BeagleBoard/GSoC/2021ProposalGPGPU

=ProposalTemplate = About Student: Steven Schuerstedt Mentors: Hunyue Yau Code: current sample code: https://github.com/StevenSchuerstedt/GPGPU_with_OpenGL Wiki: https://elinux.org/BeagleBoard/GSoC/2021ProposalGPGPU GSoC: https://elinux.org/BeagleBoard/GSoC/Ideas-2021#GPGPU_with_GLES

=Status= This project is currently just a proposal.

=Proposal= I have completet the requirements on the ideas page. ARM cross compiling pull request: https://github.com/jadonk/gsoc-application/pull/153

About you
IRC: steven100 Github: https://github.com/StevenSchuerstedt School: Karlsruhe Institute of Technology Country: Germany Primary language: German, English Typical work hours:5AM - 3PM US Eastern Previous GSoC participation: I love the idea of open source and especially open hardware. First time participant.

About your project
Project name: GPGPU with OpenGL ES

Description
The beagleboard ARM A8 Processor has an integrated graphics accelerator from PowerVR (SGX530 or 550). As the name implies this chip is mainly used and built for graphics rendering, but as the time shows there exist alot of other applications that profit from the parallel nature of graphic chips, like deep learning, bitcoin mining or analyzing DNA sequences. This is called GPGPU (general purpose computations on graphic processing units) and is done with api's like OpenCL or CUDA. The PowerVR SGX only supports the OpenGL ES 2.0 specification (there also exist a propiertary openCL driver from IT https://university.imgtec.com/fun-with-beagle-video/), this api is heavily targeted towards graphics rendering, but can also be exploited for general purpose computations. The goal of this project is, to show how to use the mostly unused graphics accelerator chip for general purpose computations using the OpenGL ES api. Therefore I will create samples, showing how to use the GPGPU and also show the timing difference when doing computations on CPU vs GPU. The samples could be convolution or matrix multiplication. The samples and techniques shown, are applicable for all beagleboards, but maybe most relevant for BBAI, as it has the best gpu.

Implementation:
I provide a first example how to add two vectors using OpenGL (https://github.com/StevenSchuerstedt/GPGPU_with_OpenGL). I will use this as a starting point for this project. OpenGL ES 2.0 is only a small subset of the whole OpenGL specification, so the specific OpenGL commands have to be choosen carefully, so they are supported on the SGX GPU. Data transfer between CPU and GPU will be done using textures. The difficulty for each GPGPU project is to find a good mapping from the input data to textures and texture coordinates. Also there exists different texture formats, with different floating point precisions. The fragment shader will include the actual computations for the data and the result will be written to a output texture attached to a framebuffer.

- ARM neon intrinsics - BBAI (SGX 544) - upstream? what happens after GSoC

Timeline
Provide a development timeline with a milestone each of the 11 weeks and any pre-work. (A realistic timeline is critical to our selection process.)

Experience and approach
I have a decent experience in programming, computer-graphics and mathematics. I developed a 2D platformer game with C++ and OpenGL (StevieJump), a Monte-Carlo Pathtracer with C++ (StevieTrace) and I'm very interested in computer architecture and embedded systems. I followed Ben Eaters excellent youtube series to build a 8-Bit Breadboard Computer (8-Bit). I currently work as a C++ / OpenGL software developer at my university. I have experience in OpenCL and did several GPGPU courses at my university.

Contingency
I got stuck many times in my life, especially with programming related tasks. Programming and computer science can sometimes be a very unforgiving and frustrating experience. There is no easy way around this, so I will just keep trying and do my best, there is no shame in failure, just in giving up. So if I dont give up I will eventually succed. If I really get stuck I just take a break and do some outdoor exercise, this always helps.

Benefit
Enable more people to use the GPU on a beagleboard. Accelerate computations. Free up the main processor to do other stuff. If successfully completed, what will its impact be on the BeagleBoard.org community? Include quotes from BeagleBoard.org community members who can be found on http://beagleboard.org/discuss and http://bbb.io/gsocchat.

Misc
Please complete the requirements listed on the ideas page. Provide link to pull request.

Suggestions
Is there anything else we should have asked you?