Tag Archives | GPU Compute

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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07-Example NDRange in 2 dimensions comprising 512 work-items

A quick guide to writing OpenCL kernels for PowerVR Rogue GPUs


This article and a follow-up to be published next month introduce OpenCL programming for the PowerVR Rogue architecture. Firstly, I’d like to give you an overview of OpenCL programming fundamentals using a basic program, followed by an explanation of OpenCL execution on Rogue GPUs. This provides the background to understand the programming guidelines for the […]

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01-SoC architecture

A primer on mobile systems used for heterogeneous computing


In the mobile and embedded market, the design constraints of electronic products can sometimes be seen as tight and contradictory: the market demands higher performance yet lower power consumption, reductions in cost but shorter time-to-market. These constraints have created a trend for more specialized hardware designs that fit a particular application; if each task is […]

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GPU compute_memory hierarchy in OpenCL

The complete glossary to heterogeneous compute


For the last decade, Imagination has been at the forefront of heterogeneous compute, becoming a founding member of the HSA Foundation and a contributor to many open heterogeneous computing standards available today, including OpenCL, OpenGL ES and Vulkan. Our MIPS processors, PowerVR multimedia and Ensigma connectivity technologies have been integrated in many mobile and embedded […]

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ELVEES goes full purple: MIPS, PowerVR and Ensigma united in one vision chip


If you follow this blog closely (and I hope you do), you may have read several articles recently about the great work Imagination is doing to help silicon vendors get to market quickly. One example is the creation of IP platforms that can easily be integrated on chip. In addition, these IP platforms support customizable […]

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The future of mobile embedded GPUs - PowerVR Series7 infographic

The future of mobile and embedded GPUs [infographic]


With the new PowerVR Rogue GPUs making appearances in several mobile chips, we’ve designed an infographic which outlines the future of graphics processing on smartphones, tablets, wearables and more. The graphic helps consumers understand how the newer GPUs stack up against their predecessors and what are the unique advantages of PowerVR over competing solutions. We’ve […]

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