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govindhtech · 1 year ago

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Azure high performance computing enhances Surface products

Azure HPC

For HPC applications, Azure high performance computing (HPC) offers a full range of networking, storage, and processing capabilities along with workload orchestration services. In comparison to on-premises alternatives, Azure delivers comparable price/performance thanks to its purpose-built HPC infrastructure, solutions, and optimized application services. provides further advantages for high-performance computing. Azure also comes with state-of-the-art machine-learning algorithms to facilitate more intelligent decision making and intelligent simulations.

Cost-controlled performance that is optimized

Utilise every bit of your CPU, GPU, FPGA, and fast connection capacity to cut down on the time it takes to complete tasks from days to minutes.

Platform of production calibre

Azure is the cloud that simply works, with strong HPC stability, data security, and worldwide regulatory compliance.

Complete workflow flexibility

Create and maintain HPC clusters for your own personal usage alone, allowing cloud-based end-to-end application lifecycle management.

Including intelligence

With integrated DevOps, autoscaling cloud computing, and automated machine learning, you can create and train new AI models more quickly.

Examine Azure high performance computing options according to industry and application

Azure high performance computing can help developers, engineers, scientists, and researchers achieve new heights in their domains.

Automobile

With a highly secure infrastructure, it is possible to simulate every facet of vehicle engineering at a reasonable cost and scale.

Banking operations

Meet regulatory obligations with assurance thanks to a sophisticated and adaptable risk modelling infrastructure. As required, increase your capacity, and only pay for what you really need.

Vitality

Optimise the exploration, appraisal, completion, and production phases of the upstream oil and gas sector.

Life sciences and health

With an almost limitless high-performance bioinformatics infrastructure, you can accelerate discoveries in genomes, precision medicine, and clinical studies.

Silicon

High-performance, scalable, safe, and available infrastructure that is optimised for electrical design automation (EDA) workloads in terms of networking, computation, and storage.

Producing

Utilise scalable and highly secure on-demand HPC infrastructure to quickly iterate product design in order to shorten time to market and enhance product quality.

Applications

Machine learning

With Azure-powered advanced analytics, machine learning, and artificial intelligence workloads, you may operate clusters at almost limitless scalability, get strong remote workstations, and improve your insights.

Display

With Azure’s more than 50 global datacenter locations, you can run any graphic-intensive job in the cloud and provide amazing experiences to any device, anywhere, at any time.

Creating

Using a scalable, non-competing, MPAA-certified platform that is trusted by 95% of the Fortune 500, render with confidence.

Platform Services for HPC

With a cloud platform designed for global reach and equipped with services tailored to HPC applications, you may access enormous computational resources.

Interaction

With Azure ExpressRoute, create secure, private tunnels for hybrid cloud communication. Use InfiniBand to leverage Linux remote direct memory access (RDMA) for message passing interface (MPI) applications in your datacenter.

Services for Applications

Using Azure Batch, create, manage, and schedule tasks. Use Azure CycleCloud to dynamically deploy Azure high performance computing clusters.

Calculate

On Azure, find the ideal high-performance computing resources at an almost limitless scale. For applications requiring a lot of memory, use H-series virtual machines; for applications requiring graphics and CUDA/OpenCL, use N-series virtual machines; and for a fully managed supercomputer, use Cray.

Sensible Services

Utilising Data Lake Analytics, create predictive analysis-based apps for the next generation of users. Utilise your HPC data to create and execute machine learning models to get insights that help you make smarter choices.

Keepsake

Use data from on-site NAS devices equipped with HPC Cache to launch your HPC apps on Azure. Azure NetApp Files, provided as an Azure service directly inside an Azure datacenter, provide access to massive volumes of I/O with a sub-millisecond latency. Use Cray ClusterSor, a bare-metal, Lustre-based HPC storage system that is completely connected with Azure, for high throughput storage.Image credit to Azure

The mission of the Microsoft Surface organization is to provide renowned end-to-end experiences in hardware, software, and services that consumers adore using on a daily basis. Microsoft think that individuals who create a product represent that person, and that talented and passionate engineers and designers can create unique things when supported by the correct infrastructure and tools. Daily decisions on product features, dependability, and design are often made using simulation models at the product level.

The company is also embarking on a multi-year plan to produce unique items with exceptional efficiency. Microsoft Azure high performance computing is essential to making this goal possible. This is a description of how they used Azure high performance computing and simulation to do more with less.Image credit to Azure

Product development: laptop Surface

Azure high performance computing’s accessibility for Abaqus-based structural simulations contributed to its status as the main tool for product design development. Detailed translations of design ideas from digital computer-aided design (CAD) systems are made into FEA models.

These comprise all of the device’s primary subsystems and are actual digital prototypes. The analyst may assess viability by applying various test and reliability conditions in a virtual environment using FEA models. Hundreds of simulations are run over the course of a few days in order to assess different design concepts and methods for strengthening the device. The chosen design is then turned into a prototype and put through extensive testing to ensure it can withstand real-world circumstances. Azure’s engineering method includes many feedback loops for comparing FEA findings with real testing to validate the model.

The dynamic simulation’s starting condition is the impact velocity for a certain height. Using the Abaqus solver, the dynamic drop simulation is run on hundreds of cores of an Azure high performance computing cluster. Azure is used the Explicit and Abaqus solver, which is renowned for providing a reliable and accurate solution for fast-moving, nonlinear dynamic events like automobile crashworthiness and consumer electronics drop testing.

These solvers allow scalability to thousands of cores for high throughputs and are specifically tuned for Azure high performance computing clusters. On these optimized Azure HPC machines, simulation workloads finish in a few hours as opposed to the days they used to take. The analysts evaluate the data and compare the stress levels to the material limitations. After reviewing the findings, analysts and design teams change the designs. Because the Azure HPC servers allow very short turnaround times for evaluations, this cycle keeps repeating in rapid cycles.

The impact-induced motion and stress levels of the hinge’s interior components could be seen by the team thanks to the simulation. Azure was able to identify the primary problem and implement the necessary design changes as a result. This realization aided in the hinge assembly’s development to reduce stress levels. Since success required just one iteration, a significant amount of time was saved in the design process. Costs for testing, physical prototyping, and tooling were also reduced.

Currently, digital prototypes (FEA models) running on Azure high performance computing clusters are used to validate designs across the whole Microsoft Surface product range. In only a few weeks, thousands of simulation projects are regularly completed to allow state-of-the-art designs with very high dependability and customer satisfaction.

Next up

The group is now concentrating on implementing more scalable simulation and Azure HPC resources for multiphysics modelling and interdisciplinary collaborations. Enabling AI and machine learning for the purpose of creating new products is a big potential. The utilization of Azure HPC and the collaborations across Microsoft entities will be used to propel extensive advancements at a quick pace. Alongside the V4 Institute, Azure is advancing this digital transformation journey by using model-based systems engineering (MBSE). Working with Azure will be very beneficial for top-tier companies trying to scale digital simulations and accomplish more with fewer resources.