Compute
Efficient AI Workloads at Scale
Bring the power of onboard compute to your next mission
Optimized Data
Filtering, prioritizing, and compressing data allows more efficient use of limited bandwidth by sending data products instead of raw data.
Autonomy
On-board processing enables satellites to make intelligent decisions without waiting for hours for commands to be uplinked from the ground.
Speed
Data products can be small enough to allow transmission through satellite-to-satellite networks in seconds instead of waiting hours for a traditional ground station pass.
GPU Based
Edge-Compute
Massive parallel computing capability. High-performance CPU’s.
KESTREL
Achieved Flight Heritage
Standard microSD card and M.2 2280 SSD slot populated with validated, industrial-grade options
Mass Storage
Gigabit ethernet is available for high-speed connectivity, as well as other common interfaces
High-Speed Connectivity
Data is protected with Error Correction Codes (ECC) for RAM and the large capacity non-violate memory allows for the storage of multiple copies of key files
Data Protection
Protection and telemetry circuits for routine monitoring, as well as fault detection and isolation
Routine Monitoring
Subsystems protected with a resettable eFuse circuit to mitigate the effects of radiation
Radiation Tolerance
Kestrel Specifications
Processing Capabilities
AI Performance 1.3 TOPS
GPU 256-Core Pascal
CPU Quad-Core A57
Dual-Core Denver 2
Video Codecs H.264, H.265, MPEG1/2/4
OS Linux-based (built w/Yocto)
Memory/Storage
RAM 8 GB of 128-bit DRAM with ECC
Storage 32 GB eMMC
microSD card default 64 GB
M.2 2280 SSD default 1 TB
EEPROM 512 kb
Connectivity
Ethernet 1000BASE-T
UART 3x RS-422, RS-485 compatible
CAN Two 1 Mbps
USB One USB3.0 SuperSpeed
Two USB2.0 Hi-Speed
PPS RS-422 hardware
GPIO 4 buffered GPIOs
Debug JTAG, Recovery USB, RS-232
Size, Weight, & Power
Size 1/3 U (96 x 89 x 30 mm)
Fits CubeSats and SmallSats
Mass 402 g
Power Idle: <1 W / Max Efficiency: 15 W / Max Performance: 25 W / Input Voltage 9-12 VDC
Protection eFuse input protection and monitoring
Telemetry Internal ADC for voltage/ temperature telemetry
Environmental
Heritage TRL-9 as of March 2024
Radiation up to 30 krad(Si)
Temperature -40 to +60 C Operating / -55 to +85 C Storage
Testing Thermal, Vibration, and EMI/EMC compliant to GSFC-STD-7000
AI-Ready GPU
284 TOPS. High-performance CPU’s. NVIDIA Jetson Orin AGX.
Falcon
Available Now
Filtering, prioritizing, and compressing data allows more efficient use of limited bandwidth by sending data products instead of raw data.
Efficiency
On-board processing enables satellites to make intelligent decisions without waiting hours for commands to be uplinked from the ground. Satellites can respond instantly to changing circumstances.
Autonomy
Data products can be small enough to allow transmission through satellite-to-satellite networks in seconds instead of waiting hours for a traditional ground station pass.
Speed
Falcon Specifications
Processing Capabilities
AI Performance: 248 TOPS
GPU: 2048-core Ampere @ 1.2 GHz, 64 Tensor Cores
CPU: 12-core A78AE @ 2.0 GHz
PVA: Programmable Vision Accelerator
FPGA: Up to 78k LUTs
OS Linux-based (built w/Yocto)
Memory/Storage
RAM: 64 GB of 256-bit DRAM with ECC
Storage: 64 GB eMMC
microSD card: 64 GB
Internal SSD: 1 TB
EEPROM: 512 kb
Connectivity
Ethernet: Two 1000BASE-T
UART: Four RS-422, RS-485 compatible
CAN: Two 1 Mbps
USB: Three USB3.2 Gen2
PPS: RS-422 hardware
GPIO: 4 buffered GPIOs
Debug: JTAG, Recovery USB, UART
Expanded Capabilities: Additional Gigabit Ethernet / SpaceWire / LVDS, Camera Link / PCIe, SpaceFibre, 40G Ethernet
Size, Weight, & Power
Optimized for SmallSats
110 x 100 x 50 mm
3U SpaceVPX planned
Mass: 600 g
Power Idle: <3 W / Max Efficiency: 45 W / Absolute Max: 90 W
Input Voltage: 24-36 VDC
Protection: eFuse input protection and monitoring
Telemetry Internal ADC for voltage/ temperature telemetry
Environmental
Radiation Minimum 5-year LEO mission
Temperature: -40 to +60 C Operating -55 to +85 C Storage
Testing: Thermal, Vibration, and EMI/EMC compliant to GSFC-STD-7000
AI Enabled
Edge-Compute
Chip-down Solution. GPU based.
AI Engines for modern workloads.
WASP
Available for Pre-Order June 2024
Processor designed for tasks like machine learning and advanced signal processing
AI-Engines
Create programs in C quickly with a framework (or library)-based approach for machine learning models
Software Programmability
Higher computing power in a smaller space compared to standard programmable devices, cutting power usage by ~40%
Efficiency