21 Feb 2024

Viewer Performance Update (Part 1 of 3): Speedier SVF2 Loading

UPDATE: This is the first post in a three-part series on enhancements to the APS Viewer.

Viewer Performance Update:
Part 1 - Speedier SVF2 Loading

Part 2 - OPFS Caching
Part 3 - TBA

We're excited to announce the latest release of LMV performance improvements and SVF2-streaming delivery. You will be experiencing much faster loading times if you’re already using SVF2 viewing format. To make the most of these improvements, we recommend upgrading to Viewer 7.95 which will take advantage of these new streaming endpoints and make model loading times faster.

We’re seeing amazing results in our test scenarios. Tests on a Mac Pro M1 with 10 Navisworks models up to 2GB at a network speed of 250 Mbps showed improvements of 800% - 1600%.

 

size vs loading time

 

Since the initial introduction of SVF2 back in 2018, your valuable feedback has helped us to further enhance SVF2 performance, leading to another significant milestone for faster loading times.

SVF (Streaming Viewing Format) is a format designed for online model viewing over the web.  SVF2 is an enhanced version of SVF using web-sockets and de-duplication of data for versioned 'viewables'. The benefits include:

  • Significantly reduce the viewable storage size
  • Reduce model loading times compared to SVF
  • Quickly switch between views and versions of the same model

Today, we've added more improvements to SVF2, to both its client side and server side components to improve data throughput.  

Here's a side-by-side comparison video, of the New-SVF2-Streaming vs current-SVF2:
New "18 seconds" vs Old "3min 10seconds"

in this example, a 10x speedup...a very encouraging result !

Upgrade your viewer to the latest version (Viewer 7.95) and experiment with this new feature "SVF2-streaming" today.

We're eager to hear your results.  Share your experience with SVF2 streaming, by filling out this 1-minute form
Your insights are invaluable and help us shape the future of visualization.

 

Tags:

Related Article