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2bbe3e1a69
Replace 9 old tutorials with 12 new numbered tutorials (00-11) covering roofline through full-stack audit. Redesign landing page, add models-and-solvers and extending-the-engine guides. Add __main__.py, cli.py, and cli/ package for command-line interface.
37 lines
1.1 KiB
Plaintext
37 lines
1.1 KiB
Plaintext
# core.solver.ReliabilityModel { #mlsysim.core.solver.ReliabilityModel }
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```python
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core.solver.ReliabilityModel()
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```
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Calculates Mean Time Between Failures (MTBF) and optimal checkpointing intervals.
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This solver handles the reliability modeling of massive clusters, helping
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determine the 'Goodput' of long-running training jobs. It identifies
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the probability of a job failure before completion and calculates the
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Young-Daly optimal interval to minimize wasted compute time.
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Literature Source:
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1. Young (1974), "A First-Order Approximation to the Optimum Checkpoint
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Interval."
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2. Daly (2006), "A Higher Order Estimate of the Optimum Checkpoint
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Interval for Restart-Dump Strategy."
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## Methods
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| Name | Description |
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| --- | --- |
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| [solve](#mlsysim.core.solver.ReliabilityModel.solve) | Calculates reliability and checkpointing metrics for a fleet. |
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### solve { #mlsysim.core.solver.ReliabilityModel.solve }
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```python
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core.solver.ReliabilityModel.solve(
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fleet,
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job_duration_hours,
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checkpoint_time_s=60.0,
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)
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```
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Calculates reliability and checkpointing metrics for a fleet.
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