Upload ScienceKernelBench

CHANGELOG.md

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+# Changelog
+
+## 0.1.0 — 2026-11-12
+
+Initial release.
+
+- 22 reference tasks across physics, chemistry, biology, statistics,
+  mathematics and economics.
+- `level_1` (8 tasks), `level_2` (7 tasks), `level_3` (7 tasks).
+- Stable `problem_id`, `task_key`, `task_version` and `reference_hash` for
+  every task.
+- Same Hugging Face layout as `ai-nikolai/KernelBench`: one `default` config
+  with `level_1`, `level_2`, `level_3` splits under `data/`.
+- Compatible with `robust-kernelbench >= 0.2.0`.

README.md

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+---
+license: agpl-3.0
+language:
+- en
+task_categories:
+- other
+pretty_name: Science KernelBench
+tags:
+- kernelbench
+- gpu
+- cuda
+- triton
+- scientific-computing
+- pde
+- kernel-methods
+configs:
+- config_name: default
+  data_files:
+  - split: level_1
+    path: data/level_1-*
+  - split: level_2
+    path: data/level_2-*
+  - split: level_3
+    path: data/level_3-*
+---
+
+# Science KernelBench
+
+A science-focused task set for `robust-kernelbench`.  Each task provides a
+PyTorch reference implementation of a numerical primitive; the candidate must
+produce a faster, numerically equivalent GPU kernel.
+
+This directory is the **source of truth**.  `to_hf.py` expands the manifest into
+a Hugging Face dataset; the generated export is not committed.
+
+Current starter set: **22 tasks** across physics, chemistry, biology,
+statistics, mathematics and economics.
+
+| level | focus | tasks |
+| --- | --- | --- |
+| `level_1` | single stencil, reduction or short elementwise expression | 8 |
+| `level_2` | all-pairs interactions, batched linear algebra, multi-state updates | 7 |
+| `level_3` | sequential dynamic programs, FFTs, tree backward induction | 7 |
+
+Each task carries `domain`, `subdomain`, `level`, `tags` and a `source` block.
+The reference files contain a docstring with the domain, the problem solved and
+the canonical paper/source.
+
+### Task list
+
+| id | task | domain | level |
+| --- | --- | --- | --- |
+| 101 | `pairwise_rbf` | statistics | 1 |
+| 102 | `laplacian_2d` | physics | 1 |
+| 103 | `heat_step_2d` | physics | 1 |
+| 104 | `lennard_jones_energy` | chemistry | 1 |
+| 105 | `lotka_volterra_step` | biology | 1 |
+| 106 | `gaussian_kde` | statistics | 1 |
+| 107 | `horner_eval` | mathematics | 1 |
+| 108 | `black_scholes_call` | economics | 1 |
+| 201 | `nbody_acceleration` | physics | 2 |
+| 202 | `coulomb_energy` | chemistry | 2 |
+| 203 | `hodgkin_huxley_step` | biology | 2 |
+| 204 | `kalman_update` | statistics | 2 |
+| 205 | `graph_laplacian` | mathematics | 2 |
+| 206 | `portfolio_variance` | economics | 2 |
+| 207 | `wave_step_2d` | physics | 2 |
+| 301 | `needleman_wunsch_score` | biology | 3 |
+| 302 | `fft_convolution` | mathematics | 3 |
+| 303 | `binomial_option_crr` | economics | 3 |
+| 304 | `split_step_schrodinger` | physics | 3 |
+| 305 | `ewald_real_space` | chemistry | 3 |
+| 306 | `gaussian_process_posterior` | statistics | 3 |
+| 307 | `floyd_warshall` | mathematics | 3 |
+
+
+## Versioning
+
+Current release: **0.1.0** (`schema_version: kernelbench-v1`), compatible with
+`robust-kernelbench >= 0.2.0`.
+
+The dataset version is independent of the package version:
+
+- `PATCH` — documentation, metadata or provenance fixes with no scoring change.
+- `MINOR` — new tasks, domains or levels; existing tasks unchanged.
+- `MAJOR` — removal/renumbering, reference-output changes, or benchmark-split
+  changes.
+
+Every task has a permanent `problem_id`, a stable `task_key`, a `task_version`
+and a `reference_hash`. Removed tasks are marked `retired`; IDs are never reused.
+Pin production runs to an HF tag or commit:
+
+```bash
+robust-kernelbench \
+  --dataset ai-nikolai/ScienceKernelBench \
+  --dataset_revision v0.1.0 \
+  --dataset_split level_1 \
+  ...
+```
+
+## Schema
+
+Required columns:
+
+| column | type | meaning |
+| --- | --- | --- |
+| `problem_id` | int | unique task id |
+| `name` | string | filesystem-safe task name |
+| `code` | string | self-contained reference source |
+
+The `code` must define:
+
+```python
+class Model(nn.Module): ...
+def get_inputs(): ...
+def get_init_inputs(): ...
+```
+
+Optional columns understood by the harness:
+
+| column | meaning |
+| --- | --- |
+| `level` | dataset split / difficulty grouping (1-3 here) |
+| `domain` | physics, chemistry, biology, statistics, mathematics, economics |
+| `subdomain` | finer label, e.g. `molecular dynamics`, `PDE`, `bioinformatics` |
+| `filter` | include in the representative subset |
+| `task_type` | `pytorch_reference` or `kernel_reference` |
+| `backend` | `cuda`, `triton`, ... |
+| `precision` | `fp32`, `fp16`, `bf16` |
+| `tags` | searchable labels |
+| `source` | provenance / license metadata |
+
+## Local layout
+
+```text
+data/science_kernels/
+├── README.md                  # this dataset card
+├── manifest.json              # versioned task list and provenance
+├── CHANGELOG.md               # dataset release history
+├── requirements.txt           # minimal HF/export dependencies
+├── kernels/
+│   ├── level_1/               # 8 tasks
+│   ├── level_2/               # 7 tasks
+│   └── level_3/               # 7 tasks
+└── to_hf.py                   # per-level export / optional push_to_hub
+```
+
+## Minimal dependencies
+
+```bash
+pip install -r requirements.txt
+```
+
+`torch` is optional and only needed for `--execute` smoke tests; it is listed as
+a comment in the requirements file so the dataset can be loaded and exported on
+a lightweight machine.
+
+## Validate locally
+
+```bash
+# Schema only
+robust-kernelbench-dataset validate \
+  --dataset_path data/science_kernels \
+  --dataset_format directory
+
+# Counts by level and domain, and a browsable list
+robust-kernelbench-dataset stats \
+  --dataset_path data/science_kernels \
+  --dataset_format directory
+robust-kernelbench-dataset list \
+  --dataset_path data/science_kernels \
+  --dataset_format directory --domain physics
+
+# Also run one forward pass per task
+robust-kernelbench-dataset validate \
+  --dataset_path data/science_kernels \
+  --dataset_format directory \
+  --execute --device cpu
+```
+
+## Use with robust-kernelbench
+
+Evaluation only:
+
+```bash
+robust-kernelbench-eval \
+  --dataset_path data/science_kernels \
+  --dataset_format directory \
+  --dataset_split level_1 \
+  --experiment science_exp --trial 1
+```
+
+Agentic generate -> compile -> evaluate:
+
+```bash
+robust-kernelbench \
+  --dataset_path data/science_kernels \
+  --dataset_format directory \
+  --dataset_split level_1 \
+  --dataset_name science-kernels \
+  --version science_v0 \
+  --model_name Qwen/Qwen3-Coder-30B-A3B-Instruct \
+  "1 1 kernelbench"
+```
+
+## Export for Hugging Face
+
+```bash
+python data/science_kernels/to_hf.py --output /tmp/science_kernels_hf
+
+# huggingface_hub >= 1 uses the `hf` command:
+hf upload ai-nikolai/ScienceKernelBench /tmp/science_kernels_hf --repo-type dataset
+
+# Works with any huggingface_hub version:
+python data/science_kernels/upload_to_hf.py \
+  --path /tmp/science_kernels_hf
+```
+
+Or export and push in one step:
+
+```bash
+python data/science_kernels/to_hf.py \
+  --output /tmp/science_kernels_hf \
+  --push
+```
+
+## Provenance and licensing
+
+Only add kernels you have the right to redistribute.  Record the source
+repository, commit, and license in each task's `source` block.  Original tasks
+written for this dataset are released under AGPL-3.0, matching the repository.
+If you combine sources with different licenses, use the strictest compatible
+license for the combined dataset and document it in this card.
+
+
+## Citation
+
+If you use this dataset, please cite `robust-kernelbench`:
+
+```bibtex
+@misc{rozanov2026robustkernelbench,
+  title        = {Robust KernelBench: A Robust Harness for GPU Kernel Generation and Evaluation},
+  author       = {Rozanov, Nikolai},
+  year         = {2026},
+  howpublished = {\url{https://github.com/ai-nikolai/robust_kernelbench}},
+  note         = {ScienceKernelBench dataset, version 0.1.0}
+}
+```
+
+The dataset card and version should also be cited when reporting benchmark
+results, together with the exact `dataset_revision` used.

data/level_1-00000-of-00001.parquet

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data/level_2-00000-of-00001.parquet

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data/level_3-00000-of-00001.parquet

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requirements.txt

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+# Minimal dependencies for loading, validating and exporting ScienceKernelBench.
+# The dataset itself is plain Parquet; no dataset loading script is required.
+datasets>=2.19
+pandas>=2.0
+pyarrow>=15
+huggingface_hub>=0.23
+
+# Optional: only needed for `robust-kernelbench-dataset ... --execute`
+# (a forward-pass smoke test for each reference task).
+# torch>=2.1