> ## Documentation Index
> Fetch the complete documentation index at: https://sdk.cerebras.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Working With Code Samples

> Compile and run Cerebras SDK code samples using the provided commands scripts and the CSL compiler and Python host runtime.

The [SDK Code Examples](/csl/sdk-examples) section contains CSL programs, the `.csl` files, that each either demonstrate individual features of the language, or solve a larger application problem.
Each program is accompanied by a Python script, the `run.py` file, to run that program with the simulator.

The source for these code samples is hosted at the
[SDK examples GitHub repository](https://github.com/Cerebras/sdk-examples).

For the GEMV tutorial code samples, we additionally provide
step-by-step explanations of the code in the [Tutorials](/csl/tutorials) section.

<Note>
  If you’re just getting started, we recommend walking through the step-by-step
  tutorials in [Tutorials](/csl/tutorials/) to get a fuller explanation of these programs.
</Note>

## Compiling the Code Samples

Each code sample contains a CSL file as the top-level source file, typically named `layout.csl`.
This file may reference additional CSL source files in that directory.

Each code sample also contains a `commands.sh` script, which contains the
commands required to compile and run the example.

For example, the `tutorials/gemv-01-complete-program/commands.sh`
in the [SDK examples repository](https://github.com/Cerebras/sdk-examples/tree/master/tutorials/gemv-01-complete-program) contains:

```bash theme={"languages":{"custom":["/languages/csl-tmlanguage.json"]}}
cslc ./layout.csl --fabric-dims=8,3 \
  --fabric-offsets=4,1 -o out --memcpy --channels 1
cs_python run.py --name out
```

<Tip>
  **See also**<br />
  See [CSL Compiler](/csl/csl-compiler) for the compiler options documentation.
</Tip>

To compile the program:

1. First cd into the directory that contains the CSL files.
2. Then run the `cslc` command shown in the `commands.sh` file to compile the program.
   Note, this command may span multiple lines. This command execution will produce files with the `elf` extension.
   For example:

```bash theme={"languages":{"custom":["/languages/csl-tmlanguage.json"]}}
$ cd tutorials/gemv-01-complete-program/
$ cslc ./layout.csl --fabric-dims=8,3 --fabric-offsets=4,1 -o out --memcpy --channels 1
$ ls out
bin  east  generated  out.json  west
$ ls out/bin
out_0_0.elf  out_rpc.json
```

## Running the Program

Use the `run.py` Python script that is in the code sample directory to execute the compiled program. For example, to run the above compiled program, execute the following command in the `gemv-01-complete-program` directory:

```bash theme={"languages":{"custom":["/languages/csl-tmlanguage.json"]}}
$ cs_python run.py --name out
```

If the program runs correctly, you will see the message `SUCCESS!` near the end of the output.

## Debugging

See [Debugging Guide](/debug/debugging) and [SDK GUI](/debug/sdk-gui).

## Moving From Simulation To Hardware

After successfully simulating your CSL program, you can run it
on hardware by following the below guidelines when using `cslc`:

### Pass `--arch` Flag

Use the `--arch` flag with `cslc`. This will ensure that the appropriate Cerebras system is targeted.

Allowed values are `--arch=wse2` for WSE-2 architecture and `--arch=wse3` for WSE-3 architecture.
The default value is `wse2`.
For example:

```bash theme={"languages":{"custom":["/languages/csl-tmlanguage.json"]}}
cslc --arch=wse2 ./layout.csl --fabric-dims=8,3 \
  --fabric-offsets=4,1 -o out --memcpy --channels 1
```

Note that `wse3` is not yet supported for all example programs.

### Provide `--fabric-dims`

When compiling for simulation with `cslc`, the `--fabric-dims` flag can be any bounding box large enough to contain your program’s PEs. However, when compiling for hardware, these dimensions must match your Cerebras system’s fabric dimensions. For example:

```bash theme={"languages":{"custom":["/languages/csl-tmlanguage.json"]}}
cslc --arch=wse2 ./layout.csl --fabric-dims=757,996 \
  --fabric-offsets=4,1 -o out --memcpy --channels 1
```

### Provide IP Address to SdkRuntime

To run on the Cerebras system hardware, you must pass the IP and port address of the network-attached Cerebras system to the `cmaddr` argument of the `SdkRuntime` constructor in your `run.py`:

```python theme={"languages":{"custom":["/languages/csl-tmlanguage.json"]}}
runner = SdkRuntime(compile_dir, cmaddr="1.2.3.4:9000")
```