Mkl.net
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Optimum | 1,908 |  | 53 | 3 months ago | 53 | December 06, 2023 | 295 | apache-2.0 | Python | |
| 🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools | ||||||||||
| Tick | 453 |  | 1 | 1 | 3 months ago | 23 | May 24, 2020 | 78 | bsd-3-clause | Python |
| Module for statistical learning, with a particular emphasis on time-dependent modelling | ||||||||||
| Optimum Intel | 268 | 3 months ago | 30 | apache-2.0 | Python | |||||
| 🤗 Optimum Intel: Accelerate inference with Intel optimization tools | ||||||||||
| Mkl.net | 132 | | 6 | 4 months ago | 28 | August 21, 2023 | apache-2.0 | C# | ||
| A simple cross platform .NET API for Intel MKL | ||||||||||
| Windows10 Latency Optimization | 122 | a year ago | 2 | Batchfile | ||||||
| :rocket: Windows 10 Latency Optimization – гайд про оптимизацию Windows и уменьшение задержек (latency, input-lag, throttling и stuttering), а так же про повышение FPS. | ||||||||||
| Mlsl | 107 | a year ago | 3 | other | C++ | |||||
| Intel(R) Machine Learning Scaling Library is a library providing an efficient implementation of communication patterns used in deep learning. | ||||||||||
| Yask | 98 | 5 months ago | 18 | other | C++ | |||||
| YASK--Yet Another Stencil Kit: a domain-specific language and framework to create high-performance stencil code for implementing finite-difference methods and similar applications. | ||||||||||
| Iodlr | 83 | a year ago | 1 | C | ||||||
| Tools and Reference Code for Intel Optimizations (eg Large Pages) | ||||||||||
| Robustgnss | 55 | 5 years ago | 3 | mit | C++ | |||||
| Robust GNSS Processing With Factor Graphs | ||||||||||
| Fastmat | 23 |  | 1 | a year ago | 16 | March 04, 2021 | 15 | apache-2.0 | Cython | |
| A library to build up lazily evaluated expressions of linear transforms for efficient scientific computing. | ||||||||||
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