Datasets:

sdrbench
/

exaalt

---
license: other
license_name: sdrbench
license_link: https://sdrbench.github.io/
pretty_name: "SDRBench: EXAALT"
tags:
- scientific-data
- lossy-compression
- sdrbench
- hpc
- sz3
configs:
- config_name: files
  data_files: files.jsonl
  default: true
---

# SDRBench — EXAALT

Molecular dynamics simulation (EXAALT, ECP): atom positions (and velocities for 'small'). Single precision, little-endian.

> **Raw binary arrays, not an Arrow/Parquet dataset.** `datasets.load_dataset("sdrbench/exaalt")` returns the table of files (`files.jsonl`: path, dtype, shape, sha256). Read the arrays with the `sdrbench` package or `hf_hub_download` + numpy as shown below.

This repository is an **unmodified mirror** of the EXAALT data of [SDRBench](https://sdrbench.github.io/datasets.html), the
Scientific Data Reduction Benchmark. The originals are hosted by Argonne National Laboratory on Globus;
every archive was unpacked and its files uploaded byte-for-byte (sha256 verified) (revision `fdd63c3e68`). `metadata/` holds
the original SDRBench property and template files. Kept in sync automatically by
[szcompressor/sdrbench](https://github.com/szcompressor/sdrbench).

- **Data provider:** EXAALT team (ECP)
- **Size:** 4.4 GB in 5 variant(s)
- **Format:** raw little-endian binary, C order (slowest dimension first); dtype and shape per field below

## Usage

```bash
pip install "sdrbench[sz3]"     # sdrbench + pysz (SZ3)
```

```python
import numpy as np
import sdrbench
from pysz import sz, szConfig, szErrorBoundMode

ds = sdrbench.dataset("exaalt")                # default variant "small"
print(ds.fields)
x = ds["vx"]                     # numpy array, dtype <f4, shape (2869440,)

# compress with SZ3 (pysz) at a 1e-3 value-range-relative error bound
conf = szConfig()
conf.errorBoundMode = szErrorBoundMode.REL
conf.relErrorBound = 1e-3
compressed, ratio = sz.compress(np.ascontiguousarray(x), conf)
y, _ = sz.decompress(compressed, x.dtype.type, x.shape)
max_err, psnr, nrmse = sz.verify(np.asarray(x), y)
print(f"ratio {ratio:.1f}x, PSNR {psnr:.1f} dB, max error {max_err:.3g}")
```

Files are fetched on first use (in parallel with `ds.download("data/")`) and cached, pinned to the revision
of the installed `sdrbench` release; if Hugging Face is unreachable the package falls back to the original
archive on Globus. Existing local SDRBench copies can be used with `sdrbench.dataset("exaalt", root="/path")`.

Without the package, with `huggingface_hub` and numpy only:

```python
from huggingface_hub import hf_hub_download
import numpy as np
p = hf_hub_download("sdrbench/exaalt", "2869440/vx.f32", repo_type="dataset", revision="fdd63c3e68af5a9243c8b954aac0b0a3b0736ad0")
x = np.fromfile(p, dtype="<f4").reshape((2869440,))
```

## Variants and fields


### `small` (default)

`sdrbench.dataset("exaalt", "small")` — folder `2869440/` — 7 files, 68.9 MB, from [SDRBENCH-EXAALT-2869440.tar.gz](https://g-d0cd3f.fd635.8443.data.globus.org/raw-data/EXAALT/SDRBENCH-EXAALT-2869440.tar.gz).

One snapshot of 2,869,440 atoms: positions xx, yy, zz and velocities vx, vy, vz.

| Field | dtype | Shape (C order) | File |
|---|---|---|---|
| `vx` | `<f4` | 2869440 | `2869440/vx.f32` |
| `vy` | `<f4` | 2869440 | `2869440/vy.f32` |
| `vz` | `<f4` | 2869440 | `2869440/vz.f32` |
| `xx` | `<f4` | 2869440 | `2869440/xx.f32` |
| `yy` | `<f4` | 2869440 | `2869440/yy.f32` |
| `zz` | `<f4` | 2869440 | `2869440/zz.f32` |

Other files: `2869440/SDRBENCH-EXAALT-2869440-template_data.txt`

### `copper-1`

`sdrbench.dataset("exaalt", "copper-1")` — folder `copper/` — 3 files, 204.1 MB, from [SDRBENCH-EXAALT-copper.tar.gz](https://g-d0cd3f.fd635.8443.data.globus.org/raw-data/EXAALT/SDRBENCH-EXAALT-copper.tar.gz).

Copper system, trajectory 1: positions x, y, z of 3137 atoms over 5423 time steps (time x atom).

| Field | dtype | Shape (C order) | File |
|---|---|---|---|
| `x` | `<f4` | 5423 x 3137 | `copper/dataset1-5423x3137.x.f32.dat` |
| `y` | `<f4` | 5423 x 3137 | `copper/dataset1-5423x3137.y.f32.dat` |
| `z` | `<f4` | 5423 x 3137 | `copper/dataset1-5423x3137.z.f32.dat` |

### `copper-2`

`sdrbench.dataset("exaalt", "copper-2")` — folder `copper/` — 3 files, 1.1 GB, from [SDRBENCH-EXAALT-copper.tar.gz](https://g-d0cd3f.fd635.8443.data.globus.org/raw-data/EXAALT/SDRBENCH-EXAALT-copper.tar.gz).

Copper system, trajectory 2: positions x, y, z of 1077290 atoms over 83 time steps (time x atom).

| Field | dtype | Shape (C order) | File |
|---|---|---|---|
| `x` | `<f4` | 83 x 1077290 | `copper/dataset2-83x1077290.x.f32.dat` |
| `y` | `<f4` | 83 x 1077290 | `copper/dataset2-83x1077290.y.f32.dat` |
| `z` | `<f4` | 83 x 1077290 | `copper/dataset2-83x1077290.z.f32.dat` |

### `helium-1`

`sdrbench.dataset("exaalt", "helium-1")` — folder `helium/` — 3 files, 97.7 MB, from [SDRBENCH-EXAALT-helium.tar.gz](https://g-d0cd3f.fd635.8443.data.globus.org/raw-data/EXAALT/SDRBENCH-EXAALT-helium.tar.gz).

Helium system, trajectory 1: positions x, y, z of 1037 atoms over 7852 time steps (time x atom).

| Field | dtype | Shape (C order) | File |
|---|---|---|---|
| `x` | `<f4` | 7852 x 1037 | `helium/dataset1-7852x1037.x.f32.dat` |
| `y` | `<f4` | 7852 x 1037 | `helium/dataset1-7852x1037.y.f32.dat` |
| `z` | `<f4` | 7852 x 1037 | `helium/dataset1-7852x1037.z.f32.dat` |

### `helium-2`

`sdrbench.dataset("exaalt", "helium-2")` — folder `helium/` — 3 files, 3.0 GB, from [SDRBENCH-EXAALT-helium.tar.gz](https://g-d0cd3f.fd635.8443.data.globus.org/raw-data/EXAALT/SDRBENCH-EXAALT-helium.tar.gz).

Helium system, trajectory 2: positions x, y, z of 106711 atoms over 2338 time steps (time x atom).

| Field | dtype | Shape (C order) | File |
|---|---|---|---|
| `x` | `<f4` | 2338 x 106711 | `helium/dataset2-2338x106711.x.f32.dat` |
| `y` | `<f4` | 2338 x 106711 | `helium/dataset2-2338x106711.y.f32.dat` |
| `z` | `<f4` | 2338 x 106711 | `helium/dataset2-2338x106711.z.f32.dat` |

## Citation

Please cite SDRBench; `sdrbench cite exaalt` prints it:

```bibtex
@inproceedings{zhao2020sdrbench,
  title     = {{SDRBench}: Scientific Data Reduction Benchmark for Lossy Compressors},
  author    = {Zhao, Kai and Di, Sheng and Liang, Xin and Li, Sihuan and Tao, Dingwen and Chen, Zizhong and Cappello, Franck},
  booktitle = {2020 IEEE International Conference on Big Data (Big Data)},
  pages     = {2716--2724},
  year      = {2020}
}
```

## License and terms

The data are distributed by the SDRBench team for research use under the terms of the original
data providers listed above (see the [SDRBench website](https://sdrbench.github.io/datasets.html)); please acknowledge them as
requested. Rights remain with the data providers.