GPU-Accelerated Compression for High-Speed Acquisition Systems Modern test and measurement systems are increasingly defined by a single constraint: not compute performance, but the ability to move, store, and retain data at scale. As digitizer bandwidth continues to increase, systems quickly encounter limits in storage throughput, network capacity, and the rising cost of high-performance NVMe infrastructure. G2CPU v1.7.0 introduces Test & Measurement ZIP, a GPU-accelerated compression feature designed specifically for high-speed acquisition workloads. Built on the foundation of NVIDIA NVCOMP, it extends GPU compression with G2CPU-specific optimizations for continuous waveform capture, instrument streaming, and high-throughput measurement workloads. Rather than treating compression as a post-processing step, it is integrated directly into the acquisition pipeline, enabling real-time data reduction at full streaming speeds without disrupting capture. In PXIe-class environments, G2CPU v1.

G2CPU V1.7.0 adds NVIDIA CUDA IPC support, showing how separate GPU-enabled applications can share data efficiently. The post explains the new functions and a LabVIEW example for real-time signal sharing.

G2CPU 1.6.2 delivers major latency reductions and adds event stream APIs, GPU pointer access, and JIT control, with a new example for efficient GPU-based array indexing and reordering.

We’re hard at work on a LabVIEW-native RTSA toolkit using G2CPU, delivering full-bandwidth real-time analysis. Experience zero-span at full rate, real-time PSD, over 1 billion FFTs/s for ultra-low POI, and extremely large FFTs for low RBW.

Experience the boost! G2CPU v1.6.1 loads faster and delivers higher throughput than ever before, pushing your LabVIEW GPU workflows to new speeds.

Learn how the G2CPU Zero Copy API boosts LabVIEW performance by linking NI DMA and CUDA DMA directly. Eliminate data copies, reduce CPU load, and stream up to 7 GB/s between NI PXI hardware and GPUs. Unlock faster, more efficient CUDA data processing