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Add basic documentation structure (#1715)

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* Add basic documentation structure

* Add terminology placeholder

* Add codegen placeholder

* Create template for each page
This commit is contained in:
Bartłomiej Kocot
2024-12-04 00:46:47 +01:00
committed by GitHub
parent 08d5c02c37
commit 5affda819d
10 changed files with 62 additions and 26 deletions
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34
README.md
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@@ -26,23 +26,15 @@ The current CK library is structured into four layers:
## General information
To build our documentation locally, use the following code:
``` bash
cd docs
pip3 install -r sphinx/requirements.txt
python3 -m sphinx -T -E -b html -d _build/doctrees -D language=en . _build/html
```
You can find a list of our developers and contributors on our [Contributors](/CONTRIBUTORS.md) page.
```note
If you use CK, cite us as follows:
* [Realizing Tensor Operators Using Coordinate Transformations and Tile Based Programming](???):
This paper will be available on arXiv soon.
* [CITATION.cff](/CITATION.cff)
```
* [CK supported operations](include/ck/README.md)
* [CK Tile supported operations](include/ck_tile/README.md)
* [CK wrapper](client_example/25_wrapper/README.md)
* [CK codegen](codegen/README.md)
* [CK profiler](profiler/README.md)
* [Examples (Custom use of CK supported operations)](example/README.md)
* [Client examples (Use of CK supported operations with instance factory)](client_example/README.md)
* [Terminology](/TERMINOLOGY.md)
* [Contributors](/CONTRIBUTORS.md)
CK is released under the **[MIT license](/LICENSE)**.
@@ -137,6 +129,14 @@ Docker images are available on [DockerHub](https://hub.docker.com/r/rocm/composa
You can find instructions for running ckProfiler in [profiler](/profiler).
* Build our documentation locally:
``` bash
cd docs
pip3 install -r sphinx/requirements.txt
python3 -m sphinx -T -E -b html -d _build/doctrees -D language=en . _build/html
```
Note the `-j` option for building with multiple threads in parallel, which speeds up the build significantly.
However, `-j` launches unlimited number of threads, which can cause the build to run out of memory and
crash. On average, you should expect each thread to use ~2Gb of RAM.