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About
QS-DMSS is created, managed, and maintained by AI-Bio Synergy Holdings LLC.
QS-DMSS Studio https://qs-dmss.studio is the public front door for QS-DMSS: an evidence-first
simulation lab for reproducible runs, evidence bundles, campaign comparison,
and research-object exports.
The project combines deterministic simulation runs, evidence bundles, replay/verification, Campaign Studio parameter studies, publication-ready research object exports, and dry-run Slurm request bundles for HPC review.
Current milestone: v0.9.0
QS-DMSS now gives reviewers and research computing teams a stable PyPI install path plus a dry-run Slurm workflow that emits reviewable scheduler artifacts without submitting jobs. This is designed to help the project move carefully toward site-policy-aware HPC execution while preserving trust, auditability, and reproducibility.
Support funds open-source stewardship, maintenance, documentation,
reproducibility infrastructure, and public build milestones. Funding does not
imply scientific endorsement or peer-reviewed validation.
Specific funding needs:
- Public package maintenance across PyPI, GitHub, and Zenodo
- Reproducibility tooling: evidence bundles, replay, verification, and reports
- Campaign Studio and Lab Mode development
- HPC/RSE review pathways before real scheduler connectors
- Documentation, onboarding, validation scenarios, and contributor support
Current public release:
- PyPI: https://pypi.org/project/qs-dmss/0.9.0/
- GitHub: https://github.com/AI-Bio-Synergy-Holdings-LLC/QS-DMSS
- v0.9.0 release: https://github.com/AI-Bio-Synergy-Holdings-LLC/QS-DMSS/releases/tag/v0.9.0
- Zenodo DOI: https://doi.org/10.5281/zenodo.20693736
- HPC site-policy review issue: https://github.com/AI-Bio-Synergy-Holdings-LLC/QS-DMSS/issues/99
QS-DMSS is beta software for reproducible package/evidence workflows. It does not claim peer-reviewed scientific validation or production HPC submission support yet.
Note:
QS-DMSS v0.9.0 remains the stable public package baseline. Current main now adds a source-only Fractal/Quadrant SSFM validation harness, and we are collecting technical review on #105 before any GPU expansion, v0.10.0 release prep, or decision-metric UI work: https://github.com/AI-Bio-Synergy-Holdings-LLC/QS-DMSS/issues/105
QS-DMSS Studio https://qs-dmss.studio is the public front door for QS-DMSS: an evidence-first
simulation lab for reproducible runs, evidence bundles, campaign comparison,
and research-object exports.
The project combines deterministic simulation runs, evidence bundles, replay/verification, Campaign Studio parameter studies, publication-ready research object exports, and dry-run Slurm request bundles for HPC review.
Current milestone: v0.9.0
QS-DMSS now gives reviewers and research computing teams a stable PyPI install path plus a dry-run Slurm workflow that emits reviewable scheduler artifacts without submitting jobs. This is designed to help the project move carefully toward site-policy-aware HPC execution while preserving trust, auditability, and reproducibility.
Support funds open-source stewardship, maintenance, documentation,
reproducibility infrastructure, and public build milestones. Funding does not
imply scientific endorsement or peer-reviewed validation.
Specific funding needs:
- Public package maintenance across PyPI, GitHub, and Zenodo
- Reproducibility tooling: evidence bundles, replay, verification, and reports
- Campaign Studio and Lab Mode development
- HPC/RSE review pathways before real scheduler connectors
- Documentation, onboarding, validation scenarios, and contributor support
Current public release:
- PyPI: https://pypi.org/project/qs-dmss/0.9.0/
- GitHub: https://github.com/AI-Bio-Synergy-Holdings-LLC/QS-DMSS
- v0.9.0 release: https://github.com/AI-Bio-Synergy-Holdings-LLC/QS-DMSS/releases/tag/v0.9.0
- Zenodo DOI: https://doi.org/10.5281/zenodo.20693736
- HPC site-policy review issue: https://github.com/AI-Bio-Synergy-Holdings-LLC/QS-DMSS/issues/99
QS-DMSS is beta software for reproducible package/evidence workflows. It does not claim peer-reviewed scientific validation or production HPC submission support yet.
Note:
QS-DMSS v0.9.0 remains the stable public package baseline. Current main now adds a source-only Fractal/Quadrant SSFM validation harness, and we are collecting technical review on #105 before any GPU expansion, v0.10.0 release prep, or decision-metric UI work: https://github.com/AI-Bio-Synergy-Holdings-LLC/QS-DMSS/issues/105
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