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Industrial
Industrial edge computing
Build flexible industrial edge systems with deterministic processing, secure connectivity, and low-latency sensor data handling.
Edge Computing for Real-Time Industrial Systems
Industrial systems move more data closer to machines, sensors, and control systems to reduce latency, improve reliability, and support real-time decisions across the factory.
Altera FPGAs provide flexible parallel data paths for sensor capture, preprocessing, industrial networking, security, and deterministic control, while Arm processors or host CPUs run higher-level software and adjacent AI compute.
The Challenges, and Why FPGA
The Challenge
Scaling cloud capabilities at the edge
Factories need cloud-like manageability without sending every workload and data stream to a remote cloud.
Why FPGA
Flexible edge platforms
FPGAs adapt to changing interfaces and workloads while keeping key processing close to the machine.
The challenge
Growing sensor data volumes
Connected machines generate more sensor, imaging, and control data than central systems can process efficiently.
Why FPGA
Parallel data processing
Parallel FPGA data paths handle capture, preprocessing, and network movement with predictable latency.
The Challenge
Security across the edge
Distributed edge nodes need trusted protection from hardware roots of trust through connected applications.
Why FPGA
Hardware security functions
Security IP can support encryption, authentication, and TLS 1.3 processing in the edge data path.
Why Altera
Deterministic connectivity
Connect sensors, controllers, and edge compute with low-latency industrial networking and time-sensitive traffic.
Flexible data processing
Process sensor and video streams in parallel while host CPUs run higher-level software and AI workloads.
Hardware security
Add hardware-based protection with security IP for encryption, authentication, and TLS 1.3 data paths.
Industrial edge ecosystem
Use reference designs, development kits, software, and partner solutions to move from evaluation to deployment.
Get Started
More Industrial Applications
Programmable Logic Controllers (PLCs)
Combine control logic, I/O, and industrial communications.
Machine vision and AI
Build custom image-processing and selected edge-inference pipelines.
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Semiconductor manufacturing equipment
Support precision control and inspection data processing.
Smart Energy
Enable intelligent energy systems with real-time monitoring, efficient power management, and adaptable FPGA solutions for modern smart grids.
Common Questions
An FPGA can aggregate industrial interfaces, preprocess sensor streams and accelerate supported local workloads. The gateway's processor can manage software and cloud communication while validated hardware paths handle timing-sensitive functions.
Run analytics locally when response time, uplink limits, availability or data-handling requirements demand it. Cloud services can still support fleet analysis and model management; define which functions must remain available during a network outage.
Check supported operators, precision, device targets and software versions, then validate converted-model accuracy and resources. Include preprocessing and transfers when measuring latency; inference-IP timing alone does not describe the full application.
Streaming preprocessing can reduce data volume and prepare the model's required format before inference. Benefits depend on the operations and buffering needs, so measure memory traffic and accuracy after the complete preprocessing chain.
Monitor input rates, buffer occupancy, memory arbitration and inference backpressure under simultaneous traffic. Check clock-domain crossings and host transfers to find which stage cannot sustain the workload.
A local data path can continue acquisition and supported inspection processing without cloud access. The complete system must also define local decision authority, result storage and later synchronization, with the required availability verified.