CALL FOR PARTICIPATION AND PAPERS

Components, Radiation, and Packaging

Focus on emerging component, module, and packaging technologies that will advance space computing capabilities. Radiation test methods for and results on complex components are included.

• COTS components, including automotive grade, and module reliability
• New packaging (e.g., 2.5D/3D) and PCB technologies, including emphasis on substrate and interconnect technologies
• Emerging space memory (e.g. Crosspoint DDR4/5, STT-MRAM, VNAND Flash, etc.)
• Wide bandgap (e.g., GaN and SiC) computing devices and modules
• Advances in computing devices (e.g. GPU, DSP, FPGA/SoC, processors)
• Part-specific challenges and solutions
• Component and module radiation effects testing and analysis
• Component security and trust, challenges and solutions

Computing Architectures

Wide range of space computing topics including reconfigurable computing systems, high performance space computing, fault tolerant design, system on a chip and embedded memories, GPU-based computing, and effective use of many-core processor platforms.

• Reconfigurable systems
• Space processors, multi-core, SoC, GPU-based
• Hybrid data processing systems
• Fault-tolerant architectures
• System modeling and design tools
• Power management, SWaP vs computing capability
• Flight application experience
• Small/Nano Sat computing

Flight Data Processing

Advances in flight data processing techniques including high-speed data processing, real-time data processing, and fault tolerance. Complex data processing applications that require software and FPGA co-processing solutions.

• Fault tolerant space computing techniques
• Autonomous operations
• Embedded software and real-time systems
• FPGA design innovative solutions
• Software/FPGA co-processing applications
• “Killer Apps”, memory/data intensive applications

Avionics Systems

Focus on current and future avionics systems and architectures. New concepts for implementing reliable space networks and interoperability.

• Future spacecraft avionics concepts (commercial and government)
• Interconnect and networking, e.g. SerDes, wireless, SpaceVPX, etc.
• Networking of multiple spacecraft
• Distributed computing, multi-node systems
• Interoperability
• Security in space systems
• Cross-agency standards
• Flight application experience
• System-level Fault Tolerance

Machine Learning/Neural Computing

Machine learning/Neural computing techniques are increasingly providing state-of-the-art solutions in signal processing and are increasingly being explored for remote sensing, decision making, and anomaly detection tasks. Space computing faces many unique challenges such as operating in a radiation environment, employing a variety of sensors, and facing low size, weight, and power (SWaP) costs. This track encourages contributions on machine learning and neural-inspired approaches for enabling computing in space including deep learning and machine learning algorithms, neuromorphic hardware and other edge devices, neural-inspired sensors, and analysis ready datasets.

• Algorithmic advances in deep learning & machine learning for space processing
• Neuromorphic hardware
• Edge devices
• Neural-inspired sensors
• Analysis ready datasets
• Benchmarks
• Robustness measures for emerging machine learning & deep learning approaches
• Machine learning for cyber security in space applications
• Advanced spacecraft planning and scheduling