AI-Enabled Science
and Engineering with NVIDIA on Rescale
Rescale partners with NVIDIA to provide the industry-leading turnkey, secure, cloud-based artificial intelligence (AI) and high performance computing (HPC) simulation platform for research & development (R&D). Integrated with the latest NVIDIA software and hardware technologies, Rescale with NVIDIA allows users to instantly scale out computationally complex and AI-powered simulations and analytics.
Ian Buck, VP of Hyperscale & HPC, NVIDIA, highlights Rescale Performance Profiles at GTC on Mar 21 — Watch for free here >
Accelerate Scientific & Engineering Discovery
via the Industrial Metaverse in the Cloud
AI Frameworks
Deploy the latest NVIDIA AI & HPC frameworks like NVIDIA Modulus by connecting to the NVIDIA NGC for GPU-optimized containers, and even deploy HPC physics in NVIDIA Omniverse in just a few clicks with the near unlimited scaling potential of the cloud
HPC Applications
Unleash breakthrough scientific & engineering discoveries by integrating AI with CPU and GPU-accelerated simulation applications on a single platform for model training, inference, design automation, and design validation
GPU-Accelerated Hardware
Accelerate HPC and AI for R&D with turnkey access to NVIDIA hardware like NVIDIA DGX systems, NVIDIA DGX Cloud, and NVIDIA LaunchPad available through NVIDIA Base Command, as well as the latest NVIDIA GPU-accelerated instances from AWS, Azure, GCP, and OCI
Perform AI-Enabled R&D Effortlessly with NVIDIA Modulus on Rescale
NVIDIA Modulus is a neural network framework that blends the power of physics in the form of governing partial differential equations (PDEs) with data to build high-fidelity, parameterized surrogate models with near-real-time latency. Whether you’re looking to get started with AI-driven physics problems or designing digital twin models for complex non-linear, multi-physics systems, NVIDIA Modulus can support your work. Best of all, it is incredibly easy to launch on any cloud in just a few clicks with Rescale.
Deploy Hundreds of AI Models and Applications for Science and Engineering on Rescale
From HPC to conversational AI to medical imaging to recommender systems and more, NGC Collections offers ready-to-use containers, pre-trained models, SDKs, and Helm charts for diverse use cases and industries—in one place—to speed up your application development and deployment process. Rescale makes it turnkey simple to launch NVIDIA NGC on any cloud, NVIDIA DGX Foundry or LaunchPad.
Accelerate CFD with NVIDIA GPUs for Next Generation Aerospace Innovation
On Rescale, aerospace customers like XTI Aircraft are seeing performance and cost advantages by leveraging NVIDIA GPUs for CFD simulations with applications like NASA’s FUN3D. Rescale recently ran a benchmark of a popular NASA aircraft model. The benchmark resulted in 2x faster performance and up to 80% reduction in costs by switching from CPUs to NVIDIA GPU-accelerated core types on Rescale.
Expanding Ecosystem of GPU Applications on Rescale
See What Others Say
Explore Use Cases
Getting Started with AI for Engineering Simulations using Modulus on Rescale Platform
High-fidelity simulations in science and engineering are computationally expensive and time-prohibitive for iterative workflows from design analysis to optimization. Learn how you can use Modulus on the ScaleX platform to get started in as little as five clicks to create a digital twin model for your application using examples from computational fluid dynamics and design optimization.
How to Run Aerospace Engineering Simulations Securely in the Cloud with Rescale (Presented by Carahsoft)
Migrating scientific workloads to the cloud has always been challenging due to complexities that require knowledge in multiple domains, including (but not limited to) scientific/engineering expertise, cloud architecture, hardware architecture, security, and software license management. Specifically, creating a technological breakthrough is especially difficult in the aerospace sector, which traditionally requires billions of dollars in R&D, a small army of engineering staff, extensive wind tunnel testing, extensive security audits, and many years of development.
AZothBio Accelerates New Drug Discovery Using Deep Learning on Rescale
AZothBio’s proprietary epitope prediction AI model uses deep learning processes, and analyzes the biological data related to antigen/antibody reactions to predict peptide sequences that activate the immune response. The combination of the AI model and genome analytics widens the possibilities for developing immunotherapeutic drugs and vaccines. However, as they scaled up multiple areas of research their on-premises compute environment could not support the capacity and complexity of their tools, and it would be time and cost prohibitive to rebuild them in-house.