Deep Learning Inference Acceleration

Share

Deep learning inference acceleration is the end-to-end process of accelerating the inference of neural models while preserving the baseline accuracy. It is fully aware of the desired target inference hardware including GPU, CPU, or any ASIC accelerator. Powered by AutoNAC, it helps AI teams to squeeze the maximum utilization out of any hardware, speed up the trained model’s runtime, and reduce its memory size.

Filter terms by

Glossary Alphabetical filter

Related resources

deci-infery-updates-blog-featured
Deployment
deci-winter-release-2023-blog-featured-5
Algorithms
deep-learning-trends-2023-header
Algorithms

The Ultimate Guide to Inference Acceleration of Deep Learning-Based Applications

Learn 12 inference acceleration techniques that you can immediately implement to improve the speed, efficiency, and accuracy of your existing AI models.