And the simulations that need to be run will run 2.5x faster on an A100 GPU. By narrowing the field, AI can slash by orders of magnitude the need for thousands of time-consuming simulations. Using this technique, AI can define a few areas of interest for conducting high-resolution simulations. The trained AI model also can take in data from an experiment or sensor, further refining its insights. Then the AI and simulation models run together, feeding off each other’s strengths until the AI model is ready to deliver real-time results through inference. The speed gains open a door for combining AI with simulations and experiments, creating a positive-feedback loop that saves time.įirst, a simulation creates a dataset that trains an AI model. That means simulations that kept researchers and designers waiting overnight can be viewed in a few hours when run on the latest A100 GPUs. Each number in the format takes up 64 bits inside a computer, making it one the most computationally intensive of the many math formats today’s GPUs support.Īs the next big step in our efforts to accelerate high performance computing, the NVIDIA Ampere architecture defines third-generation Tensor Cores that accelerate FP64 math by 2.5x compared to last-generation GPUs. Simulations make numeric models visual with calculations that use a double-precision floating-point format called FP64. They also let designers create everything from sleek cars to jet engines.īut simulations are also among the most demanding computer applications on the planet because they require lots of the most advanced math. Simulations help us understand the mysteries of black holes and see how a protein spike on the coronavirus causes COVID-19.
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