Altera and Intel are collaborating to accelerate the development of intelligent systems across industries.
Intel Corp. and Altera Corp. today said they are jointly developing flexible, real-time, sensor-bridge reference systems for edge and physical AI applications including robotics. By combining Intel compute, connectivity, and software with Altera field-programmable gate arrays or FPGAs, the companies said they aim to help manufacturers address the growing complexity of connecting, processing, and acting on real-world data across increasingly sensor-rich environments.
“Physical AI systems have to sense, decide, and act in real time, and the physical world demands accuracy, reliability, and safety,” stated Farhad Shafai, head of business solutions and marketing at Altera. “Altera FPGAs provide the sensor connectivity, data processing, and deterministic control that machines need to respond to the physical world, and they stay programmable as sensors and AI models evolve. Combining that with Intel’s compute and software is intended to give OEMs a flexible foundation to tailor systems to their needs.’
Founded in 1983, Altera provides high-performance, programmable compute and connectivity systems for a wide range of advanced and AI-enabled technologies. The San Jose, Calif.-based company claimed that it
is “the largest pure-play FPGA provider with a full-spectrum portfolio serving applications ranging from data centers and communications networks to critical embedded systems.”
Intel acquired Altera for $16.7 billion in 2015 and sold 51% of the company to Silver Lake last year.
Sensor-rich edge environments pose challenges for AI
“Edge and physical AI systems can require data from different sensors and interfaces to be brought together while meeting requirements for timing, performance, power and cost,” said Intel and Altera. “Some applications also require very high bandwidth or flexible form factors in which input/output (I/O) is located away from the compute board. Sensor data must then be streamed rapidly into memory for the host Intel processor to use across edge, robotics and other workloads.”
The companies said they plan to develop modular reference systems that combine Altera programmable hardware with a consistent Intel compute and software foundation. Their goal is to give equipment OEMs greater flexibility as applications, sensors, and workloads evolve, while helping them move more efficiently from prototype to deployment.
“As sensors multiply at the edge and through physical AI systems, our customers need a simpler way to turn real-world data into timely action,” said Dan Rodriguez, corporate vice president and general manager of the Edge Computing Group at Intel. “Together with Altera, we aim to give OEMs a flexible foundation that simplifies integration and helps them move faster from prototype to market deployment while meeting their needs across performance, power and cost.”
Submit your innovation now!Altera, Intel to apply programmable, real-time processing
Intel and Altera said they plan to address multiple markets where real-time processing and programmable computing matter most. The companies intend to make resulting reference solutions accessible to developers through Intel’s Open Edge Platform software development kit (SDK) and an Altera SDK.
- Robotics: The partners said they will combine Intel compute, connectivity, and robotics software with Altera FPGAs to address the increasingly complex sensing, timing, and real-time processing requirements of intelligent machines.
- Healthcare: The companies are jointly developing a reference system targeting the stringent latency and real-time requirements of advanced healthcare equipment.
- Aerospace and defense: Intel and Altera are collaborating to support next-generation mission systems, with a focus on size, weight, and power requirements for converged AI and signal-processing workloads.
Together, Intel and Altera said they will help OEMs move faster from prototype by reducing integration complexity and addressing performance, power, and cost requirements across a range of edge applications.
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