Spring, 77389, TX,
United States
Hewlett Packard Enterprise
Hewlett Packard Enterprise, a prominent reseller, system integrator, and consulting company, that plays a vital role in numerous system integration and digital transformation initiatives. Hewlett Packard Enterprise collaboration with software players such as SAP, SUSE Group and NVIDIA empowers organizations to embrace disruptive technologies and accelerate their journey to the cloud, thus reshaping their business models.
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Product | Category | When | Insight |
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Consumer Packaged Goods | 4000 | $549M | Switzerland | SAP | SAP S/4 HANA | ERP Financial | 2016 |
In 2016, Oettinger Davidoff implemented SAP S/4 HANA as an ERP Financial solution to support a simplified strategy focused on mastering the value creation chain and greater consumer orientation. The Basel based, family run company initiated a program to standardise and centralise a significantly fragmented IT environment and to establish a single global process centre as the foundational operating model.
The SAP S/4 HANA implementation concentrated on core ERP Financial capabilities, configured to centralise financial accounting and controlling processes, enforce master data governance, and provide standardized transaction orchestration across business units. Configuration emphasized template driven process definitions and centralized ledgers in order to align financial workflows with the company strategy and global reporting needs.
Infrastructure for the SAP S/4 HANA rollout was built on two HPE ConvergedSystem 500 solutions for SAP HANA provided by Hewlett Packard Enterprise, with installation and configuration performed in partnership with IT integrator Bechtle Steffen. The architectural approach bundled an on premise SAP HANA platform with converged hardware to support a consolidated global instance and to enable consistent platform management across sites.
Operational scope covered more than 30 global business units and used the global process centre as the primary governance and operational hub, enabling centralized change control, standardized rollout sequencing, and shared process ownership across finance and adjacent value chain functions. The deployment narrative centers on standardisation of ERP systems, centralized process governance, and infrastructure convergence using SAP S/4 HANA as the ERP Financial backbone.
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Oil, Gas and Chemicals | 100000 | $195.6B | France | SUSE Group | SUSE Linux Enterprise High Performance Computing | Operating System (OS) | 2014 |
In 2014 TotalEnergies deployed SUSE Linux Enterprise High Performance Computing as the Operating System (OS) on its SGI-built Pangea supercomputer to support seismic modelling and reservoir simulation for oil and gas exploration in Europe. The implementation uses SUSE Linux Enterprise High Performance Computing as the core operating environment for parallel compute nodes and cluster orchestration, reflecting Operating System (OS) responsibilities for kernel tuning and node provisioning in HPC contexts.
Configuration work emphasized cluster-level management and performance tuning, with SUSE Linux Enterprise High Performance Computing configured to support resource scheduling integration, optimized networking stacks, and parallel file system compatibility typical of HPC deployments. These configuration choices were aligned to run compute-intensive seismic and reservoir simulation workloads, and to provide system-level stability for long-running batch jobs and MPI style parallel processing.
The deployment was delivered on SGI hardware with SGI named as the implementation partner, and Hewlett Packard Enterprise listed as the SI VAR associated with the project. Integration points centered on the SGI Pangea supercomputer hardware, workload orchestration and storage connectivity required by seismic modelling and reservoir simulation applications, and operational handoff to centralized HPC operations supporting subsurface and reservoir engineering teams across Europe.
Governance and rollout involved vendor collaboration between SUSE, SGI, and Hewlett Packard Enterprise during system commissioning and validation, with operational governance residing in TotalEnergies HPC operations to manage job scheduling and system maintenance. The project delivered roughly 10 times the compute capacity of the prior system, enabling a significantly larger simulation footprint for exploration workflows.
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Transportation | 640000 | $78.4B | United States | NVIDIA | NVIDIA Triton | Apps Development | 2019 |
In 2019, the United States Postal Service deployed NVIDIA Triton Inference Server as part of its Edge Computing Infrastructure Program. The deployment uses NVIDIA Triton in the Apps Development category to deliver edge inference for parcel tracking and image processing workflows across postal operations.
NVIDIA Triton Inference Server was configured to host and serve multiple computer vision models, including optical character recognition, barcode recovery, and item tracking, providing model inference, batching, and GPU accelerated serving at the edge. These functional capabilities align with Apps Development practices around model orchestration, low latency inference, and throughput management to support automated image processing.
The implementation was rolled out across approximately 195 processing centers in the United States on Hewlett Packard Enterprise provided NVIDIA certified edge servers, with each edge server processing roughly 20 TB of images per day. The operational scope focused on parcel tracking and image processing business functions, and the runtime design prioritized localized inference capacity to reduce upstream network transfer and latency.
Governance and rollout were managed under the Edge Computing Infrastructure Program, which standardized hardware specifications and operational controls while enabling consistent edge model hosting across sites. NVIDIA Triton served as the inference runtime in this architecture, and the program explicitly reported dramatically reduced manual package tracking time as an outcome of the deployment.
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