README.md

metadata

pretty_name: EngiBench PowerElectronics v1
license: cc-by-nc-sa-4.0
task_categories:
  - tabular-regression
tags:
  - engineering-design
  - multi-objective-optimization
  - circuit-simulation
  - ngspice
  - engibench
size_categories:
  - 10K<n<100K
dataset_info:
  features:
    - name: dataset_schema_version
      dtype: int64
    - name: split
      dtype: string
    - name: source_index
      dtype: int64
    - name: design_sha256
      dtype: string
    - name: initial_design
      sequence: float64
    - name: v0_DcGain
      dtype: float64
    - name: v0_Voltage_Ripple
      dtype: float64
    - name: source_dataset_id
      dtype: string
    - name: source_dataset_revision
      dtype: string
    - name: problem_version
      dtype: int64
    - name: engibench_git_commit
      dtype: string
    - name: netlist_sha256
      dtype: string
    - name: simulator_version
      dtype: string
    - name: simulator_sha256
      dtype: string
    - name: simulator_platform_system
      dtype: string
    - name: simulator_platform_machine
      dtype: string
    - name: container_sha256
      dtype: string
    - name: output_voltage_mean
      dtype: float64
    - name: output_voltage_peak_to_peak
      dtype: float64
    - name: dc_gain
      dtype: float64
    - name: dc_gain_error
      dtype: float64
    - name: relative_voltage_ripple
      dtype: float64
    - name: simulation_valid
      dtype: bool
    - name: objectives_valid
      dtype: bool
    - name: simulation_status
      dtype: string
    - name: error_type
      dtype: string
    - name: error_message
      dtype: string
  splits:
    - name: train
      num_bytes: 6682584
      num_examples: 9676
    - name: val
      num_bytes: 1904125
      num_examples: 2765
    - name: test
      num_bytes: 953783
      num_examples: 1383
  download_size: 2536603
  dataset_size: 9540492
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*.parquet
      - split: val
        path: data/val-*.parquet
      - split: test
        path: data/test-*.parquet

EngiBench PowerElectronics v1

PowerElectronics v1 is a simulator-frozen EngiBench dataset for data-driven engineering design. It re-simulates the exact 13,824 input designs and preserves the train/validation/test membership from IDEALLab/power_electronics_v0, but it is a new benchmark and does not claim to reproduce the v0 labels.

The canonical backend is ngspice 44.2 on Linux x86_64 in a pinned Apptainer image. v1 corrects the objective semantics, retains signed physical measurements, and records the source, code, netlist, simulator, and container fingerprints in every row.

Loading

Pin the release tag in reproducible experiments:

from datasets import load_dataset

dataset = load_dataset(
    "IDEALLab/power_electronics_v1",
    revision="v1.0.0",
)

Splits and simulation status

Split	Rows	Status
train	9,676	9,674 ok; 2 invalid_measurements
validation (val)	2,765	2,764 ok; 1 invalid_measurements
test	1,383	1,383 ok

The possible simulation_status values are:

Status	Measurement and objective fields	Validity flags
ok	Signed measurements and both objectives are finite.	simulation_valid=true, objectives_valid=true
invalid_measurements	A raw measurement is non-finite or peak-to-peak voltage is negative. Non-finite measurements and both objectives are null; other raw measurements may remain.	Both false
undefined_relative_voltage_ripple	Mean voltage is zero. Raw measurements, gain, and gain error remain; relative ripple is null.	simulation_valid=true, objectives_valid=false
simulation_error	Simulator raised an error. All measurements and objectives are null; error_type and error_message are populated.	Both false

Keep every row and use objectives_valid to mask rows from a numeric objective loss. The published v1.0.0 dataset happens to contain only ok and invalid_measurements rows; the other statuses are part of the generation schema and explain possible future or local runs.

The three invalid simulator results are retained at train[4309], train[5960], and val[223]. Their unavailable measurements and objectives are null; they are never replaced with zero, imputed, clipped, or removed.

Consumers should retain every row and use objectives_valid as a mask when a numeric regression loss requires objective labels. Invalid rows may also be used to model the simulator-failure region. Evaluation must report the number of valid and invalid rows rather than silently dropping failures.

All finite values, including negative signed measurements and very large relative-ripple values near zero mean voltage, remain unchanged.

v1 objectives

The stored physical measurements are:

• signed mean output voltage, output_voltage_mean;
• peak-to-peak output voltage, output_voltage_peak_to_peak.

With a 1,000 V source, v1 derives the signed gain and two minimization objectives:

dc_gain = output_voltage_mean / 1000
dc_gain_error = abs(dc_gain - 0.25)
relative_voltage_ripple = output_voltage_peak_to_peak / abs(output_voltage_mean)

If the simulator does not return finite measurements, the derived objectives are null and the validity/status fields identify the failure. A zero mean voltage would similarly make relative ripple unavailable rather than assigning an artificial value.

Fields

Identity and source mapping

• dataset_schema_version: schema version for this row format.
• split, source_index: exact v0 split membership and row index.
• design_sha256: stable checksum of initial_design.
• initial_design: the original 20-dimensional v0 design.
• v0_DcGain, v0_Voltage_Ripple: immutable v0 labels retained only for direct comparison.
• source_dataset_id, source_dataset_revision: exact v0 source.
• problem_version: EngiBench problem version (1).

Reproducibility

• engibench_git_commit, netlist_sha256;
• simulator_version, simulator_sha256;
• simulator_platform_system, simulator_platform_machine;
• container_sha256.

Measurements, objectives, and validity

• output_voltage_mean, output_voltage_peak_to_peak, dc_gain;
• dc_gain_error, relative_voltage_ripple;
• simulation_valid, objectives_valid, simulation_status;
• error_type, error_message for caught simulator exceptions.

Frozen provenance

Component	Identity
Source dataset	IDEALLab/power_electronics_v0
Source revision	5c4adb2ec5cfc71794988b1297a7ff8ffe59daa5
EngiBench commit	64e6107d44349e67e031cad36633c1af26817784
EngiBench review	IDEALLab/EngiBench#279
Simulator	ngspice 44.2, Linux x86_64
ngspice binary SHA-256	11a4334ee90509f5edfdceef541711a34a1943d26a14cf0928ac8d5947b72374
Apptainer SIF SHA-256	40816f203b7e1c68ae37f4d9353bd302486d77988b98733c021f1ff71f48ae02
Container definition SHA-256	20675ae0ab31723bae9dd5881d04fcff6e7e08047898b3cbf4e6595dfb705695
Netlist SHA-256	7a3c9f061993ceddd605394cd03d899b1933370cc0cd38b48606c1d0c23d13a7

The exact original v0 runtime cannot be confirmed. An archived notebook contains evidence for Windows/x86_64 and ngspice 36, while an ngspice 44.2 ARM64 Mac reproduction is much closer to the published v0 labels than the corresponding Linux x86_64 reproduction. Because operating system, simulator version, compiler, and build also differ, the latter is evidence consistent with ARM but is not proof of the original architecture.

Do not combine v0 and v1 labels or silently train on one backend and verify on another. Cross-backend comparisons should be explicit experiments.

Generation and audit

The provenance/ directory contains:

• the 24 original generation manifests;
• the strict 13,824-row audit report;
• the JSONL-to-Parquet semantic conversion report;
• the container recipe and exact Python dependency freeze;
• the Euler Slurm generation script and both audit/conversion scripts.

The Parquet conversion sorts every split by source_index. Its report verifies that every value and null round-trips exactly from the audited JSONL source.

Limitations

• Results are specific to the frozen ngspice binary and container fingerprint.
• Relative ripple can become extremely large when the absolute mean voltage is close to zero. These finite values are intentional and are not clipped.
• Three designs do not have finite simulator measurements on the canonical backend. Their explicit invalid status is part of the benchmark.
• The v0 labels are provided for comparison, not as additional v1 targets.

Citation

@inproceedings{felten_engibench_2025,
  title = {{EngiBench}: {A} {Framework} for {Data}-{Driven} {Engineering} {Design} {Research}},
  author = {Felten, Florian and Apaza, Gabriel and B\"{a}unlich, Gerhard and Diniz, Cashen and Dong, Xuliang and Drake, Arthur and Habibi, Milad and Hoffman, Nathaniel J. and Keeler, Matthew and Massoudi, Soheyl and VanGessel, Francis G. and Fuge, Mark},
  booktitle = {Proceedings of the 39th Conference on Neural Information Processing Systems ({NeurIPS} 2025)},
  year = {2025}
}