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Project update 18 of 20
Amid all of the uncertainty in our work schedules, we think now is a great time to host a webinar on signal processing and deep learning with GPUs and the AIR-T. The Webinar will cover the items below but more importantly we will be demonstrating the usage of cuSignal on the AIR-T!
Space is limited, so make sure to register in advance. Read below for more information about the webinar and we hope you will join us!
Deepwave Digital, Inc.
We will introduce you to the Deepwave Digital team and provide an overview of what our startup does. We will also discuss the way we see deep learning being applied to systems and signals.
We will provide a detailed discussion on the application programming interface (API) for the AIR-T, AirStack. The figure below outlines the CPU, GPU, and deep learning interfaces supported.
Here we will discuss programming the embedded NVIDIA Jetson GPU that is part of the AIR-T using CUDA, pyCUDA, and GNU Radio.
cuSignal is an open source GPU accelerated version of Scipy.Signal. The team at NVIDIA started the initiative a few months back and Deepwave has decided to jump on board and contribute. If you are not familiar with cuSignal, it is part of the large RAPIDS project at NVIDIA: the push to GPU accelerate data science libraries.
Read more about cuSignal here
Finally we will close the webinar by discussing deep learning applications and how to leverage the AIR-T to acquire data and how to deploy trained neural networks on the AIR-T for inference.