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It is recommanded that one set the environment variable `XLA_PYTHON_CLIENT_PREALLOCATE=false`. By default JAX will pre-allocate 80% of the device's memory. This variable disables the GPU memory preallocation, otherwise running multiple JAX processes may cause OOM. For more information, please refer to [JAX's documentation](https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html) on this matter.
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To scale the workflow using multiple machines through Ray, use the {class}`RayDistributedWorkflow <evox.workflows.RayDistributedWorkflow>` instead of StdWorkflow.
要通过Ray使用多台机器扩展工作流，请使用 {class}`RayDistributedWorkflow <evox.workflows.RayDistributedWorkflow>` 类替代标准工作流StdWorkflow。
First, import `workflows` from evox
首先，从evox中导入'workflows'
then create your algorithm, problem, monitor object as usual.
接下来创建algorithm，problem，monitor对象。
Now use `RayDistributedWorkflow`
现在使用 `RayDistributedWorkflow`
The `RayDistributedWorkflow` also uses the `workflow.step` function to execute iterations. However, under the hood, it employs a distinct approach that allows for the utilization of multiple devices across different machines.
`RayDistributedWorkflow`同样运用 `workflow.step`函数来执行迭代过程。然而，在底层实现上，它采用了一种独特的方法，能够跨多台机器利用多个设备。
It is recommanded that one set the environment variable `XLA_PYTHON_CLIENT_PREALLOCATE=false`. By default JAX will pre-allocate 80% of the device's memory. This variable disables the GPU memory preallocation, otherwise running multiple JAX processes may cause OOM. For more information, please refer to [JAX's documentation](https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html) on this matter.
建议设置环境变量XLA_PYTHON_CLIENT_PREALLOCATE=false。默认情况下，JAX会预先分配设备内存的80%。此变量用于禁用GPU内存预分配，否则运行多个JAX进程可能会导致内存不足（OOM）。有关此事项的更多信息，请参考JAX的文档(https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html) 。
StdWorkflow
工作流
StdWorkflow is short for "Universal Workflow", which aims to use pure JAX to build a workflow that fits any requirement. Since `StdWorkflow` is written in pure JAX, it has less overhead and don't need any additional dependencies.
"StdWorkflow"是“Standard Workflow”的缩写，其目的是使用纯JAX构建一个适应任何需求的工作流。由于StdWorkflow是用纯JAX编写的，它的开销较小，不需要任何额外的依赖。
Use `StdWorkflow` to create an workflow, and use `enable_distributed` and pass in the state to enable this feature.
使用`StdWorkflow`创建一个工作流然后使用`enable_distributed`并且传入相应状态来启用此功能。
Then, at the start of your program, before any JAX function is called, do this:
在你的程序开始之前进行的任何JAX函数调用，需要做这些操作：
In this system, the `coordinator` serves as the primary or head node. The total number of participating processes is indicated by `num_process`. The process with `process_id=0` acts as the coordinator.
在这个系统中，“coordinator”（协调器）充当主节点或头节点的角色。参与进程的总数由num_process指示。具有process_id=0的进程充当协调器。

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Translation added

  1. EvoX
  2. EvoX
  3. Chinese (Simplified)
It is recommanded that one set the environment variable `XLA_PYTHON_CLIENT_PREALLOCATE=false`. By default JAX will pre-allocate 80% of the device's memory. This variable disables the GPU memory preallocation, otherwise running multiple JAX processes may cause OOM. For more information, please refer to [JAX's documentation](https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html) on this matter.
建议设置环境变量XLA_PYTHON_CLIENT_PREALLOCATE=false。默认情况下，JAX会预先分配设备内存的80%。此变量用于禁用GPU内存预分配，否则运行多个JAX进程可能会导致内存不足（OOM）。有关此事项的更多信息，请参考JAX的文档(https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html) 。
5 months ago
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  1. EvoX
  2. EvoX
  3. Chinese (Simplified)
It is recommanded that one set the environment variable `XLA_PYTHON_CLIENT_PREALLOCATE=false`. By default JAX will pre-allocate 80% of the device's memory. This variable disables the GPU memory preallocation, otherwise running multiple JAX processes may cause OOM. For more information, please refer to [JAX's documentation](https://jax.readthedocs.io/en/latest/gpu_memory_allocation.html) on this matter.
 
7 months ago
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../../source/guide/user/3-distributed.md:60
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