cuml
livegrep
| cuml | livegrep | |
|---|---|---|
| 10 | 11 | |
| 3,926 | 1,896 | |
| 1.1% | 3.2% | |
| 9.3 | 5.5 | |
| about 8 hours ago | 11 days ago | |
| C++ | C++ | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
cuml
- FLaNK Stack Weekly for 13 November 2023
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Is it possible to run Sklearn models on a GPU?
sklearn can't, bit take a look at cuML (https://github.com/rapidsai/cuml ). It uses the same API as sklearn but executes on GPU.
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[P] Looking for state of the art clustering algorithms
As a companion to the other comments, I'd like to mention that the RAPIDS library cuML provides GPU-accelerated versions of quite a few of the algorithms mentioned in this thread (HDBSCAN, UMAP, SVM, PCA, {Exact, Approximate} Nearest Neighbors, DBSCAN, KMeans, etc.).
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Is there a multi regression model that works on GPU?
CuML
- [D] What's your favorite unpopular/forgotten Machine Learning method?
- Machine Learning with PyTorch and Scikit-Learn – The *New* Python ML Book
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What are the advantages and disadvantages of using GPU for machine learning/ deep learning/ scientific computation over the conventional CPU software acceleration?
Did they implement the clustering algorithm themselves? cuML is a GPU-accelerated scikit-learn-like package that covers many of the common ML algorithms.
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Intel Extension for Scikit-Learn
https://github.com/rapidsai/cuml
> cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU equivalents. For details on performance, see the cuML Benchmarks Notebook.
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GPU Based Kernel-PCA
Cython code
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Python Machine Learning Guy getting started with CUDA. What should I be brushing up on?
Take a look at RAPIDS CUML https://github.com/rapidsai/cuml. It's useful for most common ML algorithms. Feel free to create Github issues for feature requests & bugs.
livegrep
- Livegrep: Interactively Grep Source Code
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Code Search Is Hard
If you ever leave you can use Livegrep, which was based on code-search work done at Google. I personally don't use it right now but it's great and will probably meet all your needs.
[0] https://github.com/livegrep/livegrep
- FLaNK Stack Weekly for 13 November 2023
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Sourcegraph is no longer Open Source
[4] is not really a usable 'product'. Livegrep (https://github.com/livegrep/livegrep) was inspired by it and is very usable.
[3] used to be a Google open source project as well, but it fell out of maintenance, and Sourcegraph took it over. It powers most of the basic regex/literal search in Sourcegraph.
Mozilla's code is searchable in Searchfox (https://searchfox.org/) which uses the indexer from Livegrep, combined with their own Git indexer and language-specific cross reference databases.
OpenGrok (https://github.com/oracle/opengrok) is also rather well known, but I have found it to have a slightly worse UI than alternatives.
- What code search tools do you use at your job?
- Ack is a grep-like source code search tool
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Are there any good full text searching tools? I need to search against a huge amount of source code. I'm using ripgrep. The problem is that every time I search, it has to read every file again, which is kind of slow. Is there a FT searching tool that is designed with source code searching in mind.
Yes, you want https://github.com/livegrep/livegrep
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Facebook open sources Glean: a scalable code search and query engine
If you've not had to deal with a codebase that takes VSCode longer than a few minutes to index, then you're probably outside their initial target market. If you've not had to setup a hosted code search tool (eg livegrep https://github.com/livegrep/livegrep ) because there's just too much code,
- Sourcegraph: Why we're indexing the OSS universe
What are some alternatives?
scikit-learn - scikit-learn: machine learning in Python
Glean - System for collecting, deriving and working with facts about source code.
scikit-learn-intelex - Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
sourcegraph - Code AI platform with Code Search & Cody
scikit-cuda - Python interface to GPU-powered libraries
zoekt - Fast trigram based code search
hummingbird - Hummingbird compiles trained ML models into tensor computation for faster inference.
linguist - Language Savant. If your repository's language is being reported incorrectly, send us a pull request!
cudf - cuDF - GPU DataFrame Library
codesearch - Fork of Google codesearch with more options
evojax
git-peek - git repo to local editor instantly