mirror of
https://github.com/harvard-edge/cs249r_book.git
synced 2026-07-21 00:23:30 -05:00
Vijay Janapa Reddi
cb0ae4082f
Run quartodoc build against the refactored package (engine/ extracted from core/, infra->infrastructure): regenerate the API reference so every stub points at the new paths. Adds engine.*/infrastructure.* stubs, removes the 41 stale core.solver.* / core.engine.* / core.scenarios.* / core.config.* / core.evaluation.* / infra*.qmd orphans, and refreshes the package pages (core now primitives-only) + index. Verified: all 47 documented symbols resolve in the new package; every index link resolves; zero stale mlsysim.core.<engine-mod> / mlsysim.infra references anywhere in docs/. (objects.json inventory is gitignored -- regenerated at build.)
37 lines
980 B
Plaintext
37 lines
980 B
Plaintext
# engine.solver.SingleNodeModel { #mlsysim.engine.solver.SingleNodeModel }
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```python
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engine.solver.SingleNodeModel()
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```
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Resolves single-node hardware Roofline bounds and feasibility.
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This model handles the 'Iron Law' of machine learning systems,
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calculating whether a model fits in memory and predicting its
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throughput based on arithmetic intensity.
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Literature Source: Williams et al. (2009), "Roofline: An Insightful Visual
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Performance Model for Floating-Point Programs and Multicore Architectures."
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## Methods
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| Name | Description |
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| --- | --- |
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| [solve](#mlsysim.engine.solver.SingleNodeModel.solve) | Calculates the performance profile for a single hardware node. |
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### solve { #mlsysim.engine.solver.SingleNodeModel.solve }
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```python
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engine.solver.SingleNodeModel.solve(
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model,
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hardware,
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batch_size=1,
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precision='fp16',
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efficiency=0.5,
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raise_errors=False,
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**kwargs,
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)
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```
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Calculates the performance profile for a single hardware node.
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