# Power Comparison calculix 2.21, 2.19, 2.2.18 to code aster 17.0

**URL:** <https://calculix.discourse.group/t/power-comparison-calculix-2-21-2-19-2-2-18-to-code-aster-17-0/3932>\
**Category:** Examples/Tutorials\
**Created:** [April 30, 2026, 2:47pm UTC](https://calculix.discourse.group/t/power-comparison-calculix-2-21-2-19-2-2-18-to-code-aster-17-0/3932 "2026-04-30T14:47:13Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Stefano4000](https://avatars.discourse-cdn.com/v4/letter/s/43a26b/32.png) [@Stefano4000](https://calculix.discourse.group/u/Stefano4000)\
**Post date:** [April 30, 2026, 2:47pm UTC](https://calculix.discourse.group/t/power-comparison-calculix-2-21-2-19-2-2-18-to-code-aster-17-0/3932/1 "2026-04-30T14:47:13Z")

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See [Decoding Performance: A Scalability Showdown Between CalculiX and Code\_Aster](https://www.linkedin.com/pulse/decoding-performance-scalability-showdown-between-calculix-poletto-3q3pf)

Static example, 4 Million tet10 elements  
Advantage calculix with PARDISO to 200.000 nodes per core  
Code\_aster here only half Performance.

Commercial pardiso is here extreme better with more cores than Intel MKL pardiso.

> **[Panua Technologies](https://panua.ch/pardiso/)**

So commercial users should include pardiso solver to safe computer resources, energy and time.

PaStiX is about 3 to 4 times better than Intel MKL Pardiso. But original Pardiso 8 is mostly more better in their benchmarks with factor 4 to 100 example dependent.

See academic work from year 2020: PaStiX to Intel MKL pardiso

> **[1575696.pdf](https://mediatum.ub.tum.de/doc/1575696/1575696.pdf)**