Instructions to use replicate/aiter-kernels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use replicate/aiter-kernels with Kernels:
# !pip install kernels from kernels import get_kernel # a version (or an explicit revision) is required; see the "Files and versions" tab for the available ones kernel = get_kernel("replicate/aiter-kernels", version=1) - Notebooks
- Google Colab
- Kaggle
File size: 437 Bytes
2976eec | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | import torch
def get_num_sms():
# Returns the Compute Unit count of the current device
current_device_index = torch.cuda.current_device()
current_device = torch.cuda.get_device_properties(current_device_index)
num_sms = current_device.multi_processor_count
return num_sms
def get_num_xcds():
# Currently, you can't query this programmatically. For gfx942/gfx950 it's 8, so we hardcode that here.
return 8
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