CNNdroid: GPU-Accelerated Execution of Trained Deep Convolutional Neural Networks on Android

TL;DR

CNNdroid is an open-source GPU-accelerated library that enables efficient execution of deep CNNs on Android devices, significantly improving speed and energy efficiency for mobile machine learning applications.

Contribution

It introduces CNNdroid, a novel GPU-accelerated library that enhances deep CNN performance on Android devices, addressing performance and energy constraints.

Findings

Achieves up to 60X speedup on mobile devices.

Provides up to 130X energy savings.

Open source library available for developers.

Abstract

Many mobile applications running on smartphones and wearable devices would potentially benefit from the accuracy and scalability of deep CNN-based machine learning algorithms. However, performance and energy consumption limitations make the execution of such computationally intensive algorithms on mobile devices prohibitive. We present a GPU-accelerated library, dubbed CNNdroid, for execution of trained deep CNNs on Android-based mobile devices. Empirical evaluations show that CNNdroid achieves up to 60X speedup and 130X energy saving on current mobile devices. The CNNdroid open source library is available for download at https://github.com/ENCP/CNNdroid