Signal Processing and ML Inference on the Edge (online talk by Kai Wolf)

Agenda:
This talk will recapitulate some essential audio processing basics and introduce necessary ML concepts before discussing different approaches for fast inference implementation on mobile devices. The talk will be held in English, together with the C++ UG Osnabrück.

Details:
The recent decade has been revolutionary regarding many technical aspects of our daily lives. We have experienced the transition from simplistic feature phones to fully featured little supercomputers carried
along in our pockets, capable of performing uttermost computationally heavy tasks directly on the device. Moreover, we are currently already in the midst of what some may call the third AI renaissance, and are now able to solve pattern recognition problems with relatively little effort that in the past could only be solved by humans. The latter development has been a game changer for a variety of applications including anomaly detection, classification or speech recognition.

Despite the advanced computational resources of modern mobile devices, it is still challenging to obtain optimal throughput and minimal latency with signal processing implementations, which typically involves
exploiting device specific acceleration techniques, such as vector intrinsics. However, this is not always feasible, especially when targeting a large variety of different architectures and target devices. One solution to this problem is using Androids RenderScript, a heterogeneous computing framework, to accelerate the processing of otherwise performance intensive tasks which will get optimized across multi-core CPUs, GPUs or DPSs on the target device.