Whatagraph
Whatagraph keeps fixing what breaks when one account runs a thousand sources.
Comparison · Analytics
OpenMC vs tulpa
A side-by-side editorial comparison of OpenMC and tulpa — release velocity, themes, recent moves, and the top alternatives to consider.
OpenMC vs tulpa: at a glance
What is OpenMC?
OpenMC's random ray solver has gone from new arrival to the centre of every release
OpenMC is a Monte Carlo particle transport code for neutronics and radiation analysis. Since the random ray transport solver landed in 0.15.0 it has received substantial work in every subsequent release, most recently local adjoint sources, temperature and distributed-density feedback, fission-heating tallies and a weight-window bootstrapping workflow. The other consistent thread is shutdown-dose and depletion tooling, where 0.15.3 introduced an R2SManager to automate the rigorous two-step workflow and 0.16.0 extended it with reactivity control, CRAM substeps and multiple meshes.
What is tulpa?
The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.
tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.
OpenMC vs tulpa: editorial side-by-side
OpenMC
2.5ANALYTICS
OpenMC's random ray solver has gone from new arrival to the centre of every release
◆ Current state
OpenMC is a Monte Carlo particle transport code for neutronics and radiation analysis. Since the random ray transport solver landed in 0.15.0 it has received substantial work in every subsequent release, most recently local adjoint sources, temperature and distributed-density feedback, fission-heating tallies and a weight-window bootstrapping workflow. The other consistent thread is shutdown-dose and depletion tooling, where 0.15.3 introduced an R2SManager to automate the rigorous two-step workflow and 0.16.0 extended it with reactivity control, CRAM substeps and multiple meshes.
◆ Where it's heading
The project is layering a deterministic-adjacent solver alongside its Monte Carlo core rather than replacing it, and the ratio of random-ray work to core-solver work in each release keeps rising. In parallel it is packaging expert workflows into objects — R2SManager is the clearest case, turning a multi-stage shutdown dose calculation into a class rather than a recipe. The Python API is where most of that packaging surfaces, and it is also where the compatibility breaks land, with the minimum version moving to 3.12 in 0.16.0.
◆ Prediction
Given that every release since 0.15.0 has expanded the random ray solver's feedback and tally coverage, the next is likely to continue closing the gap between it and the main solver's feature set. The notes do not indicate whether it is intended to become a default path.
tulpa
7.5ANALYTICS
The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.
◆ Current state
tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.
◆ Where it's heading
Two moves in nine days point at the same destination: the generics conversion made tulpa extensible by downstream packages, and CRAN admission makes it installable by them. The current cadence — several tags a week, some existing only to record a measurement that produced no code change — does not survive CRAN's submission overhead, so the release rhythm has to slow whether or not the project intends it. The correctness work still clusters on the joint nested-Laplace driver, and 0.1.0 extends the same diagnostics habit with .NL_AXIS_SD_REASONS, a closed vocabulary for an outer axis whose grid does not contain its own posterior mode.
◆ Prediction
Expect tulpaObs to follow tulpa onto CRAN, since it is the consumer whose registrations the engine has spent this window unblocking, and expect the version line to move in larger, less frequent steps now that each one carries a submission.
Alternatives to OpenMC and tulpa
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either OpenMC or tulpa.
Lightdash
Lightdash keeps handing authoring to outside agents and keeping the governed layer for itself.
Delta Lake
A 4.4.0 tag appears, but the feed carries only its release plumbing
distributions3
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
Basedash
Basedash keeps pushing its data out of the workspace — now to people without accounts
RStudio
RStudio ships through release branches, and the notes are commit messages
See all OpenMC alternatives → · See all tulpa alternatives →
Recent activity from OpenMC and tulpa
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agotulpaFirst CRAN release: engine surface unchanged from 0.0.198 ⚡
- 5d agotulpatulpa_re_aghq() exposes the mode/theta cross-Hessian
- 8d agotulpaDense batched joint path could silently drop a grid cell
- 9d agotulpaCalibration and goodness-of-fit entry points become S3 generics ⚡
- 9d agotulpaCUDA backend had two definitions; link order decided if it ran
- 9d agotulpaHyperparameter bounds now flag when they leave the node range
- 14d agoOpenMCSurface-flux tallies and PDG particle identifiers in OpenMC 0.16.0
- 9mo agoOpenMCR2SManager automates shutdown dose rate calculations in OpenMC 0.15.3
- 1y agoOpenMCOpenMC 0.15.2 hotfixes an MPI regression
- 1y agoOpenMCRay-traced material volumes and Phong-shaded plots in OpenMC 0.15.1
- 2y agoOpenMCOpenMC 0.15.0 introduces a random ray transport solver ⚡
- 2y agoOpenMCWeight window generation and continuous nuclide feed in OpenMC 0.14.0
Frequently asked questions
What is the difference between OpenMC and tulpa?
They serve adjacent needs but don't currently overlap on shipped themes. tulpa is currently shipping more aggressively (velocity 7.5 vs 2.5), with 2 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is OpenMC better than tulpa?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tulpa is currently shipping more aggressively (velocity 7.5 vs 2.5), with 2 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to OpenMC?
Top OpenMC alternatives in Analytics are ranked by recent ship velocity. Browse the "OpenMC alternatives" section above for the current picks, or visit /alternatives/openmc for the full list with editorial commentary on each.
What are the best alternatives to tulpa?
Top tulpa alternatives in Analytics are ranked by recent ship velocity. Browse the "tulpa alternatives" section above for the current picks, or visit /alternatives/tulpa for the full list with editorial commentary on each.