New Tool Eases Avionics Architecture Trades
What happened
VisualSim has released version 2610, a tool for system-level modeling aimed at complex aerospace platforms. The software enables engineers to run rapid trade studies comparing different compute architectures—like FPGAs versus GPGPUs—by modeling latency, power, and throughput. This is critical for making early-phase design decisions for mixed-criticality avionics systems.
Why it matters
Model-Based Systems Engineering (MBSE) is increasingly used to manage the growing complexity of avionics. Tools that support MBSE, like VisualSim, create digital models that serve as a primary means of information exchange, replacing traditional document-based processes and improving consistency and traceability across the lifecycle. This approach allows for the validation of specifications and exploration of design alternatives before any hardware is built or code is written. The trade-off between FPGAs and GPGPUs is a critical early design decision. GPGPUs excel at high-throughput parallel processing, making them suitable for tasks like deep learning and graphics rendering. FPGAs, however, offer greater power efficiency and lower latency because their hardware can be reconfigured and optimized for specific algorithms, a key advantage in the resource-constrained and real-time environments of aerospace and defense. Consolidating multiple functions onto a single multi-core processor is a major trend in avionics, driven by the need to reduce size, weight, and power (SWaP). This creates mixed-criticality systems, where flight-critical tasks and less critical functions share hardware resources. A primary challenge is ensuring that these applications are partitioned and cannot interfere with each other, a complex task that modeling helps to analyze. Ensuring this separation and predictable behavior is a requirement for certification under standards like DO-178C. DO-178C, the primary standard for commercial airborne software, defines Design Assurance Levels (DALs) based on the consequences of a software failure. Modeling and simulation tools are used to provide evidence of compliance by demonstrating that high-criticality tasks will always meet their deadlines, even in worst-case scenarios.
Key numbers
- VisualSim has released version 2610, a tool for system-level modeling aimed at complex aerospace platforms.
- Ensuring this separation and predictable behavior is a requirement for certification under standards like DO-178C.
- DO-178C, the primary standard for commercial airborne software, defines Design Assurance Levels (DALs) based on the consequences of a software failure.
What happens next
- Modeling and simulation tools are used to provide evidence of compliance by demonstrating that high-criticality tasks will always meet their deadlines, even in worst-case scenarios.
Quick answers
What happened in New Tool Eases Avionics Architecture Trades?
VisualSim has released version 2610, a tool for system-level modeling aimed at complex aerospace platforms. The software enables engineers to run rapid trade studies comparing different compute architectures—like FPGAs versus GPGPUs—by modeling latency, power, and throughput. This is critical for making early-phase design decisions for mixed-criticality avionics systems.
Why does New Tool Eases Avionics Architecture Trades matter?
Model-Based Systems Engineering (MBSE) is increasingly used to manage the growing complexity of avionics. Tools that support MBSE, like VisualSim, create digital models that serve as a primary means of information exchange, replacing traditional document-based processes and improving consistency and traceability across the lifecycle. This approach allows for the validation of specifications and exploration of design alternatives before any hardware is built or code is written. The trade-off between FPGAs and GPGPUs is a critical early design decision. GPGPUs excel at high-throughput parallel processing, making them suitable for tasks like deep learning and graphics rendering. FPGAs, however, offer greater power efficiency and lower latency because their hardware can be reconfigured and optimized for specific algorithms, a key advantage in the resource-constrained and real-time environments of aerospace and defense. Consolidating multiple functions onto a single multi-core processor is a major trend in avionics, driven by the need to reduce size, weight, and power (SWaP). This creates mixed-criticality systems, where flight-critical tasks and less critical functions share hardware resources. A primary challenge is ensuring that these applications are partitioned and cannot interfere with each other, a complex task that modeling helps to analyze. Ensuring this separation and predictable behavior is a requirement for certification under standards like DO-178C. DO-178C, the primary standard for commercial airborne software, defines Design Assurance Levels (DALs) based on the consequences of a software failure. Modeling and simulation tools are used to provide evidence of compliance by demonstrating that high-criticality tasks will always meet their deadlines, even in worst-case scenarios.
