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Tag: GPU Compute

Consumer multimedia
Chris Longstaff

Deep learning on mobile devices at the Embedded Vision Summit 2016

It was clear last week at the annual Embedded Vision Summit in Santa Clara that the time of computer vision and deep learning on mobile had finally arrived. Interest in the area is growing noticeably – the Summit program expanded from one to two days this year, there

Consumer multimedia
Alex Voica

Experience Vulkan graphics and compute at launch on PowerVR GPUs

Vulkan™ started more than a year ago as a cross-industry effort to develop an explicit API designed to work optimally on today’s leading-edge hardware. The activity has been managed by the Khronos™ Group, the same non-profit organization that develops popular APIs such as OpenGL ES, OpenCL, WebGL, or

Consumer multimedia
Kristof Beets

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

Consumer multimedia
Salvatore

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.

Consumer multimedia
Salvatore

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

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

Consumer multimedia
Salvatore

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

Consumer multimedia

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

Consumer multimedia

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

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