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16115845
] | [
16115845
] | null | null | 64,463,380 | 5943630868370f9fb98fb145205fa81d103347c2232618d15810581cd3f4886a |
region1 | yy/00068 | yy | 00068 | multi-timesteps/1840/00068-yy.f32 | <f4 | [
16115845
] | [
16115845
] | null | null | 64,463,380 | f0b048e773be43ad32ec6414b6583d24029c85cbf3fb73b40b63ad183260d25b |
region1 | zz/00068 | zz | 00068 | multi-timesteps/1840/00068-zz.f32 | <f4 | [
16115845
] | [
16115845
] | null | null | 64,463,380 | 64e6f1dad60a075e50bd0fad995d4542bacde9503e05776118dab2d86c40d480 |
region1 | xx/00070 | xx | 00070 | multi-timesteps/1840/00070-xx.f32 | <f4 | [
16113601
] | [
16113601
] | null | null | 64,454,404 | cea66cf595f099ffb5cdba8a771b9f5806b7d6131fb2070186932a7bab51353e |
region1 | yy/00070 | yy | 00070 | multi-timesteps/1840/00070-yy.f32 | <f4 | [
16113601
] | [
16113601
] | null | null | 64,454,404 | 4a1ef9eb97ff7878e81f9d553f79e7e3a3f01f3729a415999d4f7c21c00e2666 |
region1 | zz/00070 | zz | 00070 | multi-timesteps/1840/00070-zz.f32 | <f4 | [
16113601
] | [
16113601
] | null | null | 64,454,404 | ec99d578d68c6ff9e9fe0fa9d4f059ba283096949f6adbab46d818f23dea6930 |
region1 | xx/00072 | xx | 00072 | multi-timesteps/1840/00072-xx.f32 | <f4 | [
16111639
] | [
16111639
] | null | null | 64,446,556 | 2834692ce0b771ace7c1fb427c138c1e097a98aae712f126ca301fdb53055f2d |
region1 | yy/00072 | yy | 00072 | multi-timesteps/1840/00072-yy.f32 | <f4 | [
16111639
] | [
16111639
] | null | null | 64,446,556 | 7a364a1732c847c4a2477e796594ba1f88a6513fa24d3a74c79b87a8c3dcab53 |
region1 | zz/00072 | zz | 00072 | multi-timesteps/1840/00072-zz.f32 | <f4 | [
16111639
] | [
16111639
] | null | null | 64,446,556 | 5d6759bd58989b5c6a7dcdec0f2d2adcfde76a27be8f41049664ff3375ccee7a |
region1 | xx/00074 | xx | 00074 | multi-timesteps/1840/00074-xx.f32 | <f4 | [
16109740
] | [
16109740
] | null | null | 64,438,960 | c0ac66eb321b84691181094c872c81fb71a8387e0ed086a6d4294b6c02ddf493 |
region1 | yy/00074 | yy | 00074 | multi-timesteps/1840/00074-yy.f32 | <f4 | [
16109740
] | [
16109740
] | null | null | 64,438,960 | 0bc487e9987f22d4dc67a8168b89da74d44b8da52aec5be28b2d5b0dab26a7be |
region1 | zz/00074 | zz | 00074 | multi-timesteps/1840/00074-zz.f32 | <f4 | [
16109740
] | [
16109740
] | null | null | 64,438,960 | a7a40090d55951942de851794f4c5dadaa592750ba34ec735846881477ec63fc |
region1 | xx/00076 | xx | 00076 | multi-timesteps/1840/00076-xx.f32 | <f4 | [
16107873
] | [
16107873
] | null | null | 64,431,492 | 1974491b2ed50a38aa5848a4d2b46e49037f9cfb0d399680372dbe2b022b96b8 |
region1 | yy/00076 | yy | 00076 | multi-timesteps/1840/00076-yy.f32 | <f4 | [
16107873
] | [
16107873
] | null | null | 64,431,492 | fd446235df3059c3793a11032b1b1c75793896d7194d563e3e84144baa651dbf |
region1 | zz/00076 | zz | 00076 | multi-timesteps/1840/00076-zz.f32 | <f4 | [
16107873
] | [
16107873
] | null | null | 64,431,492 | 2e7a2b06db253336c42b6b1271098c72d96d4c9eb0fc40a96b1971b289df8d74 |
region1 | xx/00077 | xx | 00077 | multi-timesteps/1840/00077-xx.f32 | <f4 | [
16106907
] | [
16106907
] | null | null | 64,427,628 | 636716ee2c4c743061e84ba3544e58537e01fcf5b6709ae02936430bb0e007dc |
region1 | yy/00077 | yy | 00077 | multi-timesteps/1840/00077-yy.f32 | <f4 | [
16106907
] | [
16106907
] | null | null | 64,427,628 | 739ad679583444897c2fce1c9fc2849443d0f5122f95d76e30fe114006eb20f9 |
region1 | zz/00077 | zz | 00077 | multi-timesteps/1840/00077-zz.f32 | <f4 | [
16106907
] | [
16106907
] | null | null | 64,427,628 | 3a6e916d24615b057a3ad1c7509e03c9d34c8bcfd1deb192e6a8f54f97de7dfb |
region1 | xx/00079 | xx | 00079 | multi-timesteps/1840/00079-xx.f32 | <f4 | [
16105047
] | [
16105047
] | null | null | 64,420,188 | 1b2f32f94035a052b294099df0be5238c8a47c49956cfd568f09e8af6333a386 |
region1 | yy/00079 | yy | 00079 | multi-timesteps/1840/00079-yy.f32 | <f4 | [
16105047
] | [
16105047
] | null | null | 64,420,188 | 0c52e23510cf2dd6a5055a7898d0484fa5f6b3610c9243f89774040c82cdda52 |
region1 | zz/00079 | zz | 00079 | multi-timesteps/1840/00079-zz.f32 | <f4 | [
16105047
] | [
16105047
] | null | null | 64,420,188 | 0ce2e15e25d12e32fcd85b8a6477a50447bc93ffc999bd93163d83d5bf6a7fd0 |
region1 | xx/00081 | xx | 00081 | multi-timesteps/1840/00081-xx.f32 | <f4 | [
16103035
] | [
16103035
] | null | null | 64,412,140 | acf666f455597271dbc2ce4f8a121ba5af86085b686b547e6ad6705b7f617824 |
region1 | yy/00081 | yy | 00081 | multi-timesteps/1840/00081-yy.f32 | <f4 | [
16103035
] | [
16103035
] | null | null | 64,412,140 | bc3dc0b584d710125809d32e87fabde0a6287663b674ffa239122b555164ee6e |
region1 | zz/00081 | zz | 00081 | multi-timesteps/1840/00081-zz.f32 | <f4 | [
16103035
] | [
16103035
] | null | null | 64,412,140 | e612fecad377f67537c99ada622627572b5dd90729637153bb2edbcce47f53a4 |
End of preview. Expand in Data Studio
SDRBench — HACC
Cosmology N-body simulation (HACC, ECP ExaSky): particle coordinates xx, yy, zz and velocities vx, vy, vz as separate 1D arrays, single precision, little-endian.
Raw binary arrays, not an Arrow/Parquet dataset.
datasets.load_dataset("sdrbench/hacc")returns the table of files (files.jsonl: path, dtype, shape, sha256). Read the arrays with thesdrbenchpackage orhf_hub_download+ numpy as shown below.
This repository is an unmodified mirror of the HACC data of SDRBench, 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 36891dee00). metadata/ holds
the original SDRBench property and template files. Kept in sync automatically by
szcompressor/sdrbench.
- Data provider: HACC team (ECP ExaSky); https://www.alcf.anl.gov/science/case-studies/opencosmo-community-portal-cosmological-simulations
- Size: 150.2 GB in 8 variant(s)
- Format: raw little-endian binary, C order (slowest dimension first); dtype and shape per field below
Citation requested by the data provider: Please cite Heitmann et al., Astrophys. J. Suppl. 252 (2021) 2, 19 (https://inspirehep.net/literature/1799008) when using HACC data.
Usage
pip install "sdrbench[sz3]" # sdrbench + pysz (SZ3)
import numpy as np
import sdrbench
from pysz import sz, szConfig, szErrorBoundMode
ds = sdrbench.dataset("hacc") # default variant "medium"
print(ds.fields)
x = ds["vx"] # numpy array, dtype <f4, shape (280953867,)
# 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("hacc", root="/path").
Without the package, with huggingface_hub and numpy only:
from huggingface_hub import hf_hub_download
import numpy as np
p = hf_hub_download("sdrbench/hacc", "medium/vx.f32", repo_type="dataset", revision="36891dee003a1aa08bb7da3c3e6b90badcd661e6")
x = np.fromfile(p, dtype="<f4").reshape((280953867,))
Variants and fields
medium (default)
sdrbench.dataset("hacc", "medium") — folder medium/ — 8 files, 6.7 GB, from EXASKY-HACC-data-medium-size.tar.gz.
One snapshot with 280,953,867 particles.
| Field | dtype | Shape (C order) | File |
|---|---|---|---|
vx |
<f4 |
280953867 | medium/vx.f32 |
vy |
<f4 |
280953867 | medium/vy.f32 |
vz |
<f4 |
280953867 | medium/vz.f32 |
xx |
<f4 |
280953867 | medium/xx.f32 |
yy |
<f4 |
280953867 | medium/yy.f32 |
zz |
<f4 |
280953867 | medium/zz.f32 |
Other files: medium/EXASKY-HACC-data-medium-size-property.txt, medium/EXASKY-HACC-data-medium-size-template_data.txt
big
sdrbench.dataset("hacc", "big") — folder big/ — 8 files, 25.8 GB, from EXASKY-HACC-data-big-size.tar.gz.
One snapshot with 1,073,726,487 particles.
| Field | dtype | Shape (C order) | File |
|---|---|---|---|
vx |
<f4 |
1073726487 | big/vx.f32 |
vy |
<f4 |
1073726487 | big/vy.f32 |
vz |
<f4 |
1073726487 | big/vz.f32 |
xx |
<f4 |
1073726487 | big/xx.f32 |
yy |
<f4 |
1073726487 | big/yy.f32 |
zz |
<f4 |
1073726487 | big/zz.f32 |
Other files: big/EXASKY-HACC-data-big-size-property.txt, big/template_data_big-size.txt
sbig
sdrbench.dataset("hacc", "sbig") — folder sbig/ — 3 files, 19.5 GB, from SDRBENCH-EXASKY-HACC-data-sbig-size.tar.gz.
One region (1/768) of time step 499 of a trillion-particle run: coordinates only.
| Field | dtype | Shape (C order) | File |
|---|---|---|---|
xx |
<f4 |
1621417608 | sbig/27035-xx.f32 |
yy |
<f4 |
1621417608 | sbig/27035-yy.f32 |
zz |
<f4 |
1621417608 | sbig/27035-zz.f32 |
region1
sdrbench.dataset("hacc", "region1") — folder multi-timesteps/1840/ — 304 files, 19.5 GB, from 1840.tar.gz.
Region 1840: coordinates xx, yy, zz over about 100 time steps (the particle count changes per step) and the particle IDs.
4 variable(s) x 101 steps (00042 ... 00499): ds.series("xx"), ds["xx", "00042"].
| Field | dtype | Shape (C order) | File |
|---|---|---|---|
xx/00042 |
<f4 |
16141859 | multi-timesteps/1840/00042-xx.f32 |
yy/00042 |
<f4 |
16141859 | multi-timesteps/1840/00042-yy.f32 |
zz/00042 |
<f4 |
16141859 | multi-timesteps/1840/00042-zz.f32 |
xx/00043 |
<f4 |
16140933 | multi-timesteps/1840/00043-xx.f32 |
yy/00043 |
<f4 |
16140933 | multi-timesteps/1840/00043-yy.f32 |
zz/00043 |
<f4 |
16140933 | multi-timesteps/1840/00043-zz.f32 |
xx/00044 |
<f4 |
16139797 | multi-timesteps/1840/00044-xx.f32 |
yy/00044 |
<f4 |
16139797 | multi-timesteps/1840/00044-yy.f32 |
zz/00044 |
<f4 |
16139797 | multi-timesteps/1840/00044-zz.f32 |
xx/00045 |
<f4 |
16138878 | multi-timesteps/1840/00045-xx.f32 |
| ... 294 more |
region2
sdrbench.dataset("hacc", "region2") — folder multi-timesteps/20000/ — 304 files, 19.6 GB, from 20000.tar.gz.
Region 20000: coordinates xx, yy, zz over about 100 time steps (the particle count changes per step) and the particle IDs.
4 variable(s) x 101 steps (00042 ... 00499): ds.series("xx"), ds["xx", "00042"].
| Field | dtype | Shape (C order) | File |
|---|---|---|---|
xx/00042 |
<f4 |
16153547 | multi-timesteps/20000/00042-xx.f32 |
yy/00042 |
<f4 |
16153547 | multi-timesteps/20000/00042-yy.f32 |
zz/00042 |
<f4 |
16153547 | multi-timesteps/20000/00042-zz.f32 |
xx/00043 |
<f4 |
16152817 | multi-timesteps/20000/00043-xx.f32 |
yy/00043 |
<f4 |
16152817 | multi-timesteps/20000/00043-yy.f32 |
zz/00043 |
<f4 |
16152817 | multi-timesteps/20000/00043-zz.f32 |
xx/00044 |
<f4 |
16152061 | multi-timesteps/20000/00044-xx.f32 |
yy/00044 |
<f4 |
16152061 | multi-timesteps/20000/00044-yy.f32 |
zz/00044 |
<f4 |
16152061 | multi-timesteps/20000/00044-zz.f32 |
xx/00045 |
<f4 |
16151268 | multi-timesteps/20000/00045-xx.f32 |
| ... 294 more |
region3
sdrbench.dataset("hacc", "region3") — folder multi-timesteps/24120/ — 304 files, 19.6 GB, from 24120.tar.gz.
Region 24120: coordinates xx, yy, zz over about 100 time steps (the particle count changes per step) and the particle IDs.
4 variable(s) x 101 steps (00042 ... 00499): ds.series("xx"), ds["xx", "00042"].
| Field | dtype | Shape (C order) | File |
|---|---|---|---|
xx/00042 |
<f4 |
16156722 | multi-timesteps/24120/00042-xx.f32 |
yy/00042 |
<f4 |
16156722 | multi-timesteps/24120/00042-yy.f32 |
zz/00042 |
<f4 |
16156722 | multi-timesteps/24120/00042-zz.f32 |
xx/00043 |
<f4 |
16156136 | multi-timesteps/24120/00043-xx.f32 |
yy/00043 |
<f4 |
16156136 | multi-timesteps/24120/00043-yy.f32 |
zz/00043 |
<f4 |
16156136 | multi-timesteps/24120/00043-zz.f32 |
xx/00044 |
<f4 |
16155596 | multi-timesteps/24120/00044-xx.f32 |
yy/00044 |
<f4 |
16155596 | multi-timesteps/24120/00044-yy.f32 |
zz/00044 |
<f4 |
16155596 | multi-timesteps/24120/00044-zz.f32 |
xx/00045 |
<f4 |
16154795 | multi-timesteps/24120/00045-xx.f32 |
| ... 294 more |
region4
sdrbench.dataset("hacc", "region4") — folder multi-timesteps/30210/ — 304 files, 19.6 GB, from 30210.tar.gz.
Region 30210: coordinates xx, yy, zz over about 100 time steps (the particle count changes per step) and the particle IDs.
4 variable(s) x 101 steps (00042 ... 00499): ds.series("xx"), ds["xx", "00042"].
| Field | dtype | Shape (C order) | File |
|---|---|---|---|
xx/00042 |
<f4 |
16160806 | multi-timesteps/30210/00042-xx.f32 |
yy/00042 |
<f4 |
16160806 | multi-timesteps/30210/00042-yy.f32 |
zz/00042 |
<f4 |
16160806 | multi-timesteps/30210/00042-zz.f32 |
xx/00043 |
<f4 |
16160342 | multi-timesteps/30210/00043-xx.f32 |
yy/00043 |
<f4 |
16160342 | multi-timesteps/30210/00043-yy.f32 |
zz/00043 |
<f4 |
16160342 | multi-timesteps/30210/00043-zz.f32 |
xx/00044 |
<f4 |
16159646 | multi-timesteps/30210/00044-xx.f32 |
yy/00044 |
<f4 |
16159646 | multi-timesteps/30210/00044-yy.f32 |
zz/00044 |
<f4 |
16159646 | multi-timesteps/30210/00044-zz.f32 |
xx/00045 |
<f4 |
16158914 | multi-timesteps/30210/00045-xx.f32 |
| ... 294 more |
region6
sdrbench.dataset("hacc", "region6") — folder multi-timesteps/4529/ — 304 files, 19.9 GB, from 4529.tar.gz.
Region 4529: coordinates xx, yy, zz over about 100 time steps (the particle count changes per step) and the particle IDs.
4 variable(s) x 101 steps (00042 ... 00499): ds.series("xx"), ds["xx", "00042"].
| Field | dtype | Shape (C order) | File |
|---|---|---|---|
xx/00042 |
<f4 |
16211251 | multi-timesteps/4529/00042-xx.f32 |
yy/00042 |
<f4 |
16211251 | multi-timesteps/4529/00042-yy.f32 |
zz/00042 |
<f4 |
16211251 | multi-timesteps/4529/00042-zz.f32 |
xx/00043 |
<f4 |
16211574 | multi-timesteps/4529/00043-xx.f32 |
yy/00043 |
<f4 |
16211574 | multi-timesteps/4529/00043-yy.f32 |
zz/00043 |
<f4 |
16211574 | multi-timesteps/4529/00043-zz.f32 |
xx/00044 |
<f4 |
16212106 | multi-timesteps/4529/00044-xx.f32 |
yy/00044 |
<f4 |
16212106 | multi-timesteps/4529/00044-yy.f32 |
zz/00044 |
<f4 |
16212106 | multi-timesteps/4529/00044-zz.f32 |
xx/00045 |
<f4 |
16212596 | multi-timesteps/4529/00045-xx.f32 |
| ... 294 more |
Citation
Please cite SDRBench and the data provider (see above); sdrbench cite hacc prints it:
@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); please acknowledge them as requested. Rights remain with the data providers.
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