Very slow slicing speed on Ubuntu compared to PrusaSlicer

[Leonti]

Is there an existing issue for this problem?

• [X] I have searched the existing issues

OrcaSlicer Version

2.1.1

Operating System (OS)

Linux

OS Version

Ubuntu 22.04

Additional system information

CPU: Ryzen 7 2700X 3.7 GHz 8-Core Processor GPU: Nvidia GTX 1050 (driver version: 535.183.01)

Printer

Voron Trident

How to reproduce

1. Add an STL to a plate, I used front_skirt_a_300.stl
2. Slice the plate using 0.20mm Standard @Voron system preset by pressing Slice plate button and stopwatch on the phone
3. Press stopwatch end once slicing is finished
4. Slice the same model on PrusaSlicer with a similar profile and capture slicing speed with the same stopwatch

Actual results

The place is finished with OrcaSlicer in 8s The plate is finished in 1-2 seconds with PrusaSlicer

Expected results

Similar slicing speeds. The effect is even more pronounced with big plates, sometimes I have to wait for a minute or even more to get a plate sliced.

Project file & Debug log uploads

debug_Mon_Aug_05_18_58_31_110998.log.zip front_skirt_a_300.zip

Checklist of files to include

• [X] Log file
• [X] Project file

Anything else?

I realize that this kind of problems are hard to debug and probably system-specific, so I guess at this stage I'm looking for ways to provide more relevant information. I run it with ./OrcaSlicer_Linux_V2.1.1.AppImage --debug 5, but logs don't seem to include anything related to performance.

[tlhintoq]

Are your supports set to Tree | Strong ? I have an open ticket for Tree strong taking 24hrs on a big job while the same slice using Tree|Default takes 10mins

[Leonti]

Are your supports set to Tree | Strong ? I have an open ticket for Tree strong taking 24hrs on a big job while the same slice using Tree|Default takes 10mins

I don't have supports enabled, but I tried different supports for testing just now and the time was still around 8s for the same model.

As another data point I tried downloading OrcaSlicer 2.1.1 on another machine, also running Ubuntu 22.04 and had very similar performance results.