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I would like to recommend "Understanding UNIX/LINUX Programming: A Guide to Theory and Practice" for beginners.

You can download source code I assembled https://github.com/bssrdf/UnderstandingUnixLinuxProgramming


Indeed. Even a simple 'wc -l' type operation can benefit from SIMD [0]

[0]https://x.com/cloud11665/status/1799534538873290993


Just finished writing [0] about Blender's USD import issue.

[0] - https://news.ycombinator.com/item?id=36947946


That improvement sounds great. Any chance that’s up as a PR to blender?


Excited to see this potentially integrated into FreeCAD. It is already very good at utilizing assets from other applications like Blender, and producing assets that can be used in other applications.

It would really help smooth out some wrinkles in the building industry if we could freely interoperate with each other while using different applications. I can't afford (stomach) anything but FreeCAD for my building projects. All the engineers I work with use autocad.


I didn't submit the PR yet, but opened an issue which has not been picked up. Maybe most of the USD files used in Blender do not trigger the O(N^2) behavior.


Possibly. Do you have a link to the PR handy?


I don't think a PR is ready. My solution does not fully solve the problem. It requires more thoughts. Thanks.


Interesting. Since the list is sorted, is the insertion still a linear search (O(N)) or now a binary search (O(log(N))? Or did I misunderstand something? Also, why is it not a hash table (almost O(1))?


Good point, I have the same doubt. Even if it is sorted, you still cannot do binary search on it unless using some skip list ideas. In fact, the code right now is doing linear search to find the ID given a name.

TBH, I don't fully understand how the ID linked list is utilized in Blender and why it needs to be sorted by names. It seems some other data structure could also work, unless I missed something.


Oh is it an actual linked list and not an array?


Yes, actually it is a doubly linked list.


This was a great read, thanks for sharing.


Wow, thanks!


The key word: TUNING. Every climate model has tons of tunable parameters, many of which are not from first principles. They are empirical, observed some years ago over some remote locations, but now applied globally as the truth.


I implemented radix sort in cpython [0] and did some simple benchmarking comparing to python' built-in sort (Timsort I believe). It is indeed faster.

[0] https://github.com/bssrdf/RadixSortPy


This book <<The Nature of Computation>>[0] has the best explanation I have ever seen.

[0]: https://www.amazon.com/Nature-Computation-Cristopher-Moore-d...


You can even play with the algorithm they used "The Affine Particle-In-Cell Method" using the code discussed here

https://news.ycombinator.com/item?id=13325190


Kajiya's rendering equation


Still debating whether I should start with An Introduction to Statistical Learning (ISL) or Bishop's Pattern Recognition and Machine Learning (PRML). I really don't like using R (always a python person). Both have rave reviews on Amazon. Any thoughts?


Because it is Elon Musk?


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