HPC and AI

Boost Accuracy with GPU-Accelerated HPC and AI

Accelerated computing is helping researchers accomplish their scientific breakthroughs faster. But researchers are quickly realizing that AI can help them produce high-accuracy results that are on par with scientific simulations in a much shorter time frame. This has fueled the adoption of AI in high-performance computing (HPC).

Who Uses HPC and AI?

HPC and AI can be used in a variety of fields, including researchers working in laboratories, engineers solving complex technical problems, and financial analysts using mathematical algorithms to make market predictions.

Researchers

Researchers are enhancing their HPC simulations with AI to achieve faster and better results for various scientific workloads.

Engineers

Engineers are using AI to evaluate a variety of designs, including medical devices, manufacturing robots, and automotive components.

Analysts

Analysts at financial organizations are leveraging AI to identify and predict market trends, flag fraudulent transactions, and speed up online payments.

Accelerate Your Workloads

NVIDIA enables HPC researchers to take advantage of AI with GPU-optimized AI and HPC software—available from the NVIDIA NGC™ catalog—that can be deployed on GPU-powered HPC clusters, cloud instances, and workstations.

PyTorch

PyTorch is a GPU-accelerated tensor computational framework. Functionality can be extended with common Python libraries such as NumPy and SciPy.
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TensorFlow

TensorFlow is an open-source platform for machine learning. It provides comprehensive tools and libraries in a flexible architecture that allows easy deployment across a variety of platforms and devices.
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TorchANI

TorchANI is a PyTorch implementation of ANI and contains classes like AEVComputer, ANIModel, and EnergyShifter that can be pipelined to compute molecular energies from the 3D coordinates of molecules.
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To explore the performance speedups of some key HPC applications, visit the NVIDIA Developer Zone. To get started with these GPU-accelerated applications, visit NVIDIA NGC.

Unlock Industrial and Scientific Simulation Capabilities with NVIDIA Modulus

AI-Accelerated Simulation Toolkit

NVIDIA Modulus is a neural network framework that blends the power of physics and partial differential equations (PDEs) with AI to build more robust models for better analysis. 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.

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NVIDIA Modulus - AI-Accelerated Simulation Toolkit

HPC and AI in Action

HPC and AI have many applications, such as solving our earth’s climate problems, accelerating scientific discoveries, and simulating workflows to complete tasks faster.

Simulate Workflows for Product Designs

NVIDIA Modulus, previously referred to as SimNet, is a neural network framework that blends the power of physics and partial differential equations (PDEs) with AI to build more robust models for better analysis. Modulus helped solve a multi-physics problem to perform automatic design space exploration 1,000X faster than traditional simulation, with the accuracy of numerical solvers.
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Model Earth Systems

HPC and AI are used in many geosciences scenarios, including extreme weather forecasting, physics emulation, nowcasting, medium-range forecasting, uncertainty quantification, bias correction, generative adversarial networks, data in-painting, network-HPC coupling, PINNs, and geoengineering, among others.
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Take Advantage of HPC and AI Software from NGC

The NGC catalog offers containers for the latest versions of AI, HPC, and visualization software.
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Accelerate Scientific Discoveries

The convergence of deep learning and artificial intelligence with traditional HPC accelerates the pace of scientific discovery, from high-energy physics to life sciences and healthcare.
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Learn more about HPC and AI through session and demo videos, or get started with the NVIDIA Developer Blog.

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