Backend.AI Accelerator Plugin for CUDA (Mockup)
Project description
backend.ai-accelerator-cuda-mock
A mockup plugin for CUDA accelerators
This plugin deceives the agent and manager to think as if there are CUDA devices.
The configuration follows cuda-mock.toml placed in the same location of agent.toml.
Please refer the sample configurations in the configs/accelerator directory and copy one of them as a starting point.
The statistics are randomly generated in reasonable ranges, but it may seem like "jumping around" because there is no smoothing mechanism of generated values. The configurations for fractional/discrete mode, fraction size, and device masks in etcd are exactly same as the original plugin.
The containers are created without any real CUDA device mounts but with BACKENDAI_MOCK_CUDA_DEVICES and BACKENDAI_MOCK_CUDA_DEVICE_COUNT environment variables.
Since the manager does not know if the reported devices are real or not, you can start any CUDA-only containers (but of course they won't work as expected).
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file backend.ai-accelerator-cuda-mock-22.9.5.tar.gz.
File metadata
- Download URL: backend.ai-accelerator-cuda-mock-22.9.5.tar.gz
- Upload date:
- Size: 10.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | c89e7ef842190825f3b7bbedc0644023d217717169cd177994645b4b9d42d603 |
|
| MD5 | 25df897008c523004f9f06b387901781 |
|
| BLAKE2b-256 | 6a2a25f20398e9acd475f461ee16e8437ef660f63cfc822fc66b14e8d261d8ca |
Provenance
File details
Details for the file backend.ai_accelerator_cuda_mock-22.9.5-py3-none-any.whl.
File metadata
- Download URL: backend.ai_accelerator_cuda_mock-22.9.5-py3-none-any.whl
- Upload date:
- Size: 11.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.10.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 692686c5f62c3871265a5217de48155c764e7146a29a717f75af59cf7065e952 |
|
| MD5 | 0e7e249fff0ce40983ca74fa1538fc00 |
|
| BLAKE2b-256 | 1b0d711111b9674cc2ffdbf2500c2cc58e84deb21d0a2520546babd16fc30bc7 |
