bath Microsoft Azure High Performance Computing (HPC) Cognitive Computing directly to research capacity, teaching modernization, and a longer term program to rethink interactions among systems, applications, and data.
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FAQ - APPS RUN THE WORLD Microsoft Azure High Performance Computing (HPC) Coverage

Microsoft Azure High Performance Computing (HPC) is a Cognitive Computing solution from Microsoft.

Companies worldwide use Microsoft Azure High Performance Computing (HPC), from small firms to large enterprises across 21+ industries.

Organizations such as BASF, Johnson Matthey, Pacific Northwest National Laboratory (PNNL) and University of Bath are recorded users of Microsoft Azure High Performance Computing (HPC) for Cognitive Computing.

Companies using Microsoft Azure High Performance Computing (HPC) are most concentrated in Life Sciences, Oil, Gas and Chemicals and Government, with adoption spanning over 21 industries.

Companies using Microsoft Azure High Performance Computing (HPC) are most concentrated in Germany, United Kingdom and United States, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Microsoft Azure High Performance Computing (HPC) across Americas, EMEA, and APAC.

Companies using Microsoft Azure High Performance Computing (HPC) range from small businesses with 0-100 employees - 0%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 50%, and global enterprises with 10,000+ employees - 50%.

Customers of Microsoft Azure High Performance Computing (HPC) include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified Microsoft Azure High Performance Computing (HPC) customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Cognitive Computing.