at FOSDEM 2018 when Yunsup and the team announced the U540 there was some discussion about this: it was one of the questions asked. one of the possibilities raised there was that maddog was heading something: i've looked for that effort, and have not been able to find it [jon is getting quite old, now, bless him. he had to have an operation last year. he's recovered well].

also at the Barcelona Conference i mentioned in the very-very-very-rapid talk on the Libre RISC-V chip that i have been tasked with, that if there is absolutely absolutely no other option, it will use Vivante GC800 (and, obviously, use etnaviv). what that means is that there's a definite budget of USD $250,000 available which the (anonymous) sponsor is definitely willing to spend... so if anyone can come up with an alternative that is entirely libre and open, i can put that initiative to the sponsor for evaluation.

basically i've been looking at this for several months, so have been talking to various people (jeff bush from nyuzi [1] and chiselgpu [2], frank from gplgpu [3], VRG for MIAOW [4]) to get a feel for what would be involved.

  • miaow is just an OpenCL engine that is compatible with a subset of AMD/ATI's OpenCL assembly code. it is NOT a GPU. they have preliminary plans to make one... however the development process is not open. we'll hear about it if and when it succeeds, probably as part of a published research paper.

  • nyuzi is a modern "software shader / renderer" and is a replication of the intel larrabee architecture. it explored the concept of doing recursive software-driven rasterisation (as did larrabee) where hardware rasterisation uses brute force and often wastes time and power. jeff went to a lot of trouble to find out why intel's researchers were um "not permitted" to actually put performance numbers into their published papers. he found out why :) one of the main facts that jeff's research reveals (and there are a lot of them) is that most of the energy of a GPU is spent getting data each way past the L2/L1 cache barrier, and secondly much of the time (if doing software-only rendering) you have several instruction cycles where in a hardware design you issue one and a separate pipeline takes over (see videocore-iv below)

  • chiselgpu was an additional effort by jeff to create the absolute minimum required tile-based "triangle renderer" in hardware, for comparative purposes in the nyuzi raster engine research. synthesis of such a block he pointed out to me would actually be enormous, despite appearances from how little code there is in the chiselgpu repository. in his paper he mentions that the majority of the time when such hardware-renderers are deployed, the rest of the GPU is really struggling to keep up feeding the hardware-rasteriser, so you have to put in multiple threads, and that brings its own problems. it's all in the paper, it's fascinating stuff.

  • gplgpu was done by one of the original developers of the "Number Nine" GPU, and is based around a "fixed function" design and as such is no longer considered suitable for use in the modern 3D developer community (they hate having to code for it), and its performance would be really hard to optimise and extend. however in speaking to jeff, who analysed it quite comprehensively, he said that there were a large number of features (4-tuple floating-point colour to 16/32-bit ARGB fixed functions) that have retained a presence in modern designs, so it's still useful for inspiration and analysis purposes. you can see jeff's analysis here [7]

  • an extremely useful resource has been the videocore-iv project [8] which has collected documentation and part-implemented compiler tools. the architecture is quite interesting, it's a hybrid of a Software-driven Vector architecture similar to Nyuzi plus fixed-functions on separate pipelines such as that "take 4-tuple FP, turn it into fixed-point ARGB and overlay it into the tile" instruction. that's done as a single instruction to cover i think 4 pixels, where Nyuzi requires an average of 4 cycles per pixel. the other thing about videocore-iv is that there is a separate internal "scratch" memory area of size 4x4 (x32-bit) which is the "tile" area, and focussing on filling just that is one of the things that saves power. jeff did a walkthrough, you can read it here [10] [11]

so on this basis i have been investigating a couple of proposals for RISC-V extensions: one is Simple-V [9] and the other is a small general-purpose memory-scratch area extension, which would be accessible only on the other side of the L1/L2 cache area and ONLY accessible by an individual core [or its hyperthreads]. small would be essential because if a context-switch occurs it would be necessary to swap the scratch-area out to main memory (and back). general-purpose so that it's useful and useable in other contexts and situations.

whilst there are many additional reasons - justifications that make it attractive for general-purpose usage (such as accidentally providing LD.MULTI and ST.MULTI for context-switching and efficient function call parameter stack storing, and an accidental single-instruction "memcpy" and "memzero") - the primary driver behind Simple-V has been as the basis for turning RISC-V into an embedded-style (low-power) GPU (and also a VPU).

one of the things that's lacking from RVV is parallelisation of Bit-Manipulation. RVV has been primarily designed based on input from the Supercomputer community, and as such it's incredible. absolutely amazing... but only desirable to implementt if you need to build a Supercomputer.

Simple-V i therefore designed to parallelise everything. custom extensions, future extensions, current extensions, current instructions, everything. RVV, once it's been implemented in gcc for example, would require heavy-customisation to support e.g. Bit-Manipulation, would require special Bit-Manipulation Vector instructions to be added to RVV... all of which would need to AGAIN go through the Extension Proposal process... you can imagine how that would go, and the subsequent cost of maintenance of gcc, binutils and so on as a long-term preliminary (or if the extension to RVV is not accepted, after all the hard work) even a permanent hard-fork.

in other words once you've been through the "Extension Proposal Process" with Simple-V, it need never be done again, not for one single parallel / vector / SIMD instruction, ever again.

that would include for example creating a fixed-function 3D "FP to ARGB" custom instruction. a custom extension with special 3D pipelines would, with Simple-V, not need to also have to worry about how those operations would be parallelised.

this is not a new concept: it's borrowed directly from videocore-iv (which in turn probably borrowed it from somewhere else). videocore-iv call it "virtual parallelism". the Vector Unit actually has a 4-wide FPU for certain heavily-used operations such as ADD, and a ONE wide FPU for less-used operations such as RECIPSQRT.

however at the instruction level each of those operations, regardless of whether they're heavily-used or less-used they appear to be 16 parallel operations all at once, as far as the compiler and assembly writers are concerned. Simple-V just borrows this exact same concept and lets implementors decide where to deploy it, to best advantage.

  1. If it’s a good idea to implement, are there any projects currently working on it?

i haven't been able to find any: if you do please do let me know, i would like to speak to them and find out how much time and money they would need to complete the work.

 If the answer is yes, would you mind mention the project’s name and


 If the answer is no, are there any special reasons that nobody not

implement it yet?

it's damn hard, it requires a lot of resources, and if the idea is to make it entirely libre-licensed and royalty-free there is an extra step required which a proprietary GPU company would not normally do, and that is to follow the example of the BBC when they created their own Video CODEC called Dirac [5].

what the BBC did there was create the algorithm exclusively from prior art and expired patents... they applied for their own patents... and then DELIBERATELY let them lapse. the way that the patent system works, the patents will still be published, there will be an official priority filing date in the patent records with the full text and details of the patents.

this strategy, where you MUST actually pay for the first filing otherwise the records are REMOVED and never published, acts as a way of preventing and prohibiting unscrupulous people from grabbing the whitepapers and source code, and trying to patent details of the algorithm themselves just like Google did very recently [6]

  • [0] https://www.youtube.com/watch?v=7z6xjIRXcp4
  • [1] https://github.com/jbush001/NyuziProcessor/wiki
  • [2] https://github.com/asicguy/gplgpu
  • [3] https://github.com/jbush001/ChiselGPU/
  • [4] http://miaowgpu.org/
  • [5] https://en.wikipedia.org/wiki/Dirac_(video_compression_format)
  • [6] https://yro.slashdot.org/story/18/06/11/2159218/inventor-says-google-is-patenting-his-public-domain-work
  • [7] https://jbush001.github.io/2016/07/24/gplgpu-walkthrough.html
  • [8] https://github.com/hermanhermitage/videocoreiv/wiki/VideoCore-IV-Programmers-Manual
  • [9] libre-riscv.org/simple_v_extension/
  • [10] https://jbush001.github.io/2016/03/02/videocore-qpu-pipeline.html
  • [11] https://jbush001.github.io/2016/02/27/life-of-triangle.html