Deep Learning uses neural networks to perform tasks such as machine vision, voice recognition and natural language processing. Trained models are often deployed across many devices such as cellphones to derive insight from new data – a process called inference.
Micron’s Deep Learning Accelerators enable inference tasks to be carried out much more rapidly, using much less energy, than general-purpose computers.
Developers can easily harness our technology explore and deploy Deep Learning models using a wide range of popular open source frameworks to solve previously-intractable data analytics problems from the edge to the cloud.
Micron's DLAs are compatible with popular deep-learning frameworks and capable of running all state-of-the-art neural networks.
Simply change three lines from your existing code to go from CPU, to GPU, to Micron DLA.
The DLA SDK allows you to run multiple neural networks on one DLA device, or spread one neural network across multiple DLA cores.
The Micron DLA comes bundled with a state-of-the-art compiler that converts neural networks into machine code for the DLA. A run-time component provides execution of your applications.