Develop once, deploy anywhere with G²CPU.
Say goodbye to platform-specific code. Build your algorithm in G²CPU, and let the intelligent backend automatically select the optimal runtime—whether it’s a CUDA-enabled GPU, an OpenCL device, or a multithreaded CPU fallback.

Decisions are made dynamically at runtime, giving your customers the flexibility to pivot while you stay focused on what truly matters: delivering innovation.

Code the way you’re used to — now powered by GPU acceleration with G²CPU.

G²CPU simplifies GPU computingby mirroring familiar LabVIEW functions, so you can leverage your existing knowledge without a steep learning curve.

Easily scale your applications across multithreaded CPUs, CUDA GPUs, and OpenCL platforms — all from a unified development approach.

Catch errors early with G²CPU’s built-in code validation.
During development, G²CPU automatically analyzes your codeto detect syntax issues, incorrect array sizes, mismatched data types, and more — ensuring clean, reliable code from the start.

All before you even begin testing, so you can develop with confidence and speed.

Effortless GPU debugging with real-time data inspection in G²CPU.
Debugging GPU code has never been easier. Simply place a probeon your LabVIEW block diagramto instantly view live data — whether the computation runs on the CPU, CUDA, or OpenCL backend.

G²CPU’s smart probes not only capture values across platforms, but also help you analyze and interpret complex GPU data, streamlining your debugging process like never before.

Say goodbye to "out of memory" errors with G²CPU.

G²CPU intelligently monitors memory usage and system conditions in real time. Every function evaluates available resources and provides runtime feedback, helping you prevent crashes and bottlenecks before they happen.

Gain full control to handle system errors gracefully, ensuring maximum stability and performance across all platforms.

Full access and flexibility with G²CPU — no vendor lock-in.
G²CPU gives you complete control. Need direct access to data for custom function calls? You can do that anytime, without restrictions.

What’s more, you can seamlessly share memory pointerswith other environments using ArrayFire, enabling smooth collaboration and allowing other teams to pick up exactly where you left off.