herbie
mamba
herbie | mamba | |
---|---|---|
6 | 34 | |
729 | 6,343 | |
1.4% | 3.9% | |
9.9 | 9.5 | |
3 days ago | 7 days ago | |
HTML | C++ | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
herbie
- Herbie: Find and fix floating-point accuracy problems
-
Towards a New SymPy
The herbie project using egraphs to explore different ways of rewriting floating point expressions. https://herbie.uwplse.org/ One can also write custom rulesets in egglog (a new egraph rewriting system / language / datalog) https://egraphs-good.github.io/egglog/?example=herbie
The approach is not yet anywhere near being able to touch all the domains sympy can handle. Destructive term rewriting tends to be a bit more forgiving to unsoundness in the rules and still returning roughly meaningful results. EGraph rewriting (and other automated reasoning systems) tend to just return junk as soon as you aren't careful about your semantics. Associativity and commutativity are ubiquitous in CAS applications and encoding these concepts in general purpose terms is rather unsatisfying. The post above emphasizes specialty methods for polynomials, which it would be desirable to find a clean way to integrate into egraph techniques. Variable binding (which is treated in a rather mangled form in CAS systems) is seemingly important for treating summation, differentiation, and integration correctly. The status of doing variable binding efficiently and correctly in egraphs is also unclear imo.
-
Q: Automated floating point error analysis
As a starting point, check Herbie: https://herbie.uwplse.org/
-
Someone’s Been Messing with My Subnormals
Here is a really cool automatic tool that rewrites floating point expressions to be more accurate: https://herbie.uwplse.org/
-
Multiple precision floating point library
On a related note, see tools like Herbie which rewrite floating point expressions to improve accuracy without altering the underlying data-type. It's worth being aware that sometimes you get really bad diminishing returns from using bigger floats and what you really need to do is to rewrite the calculation to avoid a weakness of floating point representation, see numerically unstable calculations.
- Herbie – optimize floating-point expressions for accuracy
mamba
-
Minimal implementation of Mamba, the new LLM architecture, in 1 file of PyTorch
>"everyone" seems to know Mamba. I never heard of Mamba
Only the "everybody who knows what mamba is" are the ones upvoting and commenting. Think of all the people who ignore it. For me, Mamba is the faster version of Conda [1], and that's why I clicked on the article.
https://github.com/mamba-org/mamba
-
Towards a New SymPy
Yes, this is a big disadvantage. But have you tried Mamba that aims at implementing Anaconda more efficiently? It works really well in most cases.
https://mamba.readthedocs.io/
-
Why are the bioconda bioconductor packages so slow to update?
Because conda is very slow at resolving dependencies. Mamba (https://github.com/mamba-org/mamba) is faster if that is your goal
-
Is pip gaining on conda for python libs?
use mamba instead
-
Real-world examples of std::expected in codebases?
We started using tl::expected in https://github.com/mamba-org/mamba/ since the beginning of this year and some other related projects like https://github.com/mamba-org/powerloader . I don't know much other big open-source codebases that use that specific lib.
- Mamba: A Drop-In Replacement for Conda Written in C++
-
What's Great about Julia?
Great writeup. Minor comment about the portion of the post mentioning Conda being glacially slow: Mamba [1] is a much better drop-in replacement written in C++. Not only is it significantly faster, but error messages are much more sane and helpful.
That being said, I do agree that Pkg.jl is much more sleek and modern than Conda/Mamba.
[1]: https://github.com/mamba-org/mamba
- Mamba Reaches 1.0
-
Given Rust’s rapidly growing popularity and wide range of use cases, it seems almost inevitable that it will overtake Python in the near future.
I thought that python could live a little longer when I learned about mamba. But then I found out it is written in C++? Why write a package manager for a dying language in a language that is almost dead???
-
Does anyone use virtual environments (Conan's virtual env. or Conda's) for C++
Yes, I use Conda enviroments (actually I use Mamba to manage them now).
What are some alternatives?
bigint-benchmark-rs - Bechmarks for Rust big integer implementations
miniforge - A conda-forge distribution.
egglog - egraphs + datalog!
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
ibig-rs - A big integer library in Rust with good performance.
pip - The Python package installer
MuladdMacro.jl - This package contains a macro for converting expressions to use muladd calls and fused-multiply-add (FMA) operations for high-performance in the SciML scientific machine learning ecosystem
pyenv - Simple Python version management
r6rs
conda-lock - Lightweight lockfile for conda environments
pyre-check - Performant type-checking for python.
quetz - The Open-Source Server for Conda Packages