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docs/source/en/basics/command_line_tool.md

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+# Command Line Tool
+
+Author: Shenggui Li
+
+**Prerequisite:**
+- [Distributed Training](../concepts/distributed_training.md)
+- [Colossal-AI Overview](../concepts/colossalai_overview.md)
+
+## Introduction
+
+Colossal-AI provides command-line utilities for the user.
+The current command line tools support the following features.
+
+- verify Colossal-AI build
+- launch distributed jobs
+- tensor parallel micro-benchmarking
+
+## Check Installation
+
+To verify whether your Colossal-AI is built correctly, you can use the command `colossalai check -i`.
+This command will inform you information regarding the version compatibility and cuda extension.
+
+<figure style={{textAlign: "center"}}>
+<img src="https://s2.loli.net/2022/05/04/KJmcVknyPHpBofa.png"/>
+<figcaption>Check Installation Demo</figcaption>
+</figure>
+
+## Launcher
+
+To launch distributed jobs on single or multiple nodes, the command `colossalai run` can be used for process launching.
+You may refer to [Launch Colossal-AI](./launch_colossalai.md) for more details.
+
+## Tensor Parallel Micro-Benchmarking
+
+As Colossal-AI provides an array of tensor parallelism methods, it is not intuitive to choose one for your hardware and
+model. Therefore, we provide a simple benchmarking to evaluate the performance of various tensor parallelisms on your system.
+This benchmarking is run on a simple MLP model where the input data is of the shape `(batch_size, seq_length, hidden_size)`.
+Based on the number of GPUs, the CLI will look for all possible tensor parallel configurations and display the benchmarking results.
+You can customize the benchmarking configurations by checking out `colossalai benchmark --help`.
+
+```shell
+# run on 4 GPUs
+colossalai benchmark --gpus 4
+
+# run on 8 GPUs
+colossalai benchmark --gpus 8
+```
+
+:::caution
+
+Only single-node benchmarking is supported currently.
+
+:::