Hey Paul, Thanks a lot uh enjoy the speech. So you
just had a quick couple of questions for people that
are viewing this online. Just a general question for
the OpenCL is there any other I guess advantage to
using it other than its portability? Mm It would
depend on who you talk to. Um Obviously the
major advantage is uh is just portability um some would
complain that it's actually quite a bit lower level than
CUDA, um which makes it not as useful,
but yeah, no, the major advantage is its portability.
Yeah, absolutely. Okay. Is uh, does CUDA
have sort of some features. So
I'm just trying to think of uh talked a lot
about the applications that you took in and try to
convert and out of all those applications you said about
90% or so we're completely translated and then a little
bit about 10% you still needed to translate
manually. Was that specific to NVIDIA or um was
that across multiple graphic cards? Uh well,
uh the percentage of the percentage of code that
we didn't translate meant that there were still some CUDA
structures in the output OpenCL so no matter what
you were trying to target, you'd have to convert
those to OpenCL by hand. Um but so
yeah, once once you could fix those CUDA translations into
OpenCL, it would it would be fine for
whatever device other than what I mentioned to Dr. Ribbons
about the work level synchronization. So other than the
workload of synchronization, it should output the same performance
across all cards. No, it should output the
correct result. But for every different kind of architecture
going to target, you need to manually optimize for
that target still. Is a converter going to be when
when it's publicly available or when it's released, is
going to have different versions targeting different specific uh platforms
or uh graphic cards? As as it's as it's going to be
released next month? No, it will, it
will just be focused on providing that functional portability so
that you can make sure you get the same result,
but you can vision that several years down the
road. Once we get those architectural where optimizations in,
then we'd like to have yes, multiple flavors
of cuticle for targeting, saying AMG GPU versus targeting
Intel CPU. Okay. So would you say
that uh a CUDA programming right now could use it
or when it comes out and effortlessly use it to
convert their code? Uh not to a large scale
application, but it's sort of something that averaging to
the same sort of programs that you tested out
yourself. Absolutely. I mean, if you're a
student and you've got an academic prototype, the biggest
code we did was 17,000 lines of code and we
only had to change about 1700 of them afterwards.
So it might take you a few weeks to work
through the remaining translations. But yes, any CUDA
programmer, um the OpenCL Model
is very similar to CUDA. So even if you've
never programmed it in it before, it's pretty easy
to grasp if you've already had a background in CUBA
so you can translate and then run just fine,
awesome. And what do you think the biggest challenges
in the upcoming months with this project? The biggest,
honestly, the biggest challenge for this up in
the upcoming months is finding another student to work on
it. We don't have anybody in the pipeline right
now that's really like gung ho about it.
Um Got money to spend. There's tons of work
to be done, but we just need a student
that's going to be interested in and carrying the project
on. All right, great. Well, thanks
a lot Paul, really good speech. Take care.
Thanks. Bye bye.