# Memory blow-up when solving a sparse affine Hermitian SDP translated from YALMIP to JuMP

**URL:** <https://discourse.julialang.org/t/memory-blow-up-when-solving-a-sparse-affine-hermitian-sdp-translated-from-yalmip-to-jump/137744>\
**Category:** Optimization (Mathematical)\
**Tags:** jump, memory, dualization\
**Created:** [June 22, 2026, 3:10pm UTC](https://discourse.julialang.org/t/memory-blow-up-when-solving-a-sparse-affine-hermitian-sdp-translated-from-yalmip-to-jump/137744 "2026-06-22T15:10:11Z")\
**Posts on this page:** 1\
**Showing post:** 5

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**Author:** ![araujoms](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/araujoms/32/217734_2.png) [@araujoms](https://discourse.julialang.org/u/araujoms)\
**Post date:** [June 22, 2026, 8:27pm UTC](https://discourse.julialang.org/t/memory-blow-up-when-solving-a-sparse-affine-hermitian-sdp-translated-from-yalmip-to-jump/137744/5 "2026-06-22T20:27:47Z")

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My pleasure.

See this thread: [Bottleneck of JuMP](https://discourse.julialang.org/t/bottleneck-of-jump/136609) In a nutshell, there are two related problems: the first is that JuMP solves the primal problem by default, and YALMIP the dual. Here the dual happens to be more efficient. The second problem is a bug in Dualization.jl when dualising problems that use a non-native cone (here the complex PSD cone). There is a PR to fix it though: [[breaking] change DualOptimizer to not add bridges by default - Pull Request #209 - jump-dev/Dualization.jl - GitHub](https://github.com/jump-dev/Dualization.jl/pull/209)

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