mirror of
https://github.com/harvard-edge/cs249r_book.git
synced 2026-08-03 09:03:45 -05:00
Vijay Janapa Reddi
02c37be63a
Move the simulator out of core/ into a new engine/ package: solver, engine,
evaluation, results, pipeline, dse, walls, resolver_factory, explainers,
config, calibration, and the evaluatable scenarios bundle. core/ now holds
only primitives (units, types, provenance, registry, validation, exceptions).
No core primitive imports an engine module; the dependency runs one way.
Also relocate the appendix_lineage audit gate (a used lineage auditor, NOT
vestigial — kept, not deleted) from core/ to tools/, beside its consumer
audit_provenance.py.
Consumers repointed mlsysim.core.<mod> -> mlsysim.engine.<mod> (and the
from-core-import-calibration form): package internals (cli, sim, solvers,
viz), tests, runnable examples, paper scripts, and 9 book chapters. Pure
reorg, zero functional change.
482 passed; import clean (no cycles); vol1 (engine.calibration) and vol2
(engine.solver) chapters render with 0 {python} leaks, 0 tracebacks.
Deferred to P10: mlsysim/docs prose, generated docs/api/* stubs, tutorial
slides, paper.tex, README — propagate to website/slides/paper.
225 lines
4.9 KiB
Python
225 lines
4.9 KiB
Python
"""Shared fixtures for mlsysim test suite.
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All hardware, model, fleet, and solver fixtures are defined here.
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Pytest discovers this file automatically — no imports needed in test files.
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"""
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import pytest
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from mlsysim.core.constants import Q_
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from mlsysim.engine.solver import (
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CheckpointModel,
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ContinuousBatchingModel,
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CompressionModel,
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DataModel,
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DistributedModel,
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EconomicsModel,
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EfficiencyModel,
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InferenceScalingModel,
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OrchestrationModel,
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ReliabilityModel,
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ResponsibleEngineeringModel,
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ScalingModel,
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SensitivitySolver,
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ServingModel,
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SingleNodeModel,
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SustainabilityModel,
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SynthesisSolver,
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TailLatencyModel,
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TopologyModel,
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TransformationModel,
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WeightStreamingModel,
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)
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from mlsysim.hardware.registry import Hardware
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from mlsysim.infrastructure.registry import Grids, Infrastructure
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from mlsysim.models.registry import Models
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from mlsysim.models.types import TransformerWorkload
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from mlsysim.systems.registry import Systems
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from mlsysim.systems.types import NetworkFabric
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# ── Hardware Fixtures ────────────────────────────────────────────
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@pytest.fixture(scope="session")
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def h100():
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return Hardware.Cloud.H100
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@pytest.fixture(scope="session")
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def a100():
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return Hardware.Cloud.A100
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@pytest.fixture(scope="session")
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def cerebras_cs3():
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return Hardware.Cloud.Cerebras_CS3
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@pytest.fixture(scope="session")
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def jetson():
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return Hardware.Edge.JetsonOrinNX
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@pytest.fixture(scope="session")
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def esp32():
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return Hardware.Tiny.ESP32_S3
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# ── Model / Workload Fixtures ───────────────────────────────────
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@pytest.fixture(scope="session")
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def resnet():
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return Models.Vision.ResNet50
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@pytest.fixture(scope="session")
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def gpt3():
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return Models.Language.GPT3
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@pytest.fixture(scope="session")
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def llama3_8b():
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return Models.Language.Llama3_8B
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@pytest.fixture(scope="session")
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def llama3_70b():
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return TransformerWorkload(
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name="Llama-3-70B",
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architecture="Transformer",
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parameters=Q_("70e9 param"),
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layers=80,
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hidden_dim=8192,
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heads=64,
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)
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# ── Fleet / System Fixtures ─────────────────────────────────────
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@pytest.fixture(scope="session")
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def research_cluster():
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return Systems.Clusters.Research_256
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@pytest.fixture(scope="session")
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def frontier_cluster():
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return Systems.Clusters.Frontier_8K
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@pytest.fixture(scope="session")
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def grid_quebec():
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return Infrastructure.Grids.Quebec
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@pytest.fixture(scope="session")
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def grid_us_avg():
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return Infrastructure.Grids.US_Avg
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# ── Solver Fixtures ─────────────────────────────────────────────
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# Each solver is stateless, so session scope is safe.
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@pytest.fixture(scope="session")
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def single_node_solver():
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return SingleNodeModel()
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@pytest.fixture(scope="session")
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def serving_solver():
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return ServingModel()
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@pytest.fixture(scope="session")
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def continuous_batching_solver():
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return ContinuousBatchingModel()
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@pytest.fixture(scope="session")
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def weight_streaming_solver():
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return WeightStreamingModel()
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@pytest.fixture(scope="session")
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def tail_latency_solver():
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return TailLatencyModel()
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@pytest.fixture(scope="session")
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def checkpoint_solver():
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return CheckpointModel()
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@pytest.fixture(scope="session")
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def distributed_solver():
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return DistributedModel()
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@pytest.fixture(scope="session")
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def reliability_solver():
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return ReliabilityModel()
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@pytest.fixture(scope="session")
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def economics_solver():
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return EconomicsModel()
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@pytest.fixture(scope="session")
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def sustainability_solver():
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return SustainabilityModel()
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@pytest.fixture(scope="session")
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def data_solver():
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return DataModel()
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@pytest.fixture(scope="session")
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def scaling_solver():
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return ScalingModel()
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@pytest.fixture(scope="session")
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def orchestration_solver():
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return OrchestrationModel()
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@pytest.fixture(scope="session")
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def compression_solver():
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return CompressionModel()
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@pytest.fixture(scope="session")
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def efficiency_solver():
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return EfficiencyModel()
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@pytest.fixture(scope="session")
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def transformation_solver():
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return TransformationModel()
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@pytest.fixture(scope="session")
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def topology_solver():
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return TopologyModel()
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@pytest.fixture(scope="session")
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def inference_scaling_solver():
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return InferenceScalingModel()
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@pytest.fixture(scope="session")
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def sensitivity_solver():
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return SensitivitySolver()
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@pytest.fixture(scope="session")
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def synthesis_solver():
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return SynthesisSolver()
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@pytest.fixture(scope="session")
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def responsible_engineering_solver():
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return ResponsibleEngineeringModel()
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