Tag Archives | GPU Compute

PowerVR Series7 - Series7XT_USC

Imagination’s smart, efficient approach to mobile compute

             

Imagination designed its PowerVR Tile-Based Deferred Rendering (TBDR) graphics architecture more than 20 years ago with a focus on efficiency across performance, power consumption and system level integration. This approach has equally been applied to our integration of compute functionality in our GPU architecture; PowerVR Rogue is the most recent version of our GPU architecture […]

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20-Parallel versus serial execution of a statement in a warp

Measuring GPU compute performance

    

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, I am going to spend some time looking at how developers can measure the performance of their OpenCL kernels on PowerVR Rogue GPUs. The performance of scalar code running on […]

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05-Zero-copy transfer between a camera and display

Supported zero-copy flows inside the PowerVR Imaging Framework

     

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 of memory between a PowerVR GPU and other system components such as a CPU, ISP and VDE. Most flows use EGL to facilitate the sharing of objects between multiple client […]

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Debugging OpenCL programs with Oclgrind

   

James Price is currently completing a PhD degree at the Department of Computer Science, University of Bristol. When developing programs that utilise GPU compute via OpenCL, we can’t use our traditional CPU development tools. This can make debugging complex OpenCL kernels challenging. As part of my PhD, funded by Imagination Technologies, I’ve developed an OpenCL […]

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PowerVR framework offers easy imaging integration 2

The PowerVR Imaging Framework camera demo

     

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 developers can access the source code for an example camera and video post-processing application that leverages the PowerVR Imaging Framework to implement efficient zero-copy flows for a range of image […]

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12-Block-level implementation of face detection on CPU and GPU

Deep dive: OpenCL face detection on PowerVR [part 3]

       

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 a CPU and PowerVR GPU. The algorithm employs several optimizations to improve performance and accuracy. In particular, instead of searching each entire frame for faces, the detector limits its search […]

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1-Baidu offline mobile DNN app

Deep dive: Implementing computer vision with PowerVR [part 1]

     

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. Thanks to the proliferation of low-power parallel processors, the increasing availability of 3D sensors and an active ecosystem of algorithm developers, it is now possible for many embedded devices to […]

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15-Example of image filtering by means of convolution

Heterogeneous compute case study: image convolution filtering

     

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 next: a practical case study that analyzes image convolution kernels written using OpenCL. Many image processing tasks such as blurring, sharpening and edge detection can be implemented by means of […]

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25-Integrating zero-copy flow with Android Camera HAL

The PowerVR Imaging Framework for Android

     

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 created an innovative solution designed to address this common issue in mobile and embedded devices – and it comes in the form of the PowerVR Imaging Framework. Introducing the PowerVR […]

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03-Vision software pipeline implemented on top of hardware

Increasing performance and power efficiency in heterogeneous software

     

Heterogeneous architectures in embedded computing are fast becoming a reality – we indeed see many leading IP and semiconductor companies today building heterogeneous computing hardware. In the article below, I’m going to describe one typical use case for heterogeneous computing and the challenges that result from moving to a heterogeneous programming model. Running a beautification […]

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