Spectrum Instrumentation now offers driver support for the NVIDIA Clara AGX™, a universal computing architecture for the next generation of AI medical instruments. The new drivers enable scientists and developers to choose from 64 different Spectrum Digitizers, Arbitrary Waveform Generators (AWGs) and Digital I/O cards, letting the NVIDIA Clara AGX kit perform high-speed electronic signal acquisition and generation for analog and digital signals. With the big variety of cards to choose from, users can exactly match their electronic signal requirements.
The NVIDIA Clara AGX developer kit provides an easy-to-use platform for developing software-defined, AI-enabled, real-time, point-of-care medical devices. It delivers real-time streaming connectivity and AI inference by combining the flexibility of the NVIDIA® Jetson AGX Xavier™ embedded Arm® system on a chip (SoC), the performance of the integrated NVIDIA RTX™ 6000 GPU, and the 100 GbE connectivity of the NVIDIA ConnectX® SmartNIC, Clara AGX. The kit also includes full-stack GPU-accelerated libraries, SDKs, and reference applications for developers, data scientists, and researchers to create real-time, secure, and scalable solutions.
Adding a Spectrum card to the Clara system allows sensor signals to be acquired, generated, stored and processed. Data can be streamed between the cards, the processor and the GPU. In fact, the high-speed parallel processing capabilities of the GPU make it the perfect platform for handling the large volumes of data that can be acquired and generated by the Spectrum products. Spectrum already offers SCAPP (Spectrum’s CUDA Access for Parallel Processing) to make GPU-based data processing easily achievable, even at the fastest streaming rates.
Oliver Rovini, Chief Technical Officer at Spectrum, said, “We were delighted to be approached by NVIDIA, and partner with them to develop drivers for their NVIDIA Clara platform. Spectrum already has many customers using our technology in medical science. Now, together with the NVIDIA Clara, they have an easy way to create very small, low power systems, that offer some of the most advanced data processing tools available today.”
