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https://github.com/metallikecuda/gpumkat

Gpumkat is a shader debugger for metal which is designed to do what instruments can't do
https://github.com/metallikecuda/gpumkat

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Gpumkat is a shader debugger for metal which is designed to do what instruments can't do

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README

          

# Gpumkat

a GPU kernel analysis tool for macOS Metal with many features ranging from analyzing performance, cache hit rates, interface metrics, gpu software states, shader optimization recommendations, stack traces, recording timelines, traces and more.

## Requirements:

- arm MacOS and M series chip
- any platform that supports metal
- metal api
- xcode
- homebrew
- json-c 0.18 (installed with homebrew)
- curl

## Installation

To install gpumkat run this command.

```sh
curl -L -o gpumkat.tar.gz https://github.com/MetalLikeCuda/osxiec/releases/download/%s/gpumkat.tar.gz && tar -xvzf gpumkat.tar.gz && cd gpumkat && sudo sh install.sh
```

replace %s with the latest version

## Usage

```sh
gpumkat
```

---
### Commands you can use

**To update**

```sh
gpumkat -update
```

**To add plugins**

```sh
gpumkat -add-plugin
```

**To remove plugins**

```sh
gpumkat -remove-plugin
```

**To get help**

```sh
gpumkat -help
```

**To get version information**

```sh
gpumkat --version
```

**To run tests**
```sh
gpumkat -test
```

**To run lsp server**

```sh
gpumkat -lsp
```

## Examples

More examples can be seen in the examples folder

### Example config:

```json
{
"metallib_path": "default.metallib",
"function_name": "compute_shader",
"logging": {
"enabled": true,
"log_file_path": "gpumkat_profiler.log",
"log_level": 3,
"log_timestamps": true
},
"debug": {
"enabled": true,
"print_variables": true,
"step_by_step": true,
"break_before_dispatch": true,
"verbosity_level": 2,
"breakpoints": [
{
"condition": "BeforeDispatch",
"description": "After buffer initialization"
}
],
"error_handling": {
"catch_warnings": true,
"catch_memory_errors": true,
"catch_shader_errors": true,
"catch_validation_errors": true,
"break_on_error": false,
"max_error_count": 100,
"min_severity": 1
},
"timeline": {
"enabled": true,
"output_file": "gpumkat_timeline2.json",
"track_buffers": true,
"track_shaders": true,
"track_performance": true,
"max_events": 1000
},
"low_end_gpu": {
"enabled": true,
"compute": {
"processing_units_availability": 0.6,
"clock_speed_reduction": 0.4,
"compute_unit_failures": 2
},
"memory": {
"bandwidth_reduction": 0.6,
"latency_multiplier": 3.0,
"available_memory": 536870912,
"memory_error_rate": 0.02
},
"thermal": {
"thermal_throttling_threshold": 85.0,
"power_limit": 50.0,
"enable_thermal_simulation": true
},
"logging": {
"detailed_logging": true,
"log_file_path": "low_end_gpu_simulation.log"
}
},
"async_debug": {
"enable_async_tracking": true,
"log_command_status": true,
"detect_long_running_commands": true,
"long_command_threshold": 2.5,
"generate_async_timeline": true
},
"thread_control": {
"enable_thread_debugging": true,
"dispatch_mode": 3,
"log_thread_execution": true,
"validate_thread_access": true,
"simulate_thread_failures": true,
"thread_failure_rate": 0.05,
"custom_thread_group_size": [
32,
1,
1
],
"custom_grid_size": [
1024,
1,
1
],
"thread_order_file": "custom_thread_order.txt"
}
},
"buffers": [
{
"name": "inputBuffer",
"size": 1024,
"type": "float",
"contents": [
1.0,
2.0,
3.0,
4.0,
5.0
]
},
{
"name": "outputBuffer",
"size": 1024,
"type": "float",
"contents": []
}
],
"image_buffers": [
{
"name": "inputImage",
"image_path": "/path/to/image.png",
"width": 0,
"height": 0,
"type": "float"
}
]
}
```

### Example kernel:

```c
#include
using namespace metal;

kernel void compute_shader(const device float *input [[buffer(0)]],
device float *output [[buffer(1)]],
uint index [[thread_position_in_grid]]) {
output[index] = input[index] * 2.0;
}
```

### Example Logs:

## Building

You can build gpumkat using cmake with the following command:
```sh
mkdir build && cd build && cmake -S .. -B . -G "Ninja" && ninja
```

### Notes:

Other shaders you can use are located in the list of shaders: https://github.com/MetalLikeCuda/list_of_metal_shaders.md

Some things like temperature are approximated so it's better to just use instruments if you want very low level hardware specific data, though for normal debugging this should be better.