Technologies like IoT, AI, and 3-D imaging are evolving with time and the amount of data produced by them is growing exponentially. For several reasons such as tracking a developing storm, testing new products, streaming a live sporting event, or analyzing stock trends, real-time data processing has become crucial.
We now live in a world where most organizations have adopted cloud platforms to process business data. Azure HPC has become the de-facto choice for processing data that requires high-performance computing. HPC is the capacity to handle information and perform complex calculations at high speed. It is the foundation for industrial, scientific, and cultural progressions.
Recently, the Volkswagen Group’s software company has promised to collaborate with Microsoft to build an Automated Driving platform on Microsoft Azure and leverage its compute and data capabilities to deliver safe automated driving on a global scale.
In this blog, we would be learning how Azure HPC supports automotive engineering simulation workloads. But before that, you need to check out the types of virtual machines available in Azure Cloud.
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Now, let us understand how Azure HPC helps in handling the automotive engineering simulation data and eases the workloads on Azure Data Engineers.
In the process of automotive cloud engineering simulation, Azure engineer has to follow these four steps for handling and managing, and producing the required result.
1. Design
The NV series virtual machines allow automotive engineers to create prototypes remotely. These VMs are specialized for heavy graphics and video editing and therefore helps vehicle engineers to iterate new designs in the cloud.
2. Conceptualize
NC-series virtual machines assist automotive engineers to optimize the design phase by delivering vehicle prototypes. The upgraded deep learning and computing is matched with low latency and high-throughput network interfaces improve the designing cycle.
3. Simulate
H-series VMs are perfect for high-CPU and huge-memory workloads for designing and physics simulations of all kinds. Regardless of your attempt to automate crash-test or multi-physics simulations, the latest HB and HC VMs empower vehicle engineers/architects to develop secure, firmly coupled, and cost-effective HPC simulations.
4. Enhance
ND-series VMs are best for deep learning workloads because they offer secondary low latency, high-throughput infrastructure for optimized performance in training models. They have larger GPU memory space where vehicle engineers can run training jobs simultaneously to enhance a vehicle’s controllers, actuators, sensors, and interaction with the physical world.
That is all about HPC and automotive simulation workloads. We hope you found the blog informative and useful. Moreover, if you want to hire Azure Engineers or other cloud professionals, PeoplActive is the best platform you can trust on. It is specialized in remote hiring talent and delivers you the right match from its high-class talent pool.
Kartik Donga 
