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Tag: Heterogeneous Compute
After exploring a quick guide to writing OpenCL kernels for PowerVR Rogue GPUs and analyzing a heterogeneous compute case study focused on image convolution filtering,
In a previous article we described our PowerVR Imaging Framework, a set of extensions to the OpenCL and EGL APIs that enable efficient zero-copy sharing
Writing and optimizing code for heterogeneous computing can be difficult, especially if you are starting from scratch. Imagination has set up a new page where
Imagination’s R&D group has developed a face detection algorithm, which is based on a classifier cascade and is optimized to run on mobile devices comprising
Modern mobile application processors are highly heterogeneous, combing a variety of different hardware components optimized for different tasks. As shown in the figure below, a
Computer vision is the use of computers to extract useful meaning from images, such as those that arise from photographs, video and real-time camera feeds.
In a previously published article, I offered a quick guide to writing OpenCL kernels for PowerVR Rogue GPUs; this sets the scene for what follows
In my previous article about heterogeneous architectures, I identified memory bandwidth as the main bottleneck for implementing power-efficient algorithms for computer vision. Luckily, Imagination has
Heterogeneous architectures in embedded computing are fast becoming a reality – we indeed see many leading IP and semiconductor companies today building heterogeneous computing hardware.
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