[GTALUG] Running Dell branded Nvidia gtx 1060 in non-dell system

[D. Hugh Redelmeier]

| From: xerofoify via talk <talk at gtalug.org>

| On Tue, Aug 6, 2019 at 4:23 PM Alex Volkov via talk <talk at gtalug.org> wrote:

| I don't know how much your intending to do with that GPU or otherwise.

He said he wants to do human (himself) learning about machine
learning.  Less cute way of saying this: he want to experiment and
play with ML.

| If your just using Nvidia I can't help
| you as mentioned but if your interested in GPU workloads  was looking
| at the AMDGPU backend for LLVM.

Most people learning (or doing) ML pick a tall stack of software and
the learn almost nothing about the underlaying hardware.  I admint
that sometimes performance issues poke their way through those levels.

If I remember correctly, the base of the stack that Alex was playing
with was Google's TensorFlow.  Of course there is stuff below that but
the less he has to know about it the better.

See Alex's discussion about getting TensorFlow to work on AMD.  If I
understood him correctly (maybe not), the normal route to TesorFlow on
AMD is through ROCm, and that won't work on an APU.  Too bad.

My guess: even if he could run ROCm, he might hit some hangups with
TensorFlow since the most used path to TensorFlow is Nvidia cards and
(I think) Cuda.  It's always easier to follow a well-worn path.

I, on the other hand, think I'm interested in the raw hardware.  I
have not put any time into this but I intend to (one of many things I
want to do).

| Not sure if there is one that targets Nvidia cards but it may be of
| interest to you as you would be able to
| compile directly for the GPU rather than using an API to access it.
| Not sure about Nvidia so double check
| that.

As I understand it:

- LCC targets raw AMD GPU hardware

- that's probably not very useful because runtime support is needed
  for what you could consider OS-like functionality and that isn't
  provided.

  + scheduling

  + communicating with the host computer

  + failure handling and diagnostics

- Separately, a custom version of LCC is used as a code generator
  (partly(?) at runtime!) for OpenCL.  I think that AMD tries to
  "upstream" their LCC changes but this is never soon enough.

- I think that nvidia also has a custom LCC but does not try to
  upsteam all of their goodies (LCC is not copylefted).

I may be wrong about much or all of this.  I would like to know an
accurate, comprehensive, comprehensible source for this kind of
information.

| Here is the official documentation for AMD through:
| https://llvm.org/docs/AMDGPUUsage.html

Thanks.  I'll have a look.

| If your using it for machine learning it may be helpful to be aware of
| it

You'd think so but few seem to bother.  There's enough to get ones
head around at the higher levels of abstraction.

Much ML seems to be done via cook-books.

| Hopefully that helps a little,

I'd love to hear a GTALUG talk about the lower levels.  Perhaps a
lightning talk next week would be a good place to start.