The landscape of Machine Learning software libraries and models is evolving rapidly, and to satisfy the ever-increasing demand for memory and compute while managing latency, power and security considerations, hardware must...
Antmicro has been working with a large number of customers implementing AI software on embedded systems, helping utilize all the advantages of an open source-based approach. To achieve this we created a complete methodology...
Building on top of the flexibility that was the original premise of Renode, our open source simulation framework has for some years now been used for pre-silicon development, architectural exploration and hardware-software...
Kenning is Antmicro’s library aiming to simplify the workflow with machine learning applications on edge devices. It is used for testing and deploying ML pipelines on a variety of embedded platforms regardless of the underlying...
Development of Machine Learning algorithms which enable new and exciting applications is progressing at a breakneck pace, and - given the long turnaround time of hardware development - the designers of dedicated hardware accelerators...
The demand for deploying machine learning models, especially state-of-the-art deep neural networks on edge devices is rapidly growing. Edge AI allows to run inference locally, without the need for a connection to the cloud...
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