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Qualcomm does not provide a developer’s board, but the Sony Xperia Z is known to have OpenCL. Other phones are expected to have drivers pre-installed too. That is interesting, as new phones with Adreno 330 are shipped soon, such as the LG Optimus G2 LS980, Sony Xperia Z Ultra and a version of the Samsung Galaxy S4.
Drivers are still in beta and are known to have bugs (as of April 2013). This discussion is the most interesting to follow, if you want keep up to date.
There are plenty of tools available, such as the Snapdragon SDK for Android and these Tools and Resources for the Adreno GPU. In the latter you’ll find OpenCL samples you can run too (it is a Windows-installer, for some vague reason, so MAC and Linux users need to do some extracting). You can start building the code from this project.
Focus is on the more recent Snapdragon 800.
Inforce IFC6410 – Snapdragon 600
The Ifc6410 is a $149 costing single-board computer with Adreno 320 and Qualcomm Snapdragon S4 Pro – APQ8064.
Bsquare Mobile Development Boards for Snapdragon 800
Processor: Quad-core Krait 400 CPU at up to 2.3GHz per core (Snapdragon 8974) , Adreno 330 GPU, Hexagon QDSP6 V5. A few highlights: wifi n/ac, bluetooth 4, USB 3.0, NFC, 1280x720p screen (tablet: 1920x1080p), 2GB 800MHZ memory, 12MP+2MP camera. It all runs on Android 4.2 (Jelly Bean), so no Linaro-packages. More info the Qualcomm MDB page and on this Qualcomm blog.
Warning: you cannot call or use your provider’s internet with these devices! The word ‘phone’ only refers to the form factor.
DragonBoard Snapdragon APQ8060A for Snapdragon 800
Some highlight: Snapdragon 8074 quad core processor, 2GB of LPDDR3 RAM, 16GB of eMMC, Wi-Fi, Bluetooth, GPS, HDMI out and qHD LCD with capacitive multi touch, Adreno 330.
Can be ordered via http://mydragonboard.org/db8074/ for $499,-
Sony Xperia Z phones
It needs the Android NDK to run the OpenCL programs.
Sony sees great advantages in using OpenCL on their mobile phones – from the website:
You can also see that the execution speed is much faster using OpenCL on the GPU when compared to the plain single threaded c-code running on the CPU (tested on Sony Xperia Z1). In addition to the speed benefit, you may also find that you decrease energy consumption by utilizing OpenCL on the GPU compared to using standard programming methods on the CPU.
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