mirror of
https://github.com/andreinechaev/nvcc4jupyter.git
synced 2026-06-13 18:50:47 +05:30
Ștefan-Cosmin Ciocan
887c809d07
* Use NVIDIA Nsight Compute CLI profiler * Add profile and profiler-args options to argument parser. * Add missing comma to profiler-args option. * Use profile args in version 1 of the plugin * Change profiler-args option to take all remaining arguments * Change profiler_args type from string to list of strings * Add profile option to version 2 of the plugin * Add profiler usage instructions
35 lines
1.3 KiB
Markdown
35 lines
1.3 KiB
Markdown
## NVCC Plugin for Jupyter notebook
|
|
|
|
### V2 is available
|
|
|
|
V2 brings support of multiple source and header files.
|
|
|
|
##### Usage
|
|
|
|
- Load Extension
|
|
> `%load_ext nvcc_plugin`
|
|
|
|
- Mark a cell to be treated as cuda cell
|
|
> `%%cuda --name example.cu --compile false`
|
|
>> NOTE: The cell must contain either code or comments to be run successfully.
|
|
>> It accepts 2 arguments. `-n` | `--name` - which is the name of either CUDA source or Header
|
|
>> The name parameter must have extension `.cu` or `.h`
|
|
>> Second argument `-c` | `--compile`; default value is `false`. The argument is a flag to specify
|
|
>> if the cell will be compiled and run right away or not. It might be usefull if you're playing in
|
|
>> the `main` function
|
|
|
|
- To compile and run all CUDA files you need to run
|
|
```
|
|
%%cuda_run
|
|
# This line just to bypass an exeption and can contain any text
|
|
```
|
|
|
|
- To profile your CUDA kernels using NVIDIA Nsight Compute CLI profiler you need to run
|
|
```
|
|
%%cu --profile
|
|
```
|
|
- You can add options to the profiler. Keep in mind that any argument after "--profiler-args" will be considered as a profiler argument. For example, to select which sections to collect metrics for you need to run
|
|
```
|
|
%%cu --profile --profiler-args --section SpeedOfLight --section MemoryWorkloadAnalysis --section Occupancy
|
|
```
|