PXIe-GPU Compute & Graphics
Catalyst-GPU
PXI GPU | PXIe GPU | CPCI GPU | CPCIe GPU
Catalyst-GPUs are COTS products that bring cost-effective, easy-to-program, high-performance GPU compute acceleration and advanced graphics capabilities of NVIDIA professional GPUs, from Ampere to Ada Lovelace to Blackwell, to the PXIe/CPCIe platform. The Catalyst-GPU family spans entry-level RTX A1000 through high-performance Ada RTX 4000 SFF and Blackwell RTX Pro 4000 SFF, plus the NVIDIA L4 Data Center GPU for AI inference workloads.
Unmatched GPU Compute Performance — Where Data is Acquired
The Catalyst-GPU family now spans from the entry-level NVIDIA RTX A1000 (4.0 FP32 TFLOPs, 8 GB GDDR6) through the Ada Lovelace RTX 2000 SFF (12.0 TFLOPs, 16 GB) and RTX 4000 SFF (19.2 TFLOPs, 20 GB), up to the new Blackwell RTX Pro 2000 SFF (~20 TFLOPs, 24 GB GDDR7) and RTX Pro 4000 SFF (~40 TFLOPs, 32 GB GDDR7). All models fit in a single PXIe/CPCIe slot at 50–70 W TGP, compatible with all NI and 3rd-party PXIe chassis.
FFT Performance vs. Embedded Controller
RADX Catalyst-GPU PXIe-GPU-T1000-8GB Average Performance Gains Versus Intel Xeon W-2245 8C/16T 3.9 GHz Embedded Controller Under (Windows 10) MATLAB and Python on 1k to 32M Point FP32 FFTs
ML/DL AI Acceleration
Catalyst-GPUs deliver dramatic AI inference and training acceleration over CPU-only PXIe embedded controllers. Ada and Blackwell generation GPUs add dedicated 4th-gen Tensor Cores and hardware-accelerated ray tracing. The NVIDIA L4 Data Center GPU (30.3 TFLOPs FP32, 24 GB GDDR6, 72 W) is purpose-built for AI inference, video analytics, and mixed-precision workloads in thermally constrained PXIe chassis.
RADX Catalyst-GPU Performance Gain vs. NI PXIe-8881 Intel Xeon W-2245 8C/16T 3.9 GHz Embedded Controller on MATLAB FP32 Win20 DL Inference Benchmarks
Improved Accuracy & RBW for LPI Signal Processing
Catalyst-GPU supports arbitrary-length FFT, PSD, Correlation, and other DSP algorithms. In most FPGAs, the longest practical FFT lengths are typically 8k points. In Catalyst-GPUs, 1M-point and longer FFTs are practical and may be executed in real-time or near-real-time. With longer FFTs, Low Probability of Intercept (LPI) signals become readily detectable and characterizable.
LPI Signal Detection — Arbitrary Length FFT
Same signal captured with 8k-point FFT (left) vs. 1M-point FFT (right) on Catalyst-GPU. Longer FFTs dramatically
reduce RBW, resolving signals buried in the noise floor.
8K FFT — Signal Buried in Noise
Wide RBW masks LPI signal
1M FFT — Signals Clearly Resolved
Narrow RBW reveals LPI peaks
Catalyst-GPU supports 1M+ point FFTs in real-time — enabling detection and characterization of Low Probability of Intercept (LPI) signals.
Easy-to-Program via MATLAB, Python, and C/C++
Catalyst-GPUs support programming via MATLAB™, Python, and C/C++ with NVIDIA CUDA® and OpenCL® acceleration. They support both Windows and Linux operating environments, as well as popular AI frameworks including TensorFlow, PyTorch, RAPIDS AI, and RAPIDS cuSignal. All models expose a standard PCIe Gen 4 ×16 host interface to the PXIe system controller.
- All Catalyst-GPU models are based on RADX patent-pending Catalyst-X™ design, single-slot PXIe/CPCIe form factor, BAA/TAA Compliant, Designed and Assembled in the USA, and available on GSA via GSAMart by TestMart. Contact RADX sales for current pricing and availability.
| RADX Catalyst-GPU Family — PXIe/CPCIe GPU Modules & SKUs | ||||||
| All models: single-slot PXIe/CPCIe · PCIe Gen 4 ×16 host interface · BAA/TAA Compliant · Designed and Assembled in the USA | ||||||
| Part Number | GPU | Architecture | VRAM | FP32 Compute | TGP | Display Outputs |
|---|---|---|---|---|---|---|
| PXIe-GPU-RTX-A1k | NVIDIA RTX A1000 | Ampere | 8 GB GDDR6 | 4.0 TFLOPS | 50 W | 4× mDP 1.4 |
| PXIe-GPU-Ada-RTX-2k-SFF | NVIDIA RTX 2000 Ada SFF | Ada Lovelace | 16 GB GDDR6 | 12.0 TFLOPS | 70 W | 4× mDP 1.4 |
| PXIe-GPU-Ada-RTX-4k-SFF | NVIDIA RTX 4000 Ada SFF | Ada Lovelace | 20 GB GDDR6 | 19.2 TFLOPS | 70 W | 4× mDP 1.4 |
| PXIe-GPU-Blk-RTXPro-2k-SFF | NVIDIA RTX Pro 2000 Blackwell SFF | BlackwellNew | 24 GB GDDR7 | ~20 TFLOPS | 70 W | 4× mDP 2.1 |
| PXIe-GPU-Blk-RTXPro-4k-SFF | NVIDIA RTX Pro 4000 Blackwell SFF | BlackwellNew | 32 GB GDDR7 | ~40 TFLOPS | 70 W | 4× mDP 2.1 |
| PXIe-GPU-Ada-L4-DC | NVIDIA L4 Data Center GPU | Ada LovelaceAI/Inference | 24 GB GDDR6 | 30.3 TFLOPS | 72 W | None (compute only) |
Pricing is FOB San Jose, CA and excludes US import tariffs not in effect prior to RADX PO acceptance. BAA & TAA Compliant. Available on GSA via GSAMart by TestMart. Delivery: ~30–60 days ARO. Contact RADX for volume and educational pricing.
Compliance & Standards
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Contact RADX sales or download the datasheet for full specifications.