At Embedded World North America 2026, Altera and its ecosystem partners showed how FPGA-based connectivity feeds real-time sensor data to NVIDIA GPUs, bringing AI-accelerated decisions closer to the edge.
September 28, 2026
The next generation of embedded systems will not be defined by compute alone. It will depend on how quickly, reliably, and intelligently systems can move data from the physical world into AI engines and turn insights back into action.
That message came through clearly at Embedded World North America 2026, held September 22–24 at the Anaheim Convention Center.
For Altera, the show provided an opportunity to highlight a growing collaboration with NVIDIA and demonstrate the role of FPGAs in high-performance edge AI architectures.
Connecting sensors to AI with flexibility and determinism
At the center of the story was NVIDIA Holoscan Sensor Bridge technology. The solution creates a high-bandwidth, low-latency path between real-world sensors and GPU-based AI processing, an increasingly important capability for robotics, industrial automation, intelligent video, medical systems, and other physical AI applications.
FPGAs are well suited to this role because they can provide deterministic processing, flexible I/O, and protocol adaptation close to the sensor. Rather than forcing every application into the same hardware configuration, FPGA-based designs can be tailored to performance, connectivity, and latency requirements of a specific system.
In the show’s keynote, NVIDIA Vice President Deepu Talla described the value of this flexibility: “You can select any of the Altera FPGAs depending on the application and pair them with any of the NVIDIA frameworks.” Altera’s post noted that Altera offers Holoscan Sensor Bridge solutions spanning 10G to 100G, where 25G and 100G offer significantly more bandwidth compared to other Holoscan ecosystem partners, helping developers scale connectivity for demanding edge workloads.
The result is a practical sensor-to-compute architecture: Altera FPGAs handle the flexible, deterministic front end, while NVIDIA platforms provide the accelerated environment for AI and robotics workloads.
An ecosystem approach to accelerating development
The demonstrations also underscored that successful edge AI deployments require more than individual components. Developers need reference designs, production-ready boards, and partners that help bridge the gap between evaluation and deployment.
Altera’s growing Holoscan ecosystem includes more than 10 reference designs and partner boards. These building blocks can help teams reduce integration effort and move faster from proof of concept to a real-time AI product.
One example was on display at Altera partner Critical Link’s booth. Critical Link was recognized as a Best in Show Award winner in the AI & Machine Learning category at the show. Visitors to the booth could see a live demonstration of a 5-camera Holoscan Sensor Bridge solution, using Critical Link’s MitySOM-A5E as the featured Agilex® 5 FPGA hardware platform.
The demonstration showed how an Agilex 5 FPGA-based system can help bring sensor data into an NVIDIA-powered AI pipeline while preserving the low-latency, high-bandwidth behavior required by edge applications.
From 10G to 100G: Building the data plane for edge AI
Altera’s Holoscan Sensor Bridge solutions are designed to make the sensor-to-GPU path faster and more adaptable. A recent Altera technical blog describes 10G, 25G, and 100G reference designs, including a 25G design on Agilex 5 SoC FPGAs for multi-camera sensor data flow and accelerated processing at the edge.
In this architecture, the FPGA serves as the data plane: connecting to diverse sensors, aggregating streams, adapting protocols, and preprocessing data before it reaches the NVIDIA GPU. That division of labor helps reduce data-movement bottlenecks while preserving deterministic timing and giving developers room to evolve the system as sensor interfaces and AI workloads change.
Altera Technical Holoscan blog for Robotics: Altera Pushes the Boundaries of Edge AI with New Holoscan Sensor Bridge Solutions | Altera Community - 355665
Watch the 25G Holoscan demo video: YouTube/Altera
Why the sensor-to-compute path matters
As AI moves into physical environments, system designers are balancing several competing requirements:
- Real-time response: Applications such as robotics and industrial inspection cannot always afford the delay of sending raw sensor data to a remote system.
- High-bandwidth data movement: Modern sensors generate increasingly rich data streams that must be transported without creating a bottleneck.
- Deterministic behavior: Safety-critical and industrial systems need predictable timing and consistent performance.
- Design flexibility: Product teams must support different sensors, interfaces, and deployment conditions without redesigning the entire platform.
- Faster development: Reference designs and ecosystem partnerships can shorten the path from concept to production.
The Altera and NVIDIA approach addresses these needs by combining FPGA-based connectivity and processing with GPU-accelerated AI. It gives developers a modular foundation for building systems that can adapt as sensors, models, and application requirements evolve.
Building what comes next at the edge
The conversation at Embedded World North America 2026 pointed toward a broader shift in embedded design. Edge systems are becoming intelligent, connected, and increasingly autonomous, but their performance still depends on the data path that feeds them.
By pairing Altera FPGAs with NVIDIA platforms and collaborating with partners such as Critical Link, developers gain more options for designing that path. The combination of flexible hardware, high-speed connectivity, and accelerated AI can help transform raw sensor input into timely decisions at the point where data is created.
For teams developing the next generation of robotics, industrial automation, intelligent vision, and physical AI systems, this is the opportunity: Build a sensor-to-compute architecture that is fast enough for today’s workloads, flexible enough for tomorrow’s requirements, and ready to scale from demonstration to deployment.
Learn more about Altera’s Physical AI-related Solutions:
Contributor