HackerTrans
TopNewTrendsCommentsPastAskShowJobs

CoreyFieldens

no profile record

Submissions

Mojo clarifies meaning of "Python superset"

github.com
24 points·by CoreyFieldens·2 वर्ष पहले·5 comments

Julia 1.10

docs.julialang.org
192 points·by CoreyFieldens·3 वर्ष पहले·99 comments

What's the deal with Julia binary sizes? [video]

youtube.com
6 points·by CoreyFieldens·3 वर्ष पहले·1 comments

Key Announcements from ModCon 2023

modular.com
5 points·by CoreyFieldens·3 वर्ष पहले·0 comments

comments

CoreyFieldens
·2 वर्ष पहले·discuss
I think I would agree with you. In my opinion, that already exists and is decently mature. CuPy [0] for Python and CUDA.jl [1] for Julia are both excellent ways to interface with GPU that don't require you to get into the nitty gritty of CUDA. Both do their best to keep you at the Array-level abstraction until you actually need to start writing kernels yourself and even then, it's pretty simple. They took a complete GPU novice like me and let me to write pretty performant kernels without having to ever touch raw CUDA.

[0] https://cupy.dev/

[1] https://cuda.juliagpu.org/stable/
CoreyFieldens
·2 वर्ष पहले·discuss
As someone who has been playing around with (and enjoying) Mojo, I have my doubts about how useful Mojo will end up being for your average scientist. You can't get performant code out of Mojo if you're not willing to learn some deeper programming concepts like SIMD or tiling.

I don't have the exact quote on hand, but in the Mojo Discord, Chris Latner explicitly said he wants no "compiler magic" in Mojo. With that idea in mind, Mojo makes it a lot easier to do optimizations like SIMD vectorization by hand, but you will still have to do it manually. My guess is that many scientists who don't like programming would find it annoying to hand-write those kinds of optimizations. If you want a language that gives you nice, performant code on your first attempt, Julia is always a decent option.

These are the docs for some of Mojo's higher order functions that implement vectorization, parallelization, tiling, loop switching, etc. https://docs.modular.com/mojo/stdlib/algorithm/functional

I do think they are a good idea and relatively easy to use; I'm just not convinced that the non-programmer scientist will like them.
CoreyFieldens
·3 वर्ष पहले·discuss
One thing that concerns me so far is that nothing put out by Mojo or said by any of the Modular leaders indicates that the language itself will ever be open sourced. The Mojo FAQ says:

"Over time we expect to open-source core parts of Mojo, such as the standard library."

In the most recent keynote, Chris Latner said the standard library will be open-sourced starting next year. I have never seen anything about the actual rest of the language. I worry that they don't actually plan to open-source all the core parts of Mojo and they're just letting others put words in their mouth to hype up the language.
CoreyFieldens
·3 वर्ष पहले·discuss
> "Drought and heat have already reduced global cereal production by as much as 10 percent in recent years, according to Steffen."

I'm not sure how they define this because I find conflicting info elsewhere. Our world in data has global cereal production only going up [0]. That data only goes until 2021 so there could have been a decrease in 2022 but then it would probably be wrong to say "recent years".

[0] https://ourworldindata.org/grapher/cereal-production?tab=cha...