mirror of
https://github.com/ROCm/ROCm.git
synced 2026-01-06 21:33:57 -05:00
Taichi removed (#5801)
This commit is contained in:
Pratik Basyal
@@ -465,8 +465,6 @@ TPS
|
||||
TPU
|
||||
TPUs
|
||||
TSME
|
||||
Taichi
|
||||
Taichi's
|
||||
Tagram
|
||||
TensileLite
|
||||
TensorBoard
|
||||
|
||||
@@ -34,7 +34,6 @@ ROCm Version,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6
|
||||
:doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>` [#stanford-megatron-lm_compat]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,85f95ae,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat]_,N/A,N/A,N/A,2.4.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,
|
||||
:doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>` [#megablocks_compat]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.7.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`Taichi <../compatibility/ml-compatibility/taichi-compatibility>` [#taichi_compat]_,N/A,N/A,N/A,N/A,N/A,1.8.0b1,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`Ray <../compatibility/ml-compatibility/ray-compatibility>` [#ray_compat]_,N/A,N/A,2.48.0.post0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`llama.cpp <../compatibility/ml-compatibility/llama-cpp-compatibility>` [#llama-cpp_compat]_,N/A,N/A,N/A,b5997,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
`ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.2,1.2,1.2,1.2,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.14.1,1.14.1
|
||||
|
||||
|
@@ -245,7 +245,6 @@ Expand for full historical view of:
|
||||
.. [#stanford-megatron-lm_compat] Stanford Megatron-LM is only supported on ROCm 6.3.0.
|
||||
.. [#dgl_compat] DGL is only supported on ROCm 6.4.0.
|
||||
.. [#megablocks_compat] Megablocks is only supported on ROCm 6.3.0.
|
||||
.. [#taichi_compat] Taichi is only supported on ROCm 6.3.2.
|
||||
.. [#ray_compat] Ray is only supported on ROCm 6.4.1.
|
||||
.. [#llama-cpp_compat] llama.cpp is only supported on ROCm 6.4.0.
|
||||
.. [#kfd_support-past-60] As of ROCm 6.4.0, forward and backward compatibility between the AMD Kernel-mode GPU Driver (KMD) and its user space software is provided up to a year apart. For earlier ROCm releases, the compatibility is provided for +/- 2 releases. The tested user space versions on this page were accurate as of the time of initial ROCm release. For the most up-to-date information, see the latest version of this information at `User and kernel-space support matrix <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/reference/user-kernel-space-compat-matrix.html>`_.
|
||||
|
||||
@@ -1,76 +0,0 @@
|
||||
:orphan:
|
||||
|
||||
.. meta::
|
||||
:description: Taichi compatibility
|
||||
:keywords: GPU, Taichi compatibility
|
||||
|
||||
.. version-set:: rocm_version latest
|
||||
|
||||
*******************************************************************************
|
||||
Taichi compatibility
|
||||
*******************************************************************************
|
||||
|
||||
`Taichi <https://www.taichi-lang.org/>`_ is an open-source, imperative, and parallel
|
||||
programming language designed for high-performance numerical computation.
|
||||
Embedded in Python, it leverages just-in-time (JIT) compilation frameworks such as LLVM to accelerate
|
||||
compute-intensive Python code by compiling it to native GPU or CPU instructions.
|
||||
|
||||
Taichi is widely used across various domains, including real-time physical simulation,
|
||||
numerical computing, augmented reality, artificial intelligence, computer vision, robotics,
|
||||
visual effects in film and gaming, and general-purpose computing.
|
||||
|
||||
* ROCm support for Taichi is hosted in the official `https://github.com/ROCm/taichi <https://github.com/ROCm/taichi>`_ repository.
|
||||
* Due to independent compatibility considerations, this location differs from the `https://github.com/taichi-dev <https://github.com/taichi-dev>`_ upstream repository.
|
||||
* Use the prebuilt :ref:`Docker image <taichi-docker-compat>` with ROCm, PyTorch, and Taichi preinstalled.
|
||||
* See the :doc:`ROCm Taichi installation guide <rocm-install-on-linux:install/3rd-party/taichi-install>` to install and get started.
|
||||
|
||||
.. note::
|
||||
|
||||
Taichi is supported on ROCm 6.3.2.
|
||||
|
||||
Supported devices and features
|
||||
===============================================================================
|
||||
There is support through the ROCm software stack for all Taichi GPU features on AMD Instinct MI250X and MI210X series GPUs with the exception of Taichi’s GPU rendering system, CGUI.
|
||||
AMD Instinct MI300X series GPUs will be supported by November.
|
||||
|
||||
.. _taichi-recommendations:
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
To fully leverage Taichi's performance capabilities in compute-intensive tasks, it is best to adhere to specific coding patterns and utilize Taichi decorators.
|
||||
A collection of example use cases is available in the `https://github.com/ROCm/taichi_examples <https://github.com/ROCm/taichi_examples>`_ repository,
|
||||
providing practical insights and foundational knowledge for working with the Taichi programming language.
|
||||
You can also refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`_ to search for Taichi examples and best practices to optimize your workflows on AMD GPUs.
|
||||
|
||||
.. _taichi-docker-compat:
|
||||
|
||||
Docker image compatibility
|
||||
================================================================================
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
|
||||
<i class="fab fa-docker"></i>
|
||||
|
||||
AMD validates and publishes ready-made `ROCm Taichi Docker images <https://hub.docker.com/r/rocm/taichi/tags>`_
|
||||
with ROCm backends on Docker Hub. The following Docker image tags and associated inventories
|
||||
represent the latest Taichi version from the official Docker Hub.
|
||||
The Docker images have been validated for `ROCm 6.3.2 <https://rocm.docs.amd.com/en/docs-6.3.2/about/release-notes.html>`_.
|
||||
Click |docker-icon| to view the image on Docker Hub.
|
||||
|
||||
.. list-table::
|
||||
:header-rows: 1
|
||||
:class: docker-image-compatibility
|
||||
|
||||
* - Docker image
|
||||
- ROCm
|
||||
- Taichi
|
||||
- Ubuntu
|
||||
- Python
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
<a href="https://hub.docker.com/layers/rocm/taichi/taichi-1.8.0b1_rocm6.3.2_ubuntu22.04_py3.10.12/images/sha256-e016964a751e6a92199032d23e70fa3a564fff8555afe85cd718f8aa63f11fc6"><i class="fab fa-docker fa-lg"></i> rocm/taichi</a>
|
||||
- `6.3.2 <https://repo.radeon.com/rocm/apt/6.3.2/>`_
|
||||
- `1.8.0b1 <https://github.com/taichi-dev/taichi>`_
|
||||
- 22.04
|
||||
- `3.10.12 <https://www.python.org/downloads/release/python-31012/>`_
|
||||
@@ -100,7 +100,6 @@ article_pages = [
|
||||
{"file": "compatibility/ml-compatibility/stanford-megatron-lm-compatibility", "os": ["linux"]},
|
||||
{"file": "compatibility/ml-compatibility/dgl-compatibility", "os": ["linux"]},
|
||||
{"file": "compatibility/ml-compatibility/megablocks-compatibility", "os": ["linux"]},
|
||||
{"file": "compatibility/ml-compatibility/taichi-compatibility", "os": ["linux"]},
|
||||
{"file": "compatibility/ml-compatibility/ray-compatibility", "os": ["linux"]},
|
||||
{"file": "compatibility/ml-compatibility/llama-cpp-compatibility", "os": ["linux"]},
|
||||
{"file": "how-to/deep-learning-rocm", "os": ["linux"]},
|
||||
|
||||
@@ -98,18 +98,6 @@ The table below summarizes information about ROCm-enabled deep learning framewor
|
||||
|
||||
<a href="https://github.com/ROCm/megablocks"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - `Taichi <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/taichi-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/taichi-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/taichi-install.html#use-a-prebuilt-docker-image-with-taichi-pre-installed>`__
|
||||
- `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/taichi-install.html#use-a-wheels-package>`__
|
||||
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/taichi"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - `Ray <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/ray-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
|
||||
@@ -93,7 +93,7 @@ The following table shows whether a ROCm library is graph-safe.
|
||||
- ⚠️ (experimental)
|
||||
*
|
||||
- `rocThrust <https://github.com/ROCm/rocThrust>`_
|
||||
- ❌ (see :doc:`details <rocthrust:hipgraph-support>`)
|
||||
- ❌ (see :doc:`details <rocthrust:reference/rocThrust-hipgraph-support>`)
|
||||
*
|
||||
- `rocWMMA <https://github.com/ROCm/rocWMMA>`_
|
||||
- ❌
|
||||
|
||||
@@ -723,7 +723,7 @@ detailed description.
|
||||
- ❌/❌
|
||||
|
||||
*
|
||||
- :doc:`MIGraphX <amdmigraphx:reference/cpp>`
|
||||
- :doc:`MIGraphX <amdmigraphx:reference/MIGraphX-cpp>`
|
||||
- ✅/✅
|
||||
- ✅/✅
|
||||
- ✅/✅
|
||||
@@ -863,7 +863,7 @@ detailed description.
|
||||
- ✅/✅
|
||||
|
||||
*
|
||||
- :doc:`MIGraphX <amdmigraphx:reference/cpp>`
|
||||
- :doc:`MIGraphX <amdmigraphx:reference/MIGraphX-cpp>`
|
||||
- ✅/✅
|
||||
- ✅/✅
|
||||
- ✅/✅
|
||||
|
||||
@@ -43,8 +43,6 @@ subtrees:
|
||||
title: DGL compatibility
|
||||
- file: compatibility/ml-compatibility/megablocks-compatibility.rst
|
||||
title: Megablocks compatibility
|
||||
- file: compatibility/ml-compatibility/taichi-compatibility.rst
|
||||
title: Taichi compatibility
|
||||
- file: compatibility/ml-compatibility/ray-compatibility.rst
|
||||
title: Ray compatibility
|
||||
- file: compatibility/ml-compatibility/llama-cpp-compatibility.rst
|
||||
|
||||
Reference in New Issue
Block a user