G2CPU v1.6.1 is finalized and has been handed over to NI for publishing.
Once NI completes their review and posting process, the update will appear on the LabVIEW Tools Network in the coming days.
In the meantime, a pre-release build is available for anyone who wants the performance improvements now.
To illustrate the difference, we recorded a side-by-side comparison of v1.6.1 and v1.6.0 using the same hardware, same LabVIEW application, and identical GPU dataflow. The performance gain is visible without explanation.
What’s Improved in v1.6.1
This release focuses on throughput and developer experience:
- Higher sustained GPU and CPU throughput for continuous workloads
- Lower overhead in data movement across host memory, GPU memory, and compute kernels
- Significantly improved IDE responsiveness when inspecting and handling large GPU arrays
- Smoother real-time execution in systems pushing high-bandwidth signals or large data frames
These improvements apply without changing your code. Existing G2CPU applications simply run faster and feel more responsive.
Why Performance at the IDE Level Matters
Many GPU acceleration toolkits deliver performance only inside the running application. G2CPU also targets the development loop itself.
Faster array inspection, quicker data handling, and reduced UI stalls allow you to iterate faster — the biggest multiplier in real-world LabVIEW workflows.
In other words:
v1.6.1 makes your system faster, and it makes you faster.
Pre-Release Access
The final release will be available on the LabVIEW Tools Network soon.
If you want the performance improvements now, use the pre-release.
Watch the Comparison Video
Upgrade Notes
- No API changes
- No diagram edits required
- Existing projects will load and run normally
This is a drop-in update intended to improve productivity and throughput immediately.
GPU Performance. LabVIEW Simplicity.
