Converting existing apps to work with the LPGPU2 Tool Suite

Many of our potential customers for LPGPU2 may have existing applications that they want to use with the tool. In order to do this some minor modifications are required (this is due to wanting the tool to support commercial devices that are not rooted) and we feel the minor inconvenience of modifying your app is outweighed by being able to profile on end user devices.

In order to provide a worked example of this, we have taken one of the apps that Samsung developed as part of the project that implements different font-rendering methods (CPU & GPU) and written a report that describes what the app does and how we modified it to work with the tool.


In subsequent posts we will provide details on the results of the CPU vs. GPU font rendering analysis and best practices for using the LPGPU2 Tool Suite if you haven’t created your application yet.



PEGPUM18 Workshop Highlights!

LPGPU2 consortium member Codeplay have taken pictures taken by Spin Digital at the PEGPUM18 workshop and wrapped them all up into a cool slideshow video, which is now available on our YouTube channel:


LPGPU2 – HiPEAC Highlight Day 1!

The LPGPU2 consortium were very happy to see that some of the PEGPUM18 workshop was included in the HiPEAC Day 1 highlights! See more here:




Face to Face meeting: Jan 2018 – Codeplay (Edinburgh)

Last week representatives from all of the LPGPU2 consortium attended the first face to face of 2018 at Codeplay in Edinburgh. Despite wind, sleet and snow a very productive meeting was held with discussions covering the current progress and plans for the rest of the project.

Spin Digital to present its latest developments in video rendering at PEGPUM-18

Spin Digital will be part of the PEGPUM workshop organized by the LPGPU2 consortium that will take place in Manchester from January 22ns to 24th 2018.  Read more »

Think Silicon @CES2018

Think Silicon kicked-off successfully the new year at the Consumer Electronics Show  (@CES2018), in Las Vegas. CES is the place to be, when you are in the consumer electronics business and looking for the latest technology-trends and gadgets.

Think Silicon launched an ultra-low power Internet of Things (IoT) platform, created in cooperation with Synopsys. Designed to extend battery life of a wearable or embedded device for days (not for hours…) it runs just at 33MHz, yet still provides smartphone-like fast responsive graphics. The FPGA development platform contains a DesignWare® ARC EM5D Processor and Think Silicon’s® IP including a NEMA®|p single core GPU, NEMA®|DC Display-controller, and the NEMA®|GFX-API. The fully-fledged platform, is aimed to develop ultra-low power, connected wearables and low-power embedded (touch-) display devices.

7 New Video Uploads from the Samsung LPGPU2 Team!

Today Samsung has uploaded videos for 7 of their Vulkan test apps. Find out more about each one, including why it was written the way it was, and what we hope the LPGPU2 tool will identify when analysing them:

The LPGPU2 Vulkan Raymarching test app is designed to test the LPGPU2 profiling tool’s ability to analyse GPU compute-bound scenarios. All of the work for this app is confined to the fragment shader, which involves a computationally expensive loop detecting the distance a ray travels into the scene before colliding with geometry.

The LPGPU2 Vulkan Overdraw App displays a stack of translucent sheets that span almost the entire display area. The stack can be drawn either front to back or back to front. Can the LPGPU2 profiling tool detect a difference between these scenarios, and what are the implications of having many pixels repeatedly overdrawn?

The LPGPU2 Vulkan OverdrawTex App is geometrically identical to the Overdraw App – it displays a stack of translucent sheets that span the display area. The difference is that instead of colouring the triangle with a simple interpolation between values, a texture lookup is invoked. What happens when many more texture lookups are issued than there are pixels? Can the LPGPU2 profiling tool recognise this scenario?

The LPGPU2 Vulkan Menger Sponge app has a variable amount of geometry and a variable amount of detail on that geometry. The detail is implemented through a multi-level fragment shader algorithm. The result is an app that has a tuneable volume of geometry and independently tuneable compute burden.

The LPGPU2 Vulkan Hypercube app displays a representation of a 4D hypercube as it tumbles about the three most interesting planes of a 4D space. The scene contains a small amount of geometry and uses almost trivial shaders. The app is designed to have a low graphics overhead to find out what the LPGPU2 profiling tool reports in that situation.

The LPGPU2 Vulkan Globe app simulates a cloud-covered earth spinning in a starry sky. The number of cloud layers is variable, resulting in an app that specifically stresses the texture capabilities of the GPU.

The LPGPU2 Vulkan Uber app is the ‘kitchen sink’ of tests with its high levels of geometry, many textures, and heavy fragment- and vertex-processing, resulting in a low frame rate and very slow start-up time. Can the LPGPU2 profiling tool pick it apart?


Verifying behaviour with the LPGPU2 Toolsuite

Yesterday I was looked at the behaviour of one of our test apps (you can see an example of the sort of thing here  ) after observing it behaving strangely on one of our test devices.

The application I was using runs through a set of ‘apps’ for a fixed number of frames and then loops. The first app being run was running slowly and not as fluidly as the others.

The first thing I did was to take a capture with the LPGPU2 tool and get a high level overview of what was occurring:

Screen grab from tool – click to zoom

All of the counter data you can see if live and valid and reflects the system state at the time the graphics API calls from the application were being captured (GLES and EGL in this case).

Take a closer at the Regions of Interest (ROI) (shown in a blue gradient) and frames (shown in green)ribbons:

ROI and frames ribbons – click to zoom

In the above you can see that there are ROI that correspond to the heavy content being equally spaced along the timeline. You can also see how these ROI align with frames.

The more astute of you may notice that the ROI and frames are not completely consistent yet, but this is all part of the toolset validation and will be addressed as the project progresses.


PEGPUM 2018 Program Announcement!

The program for the PEGPUM 2018 workshop at HiPEAC 2018 in Manchester has been announced. More information can be found here. The program includes various technical presentations (from industry and academia) as well as a live demonstration showing the LPGPU2 toolchain analyzing GPU software.

LPGPU2 D5.3 Demonstration Video

In this the third video, we show off some more of the new features of LPGPU2 CodeXL including some of the new visualisations that are now available. In the video, we demonstrate the typical work flow for carrying out a power data profile capture session. Included in this workflow we also show you how to run the data analysis Feedback Engine to receive advice on issues found in the capture data.


The DC API, developed by Samsung and implemented by Think Silicon, TUB and Samsung is used by the application on the remote device which in this case is a standard Nexus Six Android phone to generate profile data sent over to CodeXL.

The visualisations seen in LPGPU2 CodeXL to display the API calls, frames and performance data along with the Help and feedback visualisations were created by Codeplay. The Feedback Engine’s advice, written in Lua by Samsung, is first seen in the power profile view as a Help ribbon under the frame data as Regions of Interest (ROI). From there a user can drill down to specific areas of interest or examine the advice given for that region in time.

Last but not least is a powerful new feature which allows the user to be able to compare the current profile session or any previous profile session with others so you are able to visualise graphically any differences for a counter over time.

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