Mobile GPU Computing for Accelerated Apps |
This software is not yet available as a product. Mobile GPU consulting services are currently available. To get started with mobile GPU computing, email us at sales@accelereyes.com and include a description of your application.
Overview
AccelerEyes is building a software acceleration library for mobile devices. It contains commonly used compute functions. It delivers a 5 to 30X speed boost for convolutions and other common compute functions. It enables:
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The AccelerEyes mobile GPU computing software delivers performance through its unique GPU computing capability. All mobile devices have a GPU which can deliver greater compute throughput than the CPU. Why not use the GPU to make your app faster?
Details
The AccelerEyes mobile library is a C/C++ library with a simple matrix API. The same code can be deployed on all platforms without any further code rewrites. For software and documentation, register below.
Supported Platforms
 Android |
 iOS |
Supported GPUs
The mobile library supports the OpenGL ES 2.0 and OpenCL specs, compatible with all popular GPUs, including the following:
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Example - Tennis Volley Game
This tennis game demonstrates controller free gaming with mobile devices, made possible using GPU acceleration. The motion detection is done via Horn-Schunck optical flow.
Download the "Tennis Volley" game on the iTunes App Store or the Android Market.
iPad2 using PowerVR GPU
Motorola Xoom using Tegra2 GPU
Example - Traffic Video Processing
Simple demonstration of performance boost in a video processing application, computing the gradient of the image frames. Filmed in midtown Atlanta.
Google Nexus S: CPU at 1.3 FPS, GPU at 35 FPS
Motorola Atrix: CPU at 2.9 FPS, GPU at 29 FPS
Example - Tracking with Chan/Vese Active Contours
Simple demonstration of a real-time tracking application, using the popular Chan/Vese active contours. Filmed in midtown Atlanta.
Google Nexus S
Motorola Atrix