Hi Matthew,
I hate to say I'm still a noob in the implementation details of Numpy, I
just got an interpreter for sth else working, and suddenly realized it
can make seemingly better magic methods in Python spirit.
Repa and Accelerate per my learning so far, are focused on loop-fusion,
i.e. optimization after all intended computations have been expressed
and composed together, this seems some different from Numpy/Pandas
tradition to implement doable things ex ante, and let the users do
things interactively ad-hoc. That said, so I feel Repa will do composed
computations more speedy, once properly organized. And with Accelerate,
since it does GPU natively, I do feel a sure thing for it to excel CPU
implementations.
btw I'm not a native English speaker, please don't hesitate to ask me to
make myself clearer in my wordings, I'm aware of my flaws in English skills.
btw I'm a believer that Brain-Computer-Interface ought to happen sooner,
especially non-intrusive ones, I can't wait to program such interfaces
for great good and fun. I see you are pioneering in this area, take my
admiring, and I started following you on github, looking forward to hear
from you more.
btw I'm behind China's Great Fire Wall, access to some western sites are
banned badly at times, that will explain why I can be unresponsive some
times.
Cheers,
Compl
On 2020/1/21 下午10:20, Matthew Brett wrote:
Hi,
On Mon, Jan 20, 2020 at 3:00 PM YueCompl <compl....@icloud.com> wrote:
Hello folks,
Myself a long time Numpy user, and recently done some Haskell stuff,
Please have a look at
https://github.com/e-wrks/edh/tree/master/Tour#defining-more-magic-methods and
https://github.com/e-wrks/edh/tree/master/Tour#indexing , any interest to port
Numpy to Haskell,
with http://hackage.haskell.org/package/accelerate and/or
http://hackage.haskell.org/package/repa doing the number crunching?
Interesting - do you have any feeling for the differences in speed for
Haskell accelerate array processing as compared to Numpy with default
OpenBLAS?
Cheers,
Matthew
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