SDS Central Compute
Central compute is the supervisory processing layer used across all Software-Defined Systems (SDS). It provides the execution environment for real-time control, coordination, analytics, and AI-assisted decision-making in vehicles, robots, depots, charging sites, energy systems, and industrial operations. In every SDx system—SDV, SDR, SDI, SDE, and SDIO—central compute replaces scattered controllers with a unified, programmable platform.
Roles of Central Compute
Across domains, central compute provides orchestration, policy enforcement, data processing, and lifecycle management.
| Role | Description | Domain Examples |
|---|---|---|
| Cross-domain orchestration | Coordinate subsystems and enforce global policies | Vehicle energy + thermal, depot queues, DER dispatch, robot workflows |
| Compute for perception and analytics | Execute sensor processing, analytics, or autonomy pipelines | Vision, radar, lidar fusion, power-quality analytics, factory inspection |
| AI-assisted decision-making | Run inference models locally for reliability and latency | Routing, charge planning, anomaly detection, robot navigation |
| OTA and lifecycle management | Manage software images, configurations, rollback, and scheduling | Vehicles, robots, depots, DERs, and industrial cells |
| Telemetry and observability | Aggregate, compress, and forward data | Health, performance, usage, fault codes, operator actions |
| Safety and fault containment | Monitor system state and enforce fallback behavior | Fail-operational automation, safe robot states, energy protection limits |
Hardware Building Blocks
Central compute systems use combinations of CPU cores, accelerators, safety processors, memory, durable storage, and network interfaces. These appear in every SDx domain with domain-specific packaging and isolation.
| Component | Function | Cross-Domain Considerations |
|---|---|---|
| CPU cores | General-purpose processing | Real-time extensions, determinism, multi-domain workloads |
| GPU / NPU / DSP accelerators | Parallel compute for perception or analytics | Thermal limits, model size, performance headroom |
| Safety cores | Independent safety logic and monitoring | ASIL/PL compliance, redundancy, lockstep behavior |
| Memory subsystem | Shared memory for workloads and models | ECC, bandwidth guarantees, QoS per domain |
| Persistent storage | Images, logs, model weights, configs | A/B slots, endurance, atomic updates |
| Networking interfaces | Connect to sensors, actuators, controllers | Ethernet, TSN, CAN, LIN, wireless backhaul |
| Power and thermal | Support predictable compute under load | Cooling integration, redundancy, derating behavior |
Deployment Patterns
Across SDV, SDR, SDI, SDE, and SDIO, central compute nodes follow similar deployment topologies.
| Pattern | Description | Domains |
|---|---|---|
| Single compute node | One supervisory controller coordinates multiple subsystems | Robots, smaller vehicles, compact industrial cells |
| Redundant compute nodes | Two or more nodes with overlapping capabilities | Autonomous vehicles, energy systems, high-availability depots |
| Compute + zonal controllers | Central node plus real-time zonal or cell controllers | Vehicles, robots, factory lines, microgrids |
| Dedicated autonomy / analytics compute | High-performance node for perception or optimization | Robotaxis, advanced robotics, DER forecasting hubs |
Interfaces to Other SDS Components
Central compute interacts with storage, networking, sensors, actuators, domain controllers, cloud systems, and operator tools.
| Interface | Counterpart | Information Exchanged |
|---|---|---|
| Domain / zonal controllers | Local control units | Setpoints, configuration, fault codes, status |
| Sensor networks | Vehicles, robots, depots, industrial sites | Raw or fused data streams, calibration, time sync |
| Persistent storage | Local flash/SSD | Software images, logs, buffers, model data |
| Operations cloud | Fleet, depot, grid, or factory systems | OTA packages, config updates, telemetry uploads |
| Operator tools | Dashboards and engineering interfaces | Status, metrics, alerts, debug signals |
Design Considerations
Central compute designs must balance safety, performance, observability, security, and lifecycle costs.
| Dimension | Key Question | Implications |
|---|---|---|
| Safety | What must remain operational under faults? | Safety islands, fallback states, redundant paths |
| Latency | What is real-time vs best-effort? | QoS, scheduling, memory isolation |
| Scalability | How will workloads grow over time? | Accelerator sizing, modular compute |
| OTA | How often will software/models change? | Partitioning, versioning, rollback |
| Security | What are attack surfaces? | Secure boot, isolation, signed updates |
| Observability | How will debugging occur in the field? | Structured logs, traces, telemetry schemas |