# SOME DESCRIPTIVE TITLE.
# Copyright (C) 1999-2020, The Alibaba Group Holding Ltd.
# This file is distributed under the same license as the mars package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 2020.
#
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msgid ""
msgstr ""
"Project-Id-Version: mars 0.5.0a2\n"
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"POT-Creation-Date: 2021-08-04 18:24+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
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"Generated-By: Babel 2.9.1\n"

#: ../../source/getting_started/gpu.rst:4
msgid "Mars on GPU"
msgstr "GPU 指南"

#: ../../source/getting_started/gpu.rst:6
msgid ""
"Mars can run on NVIDIA GPUs. However, extra requirements are necessary "
"for different modules."
msgstr ""
"Mars 可以利用 NVIDIA 显卡执行，但对于 Mars 里的不同模块，需要一些必要的"
"依赖。"

#: ../../source/getting_started/gpu.rst:9
msgid "Installation"
msgstr "安装"

#: ../../source/getting_started/gpu.rst:11
msgid ""
"For Mars tensors, CuPy is required. Assuming that your CUDA driver is "
"10.1, install cupy via:"
msgstr "Mars tensor 依赖于 CuPy，假设你的 CUDA 驱动是 10.1，用如下方式安装 cupy："

#: ../../source/getting_started/gpu.rst:17
msgid ""
"Refer to `install cupy <https://docs-"
"cupy.chainer.org/en/stable/install.html>`_ for more information."
msgstr ""
"参考 `安装 cupy <https://docs-cupy.chainer.org/en/stable/install.html>`_ "
"获取更多信息。"

#: ../../source/getting_started/gpu.rst:20
msgid "For Mars DataFrame, RAPIDS cuDF is required. Install cuDF via conda:"
msgstr "Mars DataFrame 依赖于 RAPIDS cuDF，使用 conda 安装 cuDF："

#: ../../source/getting_started/gpu.rst:27
msgid ""
"Refer to `install cuDF <https://rapids.ai/start.html#get-rapids>`_ for "
"more information."
msgstr "参考 `安装 cuDF <https://rapids.ai/start.html#get-rapids>`_ 获取更多信息。"

#: ../../source/getting_started/gpu.rst:30
msgid "Mars tensor on CUDA"
msgstr "CUDA 上运行 Mars tensor"

#: ../../source/getting_started/gpu.rst:32
msgid ""
"Tensor can be created on GPU via specifying ``gpu=True``. Methods "
"included are mentioned in :ref:`tensor creation <tensor_creation>` and "
":ref:`random data <tensor_random>`."
msgstr ""
"Tensor 通过指定 ``gpu=True`` 来指定在 GPU 上创建。:ref:`创建 Tensor <"
"tensor_creation>` 和 :ref:`随机抽样 <tensor_random>` 中的方法都支持这个"
"参数。"

#: ../../source/getting_started/gpu.rst:42
msgid ""
"Remember that when creating tensors, no GPU memory allocation happens "
"yet. When ``.execute()`` is triggered, real memory allocation and "
"computation on GPU will happen then."
msgstr ""
"记住，创建 tensor 的时候，并没有实际的 GPU 内存分配。当 ``.execute()`` "
"触发的时候，GPU 上才会有真正的内存分配和计算。"

#: ../../source/getting_started/gpu.rst:45
msgid ""
"For a tensor on host memory, call ``.to_gpu()`` to tell Mars to move data"
" to GPU."
msgstr "对于一个主存上创建的 tensor，调用 ``.to_gpu()`` 来指示把数据移至 GPU。"

#: ../../source/getting_started/gpu.rst:53
#: ../../source/getting_started/gpu.rst:80
msgid "Call ``.to_cpu()`` to tell Mars to move data to host memory."
msgstr "调用 ``.to_cpu()`` 来指示把数据移到主存。"

#: ../../source/getting_started/gpu.rst:61
msgid "Mars DataFrame on CUDA"
msgstr "CUDA 上运行 Mars DataFrame"

#: ../../source/getting_started/gpu.rst:63
msgid "Mars can read CSV files into GPU directly."
msgstr "Mars 可以直接读取 CSV 文件至显存。"

#: ../../source/getting_started/gpu.rst:71
msgid ""
"For a DataFrame that on host memory, call ``.to_gpu()`` to tell Mars to "
"move data to GPU."
msgstr "对于主存上的 DataFrame，调用 ``.to_gpu()`` 指示把数据移至显存。"

#: ../../source/getting_started/gpu.rst:89
msgid "Multiple GPU"
msgstr "多卡"

#: ../../source/getting_started/gpu.rst:91
msgid ""
"For Mars tensor and DataFrame, multiple GPUs on a single machine can be "
"utilized."
msgstr "对于 Mars tensor 和 DataFrame，可以利用单机多卡。"

#: ../../source/getting_started/gpu.rst:99
msgid ""
"The code above will try to leverage all the visible GPU cards to perform "
"computation."
msgstr "如上代码会利用所有可见的显卡来计算。"

#: ../../source/getting_started/gpu.rst:101
msgid ""
"If you want to limit computation to some GPU cards, you can set "
"environment variable ``CUDA_VISIBLE_DEVICES``."
msgstr "如果要限制使用的显卡，可以设置环境变量 ``CUDA_VISIBLE_DEVICES``。"

#: ../../source/getting_started/gpu.rst:108
msgid ""
"This will limit the ipython to GPU 0, 3 and 5 only. Thus all the Mars "
"tensor executed in the ipython will run on the visible GPUs only."
msgstr ""
"这会让 ipython 只使用 0、3、5 显卡。因此在 ipython 中跑的 Mars tensor "
"任务只会使用这些显卡。"

#: ../../source/getting_started/gpu.rst:112
msgid "Distributed"
msgstr "分布式"

#: ../../source/getting_started/gpu.rst:114
msgid ""
"For Mars supervisor, the command to start is the same. Refer to "
":ref:`deploy`."
msgstr "Mars Supervisor 启动命令完全相同，参考 :ref:`deploy`。"

#: ../../source/getting_started/gpu.rst:116
msgid "For Mars worker, one worker can be bind to one or multiple GPUs."
msgstr "Mars worker 可以绑定到一个或者多张显卡。"

#: ../../source/getting_started/gpu.rst:118
msgid "Basic command to start a worker that binds to some GPU is:"
msgstr "绑定到某个显卡的 Worker 可以按如下命令启动："

#: ../../source/getting_started/gpu.rst:124
msgid "The worker started will be bind to GPU 0, 1 and 2."
msgstr "这个 Worker 会绑定到显卡 0、1 和 2。"

#: ../../source/getting_started/gpu.rst:126
msgid ""
"Refer to :ref:`extra arguments for starting worker "
"<deploy_extra_arguments>` for more information."
msgstr "参考 :ref:`启动 Worker 的其他命令 <deploy_extra_arguments>` 获取更多信息。"

#: ../../source/getting_started/gpu.rst:128
msgid "Once a Mars cluster is started, you can run the code below."
msgstr "一旦一个集群创建好了，可以运行如下代码。"

