If you don’t study AI, you will really fall behind! ! !
When we open various news apps every day, we will find that news related to AI has already occupied a place. Keywords such as "artificial intelligence, neural network" are frequently searched, and various industries such as design, manufacturing, and software engineering have also appeared. Begin to apply AI-related technologies on a large scale. The general trend of AI development is irresistible.
With traditional design workflows, engineers struggle to fully explore the design space and quickly come up with solutions to emerging challenges. The emergence of AI helps these engineers discover novel solutions, utilize large amounts of existing simulation data, and improve the final design, thereby helping to speed up the design and simulation process.
Recently, Dell Technologies and NVIDIA jointly released the "Application of Artificial Intelligence in Design and Engineering Workflow" white paper, introducing how AI is integrated into design and engineering solutions and workflows, as well as new workstations and high-performance computing solutions How to enable engineers to effectively utilize these functions. Let’s take a look!
Product design: being closely integrated with AI
●In design and CAD scenarios, AI is already having a tangible impact thanks to the emergence of generative design tools. In design applications, AI (artificial intelligence) and ML (machine learning) can create a series of excellent design solutions based on predefined constraints. Generative design tools require engineers to predetermine these constraints, including thermal performance, stiffness, material options and even specific manufacturing processes, and the software can then create hundreds or even thousands of options for evaluation. At this point, engineers can narrow down the options by fine-tuning constraints to build a design that combines the specific needs of the user.
●In the field of electronic CAD (ECAD), many companies have also developed AI-supported software tools to help designers speed up printed circuit board (PCB) design. These tools rely on data from previous design plans to help automate circuit board layout and routing design and improve work efficiency.
It is also worth noting that more and more AI rendering visualization tools are emerging. For example, NVIDIA AI uses the open source Stable Diffusion model to support users to generate 2D sketches and images using text prompts. Depix Technologies has launched a tool that allows users to create high dynamic range (HDR) panoramic images and backplates using simple text prompts.
Simulation: Improving efficiency with AI is key
AI has also been widely used in simulation, and has helped companies greatly improve work efficiency and design quality.
Analysis and simulation often become bottlenecks during the design cycle, especially as models grow in size and complexity. In order to improve this situation, simulation software companies are actively exploring and testing generative artificial intelligence natural language tools, aiming to optimize the user interface and lower the threshold for software use. Simple text prompts make it easy to run simulations even if users have no expertise in a specific solver, significantly reducing the time required to learn new software.
Take Ansys as an example. They have launched a support tool based on generative artificial intelligence technology - AnsysGPT, which can quickly handle common customer support requests. What’s even more striking is that according to data, users can even write Java programs through AI to perform specific simulation tasks, without any programming experience.
Generating synthetic data also requires AI, which has become a key driver in training autonomous vehicle systems. For example, training a self-driving car requires collecting millions of hours of operational data across countless vehicle scenarios, so this process can be accelerated virtually using synthetic data that reflects real-world scenarios. For example, NVIDIA offers the NVIDIA DRIVE Sim™ platform (based on NVIDIA Omniverse™) for running physically accurate, large-scale multi-sensor simulations in immersive 3D environments. The NVIDIA Omniverse Replicator platform generates synthetic data for these simulations. When working with this type of data, you no longer need to perform time-consuming data cleaning and labeling tasks that are required when working with existing datasets.
A good saddle for a good horse: Dell Precision
7960 Tower Workstation is born for the AI era
Advanced AI-based design and simulation tools can run more effectively and efficiently on engineering workstations equipped with new NVIDIA® RTX™ GPUs.
Dell Technologies has created a series of high-performance workstations specifically for AI and data science applications, providing engineers with the computing resources they need to ensure they can smoothly use these advanced tools. Among them, the Dell Precision 7960 tower workstation has become an ideal choice for AI engineering workflow due to its excellent performance configuration.
This redesigned Dell Precision 7960 tower workstation is impressive with its powerful performance. It supports a single 56-core CPU while boasting a spacious chassis that can easily accommodate up to four double-wide graphics cards. This means users can configure up to four NVIDIA® RTX™ 6000 Ada GPUs for tasks such as AI-based CAE workflows, rendering and visualization .
NVIDIA® RTX™ 6000 Ada is a powerful graphics card equipped with 48GB of graphics memory. This huge memory capacity allows users to easily process massive data sets and perform simulation and rendering tasks on large and complex models.
Equipped with one or more NVIDIA® RTX™ GPUs, these workstations provide engineers with a powerful platform to locally process large models and data sets typical of AI-based workflows. In addition, engineers can use reduced-order models (ROM) to quickly complete verification in the early stages of design, thus greatly improving work efficiency. Together, these advanced engineering workstations play a vital role in driving the development of more accessible automated design and simulation scenarios .
Summarize
While AI isn’t always suitable for every scenario, it opens up endless possibilities for teams that have access to sufficient amounts of legacy design, simulation, and test data. By leveraging AI, these teams can expand the potential design space, reveal unprecedented engineering insights, and accelerate verification and simulation processes, resulting in faster, better design iterations.
In addition to rich data resources, the successful application of AI solutions also requires the support of powerful workstations and high-performance computing resources. In this regard, the combination of Dell Precision professional workstations and NVIDIA® RTX™ GPUs provides powerful processing capabilities. Engineers can rely on these emerging AI-based tools to support their current design workflows and be fully prepared for future technology developments. This combination not only allows engineers to realize the full potential of AI, but also ensures that they stay ahead of the curve and remain competitive in the face of complex and ever-changing engineering challenges.
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