# JuMP semidefinite programming - formulating via constraints versus variables

**URL:** <https://discourse.julialang.org/t/jump-semidefinite-programming-formulating-via-constraints-versus-variables/90832>\
**Category:** Optimization (Mathematical)\
**Tags:** jump\
**Created:** [November 25, 2022, 10:56pm UTC](https://discourse.julialang.org/t/jump-semidefinite-programming-formulating-via-constraints-versus-variables/90832 "2022-11-25T22:56:02Z")\
**Posts on this page:** 1\
**Showing post:** 5

<div class="post-metadata">

**Author:** ![greatpet](https://avatars.discourse-cdn.com/v4/letter/g/e495f1/32.png) [@greatpet](https://discourse.julialang.org/u/greatpet)\
**Post date:** [November 26, 2022, 11:45pm UTC](https://discourse.julialang.org/t/jump-semidefinite-programming-formulating-via-constraints-versus-variables/90832/5 "2022-11-26T23:45:00Z")

</div>

For large matrix sizes, I get much better accuracy if I use [Dualization.jl](https://github.com/jump-dev/Dualization.jl) (at least with the Mosek solver), probably due to how my problem is formulated, following [suggestions in another thread](https://discourse.julialang.org/t/solving-sdp-problem-is-100x-slower-than-matlab-cvx/79704/5).

---

_[View the full topic](https://discourse.julialang.org/t/jump-semidefinite-programming-formulating-via-constraints-versus-variables/90832)._