Akida Execution in Heterogeneous Environments
Heterogeneous Computing in Space
By Dr. Jonathan Tapson, Chief Development Officer
Why Neuromorphic Processing Belongs on the Spacecraft
In space, there’s no repair crew, no spare power, and no fast connection home.
Every watt, every kilogram, and every bit of downlink is rationed. Workloads range from precise control loops to massive sensor streams. And every component must survive years of radiation without maintenance.
No single processor handles all of that well. Space needs a team.
Matching each task to the right processor
Heterogeneous computing assigns each job to the processor best suited to it:
| Processor | Role on the spacecraft |
|---|---|
| Radiation-hardened microcontroller or CPU | Command handling and fault management |
| FPGA or DSP | Reconfigurable signal conditioning |
| Specialized accelerators | Perception and inference |
Dividing the work this way delivers far more capability per watt and per kilogram than a single processor sized for the worst case. It also lets the system degrade gracefully: processors can back each other up, and each one can be powered down when it isn’t needed.
Why intelligence has to live on board
Communication is the strongest reason to put intelligence on the spacecraft itself.
- Bandwidth is scarce. Downlink capacity is limited, and contact windows come and go.
- Latency rules out ground control. Round trips take hundreds of milliseconds through relays in low Earth orbit, and minutes to hours in deep space. Anything time-critical can’t wait for a human on the ground.
- Raw data is enormous. Hyperspectral images, synthetic aperture radar returns, star tracker frames, and RF spectrum captures dwarf the link available to send them.
The answer is to shrink the data at the source. Detect events, extract features, classify content, and discard what doesn’t matter. Terabytes of raw data become a small payload that carries the information that counts.
This on-board reduction makes both bandwidth-limited science and autonomous operation practical. It’s best handled by a dedicated accelerator, not a general-purpose core.
Why neuromorphic fits the job
Neuromorphic processors are a natural fit for that accelerator role, for four reasons.
1. Power follows information. Event-based, spiking architectures compute only when the input changes. Power tracks the information in the signal, not the clock rate. That’s exactly what data reduction needs, and it delivers inference at milliwatt-scale power. In space, where every watt of heat must be radiated away, that matters.
2. Built for space sensor data. Neuromorphic designs handle the sparse, time-based data that space sensors produce, from event cameras to radar and RF, without the heavy preprocessing conventional deep learning requires.
3. Learning after launch. On-device learning lets a spacecraft adapt to its own sensors and environment once it’s in orbit.
4. Tolerant of radiation. A neuromorphic fabric is made of many small, replicated, loosely coupled processing elements, and neural computation naturally tolerates noise.
- A single bit flip in a weight or activation typically reduces accuracy slightly instead of causing failure.
- If radiation damages part of the fabric, the network can be remapped to route around the affected nodes.
- Because the computation is distributed, capability declines gradually rather than failing all at once.
BrainChip in orbit
Akida is already on the path to space:
- In March 2024, Akida technology launched into low Earth orbit inside the ANT61 Brain computer aboard the Space Machines Company’s Optimus-1 spacecraft.
- Frontgrade Gaisler licensed Akida IP to bring neuromorphic AI into its future space processors.
From orbit to the tactical edge
The same strengths carry over directly to distributed defense computing.
Tactical edge nodes, unmanned vehicles, sensor networks, and platforms in contested environments share the same constraints as spacecraft:
- Limited or denied communications
- Tight size, weight, and power budgets
- A need to act on data locally instead of sending it to a central site
Neuromorphic processing answers each one:
- Lower exposure. On-node data reduction shrinks a node’s bandwidth signature and makes it harder to detect.
- Longer endurance. Ultra-low-power inference stretches battery or harvested energy further.
- Resilience under attack. Fabrics that absorb bit flips and route around damage hold up against radiation, electromagnetic interference, jamming, and physical attack.
The bottom line
Space and defense ask for the same thing: intelligence that is autonomous, resilient, and efficient, at the edge, where connectivity can’t be assumed and maintenance isn’t an option.
A heterogeneous architecture with a neuromorphic processor delivers that for both, from a single technology base.
Build intelligence that doesn’t need a connection home.
- Explore the architecture: Learn how Akida powers physical AI on platforms with tight size, weight, and power limits.
- Talk to our team: Contact us about mission requirements for space or defense programs.
- Read the series: “Heterogeneous Computing: Where Akida Adds Value”, also by Dr. Jonathan Tapson.
Stay tuned to the next in the series: our vision of heterogeneous computing and its impact on today’s world, posted every Wednesday.
