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All IPs > Graphic & Peripheral > GPU > Trifecta-GPU

Trifecta-GPU

From RADX Technologies, Inc.

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Description

The Trifecta-GPU is a sophisticated family of COTS PXIe/CPCIe GPU Modules by RADX Technologies, designed for substantial computational acceleration and ease of use in PXIe/CPCIe platforms. Powered by the NVIDIA RTX A2000 Embedded GPU, it boasts up to 8.3 FP32 TFLOPS performance, becoming a preferred choice for modular Test & Measurement (T&M) and Electronic Warfare (EW) systems. It integrates seamlessly into systems, supporting MATLAB, Python, and C/C++ programming, making it versatile for signal processing, machine learning, and deep learning inference applications.

A highlight of the Trifecta-GPU is its remarkable computing prowess coupled with its design that fits within power and thermal constraints of legacy and modern chassis. It is available in both single and dual-slot variants, with the capability to dissipate power effectively, allowing users to conduct fast signal analysis and execute machine learning algorithms directly where data is acquired within the system.

With its peak performance setting new standards for cost-effective compute acceleration, the Trifecta-GPU also supports advanced computing frameworks, ensuring compatibility with a myriad of applications and enhancing signal classification and geolocation tasks. Its hardware capabilities are complemented by extensive software interoperability, supporting both Windows and Linux environments, further cementing its position as a top-tier solution for demanding applications.

Features
  • Supports MATLAB, Python, C/C++
  • NVIDIA CUDA and OpenCL integration
Tech Specs
Class Value
Categories Graphic & Peripheral > GPU
Processor > CPU
Processor > DSP Core
Processor > AI Processor
Platform Level IP > Multiprocessor / DSP
Platform Level IP > Processor Core Dependent
Platform Level IP > Processor Core Independent
GPU NVIDIA RTX A2000
TFLOPS 8.3 FP32
Memory 8GB GDDR6
PCIe Gen 4 x8
Outputs 4 x miniDP up to 4k
Power (W) 58W
Availability All Countries & Regions
Applications
  • Signal processing
  • Machine learning
  • Deep learning inference
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