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Shared Data in Asymmetric Multiprocessing (AMP) Configurations
What is Asymmetric MultiProcessing (AMP)?
Heterogeneous multi-core systems are becoming ever more popular in mixed criticality systems for automotive and industrial applications due to their high performance and energy efficiency. Heterogeneous systems have two or more CPUs with different instruction sets and different operating systems running on the device.
An AMP system has multiple CPUs, each of which are a different architecture. Each CPU has its own address space (though some of the memory may be shared with other cores). The system is typically equipped with a communication facility between the CPUs, normally a hardware messaging unit and DDR shared memory. In addition, more than one operating system runs independently on one or more processors with different architectures. For example, NXP i.MX8x with embedded Linux on the ARM Cortex-A and FreeRTOS or Vector’s MicroSAR on the ARM Cortex-M4.
What benefits do AMP systems offer?
By dividing tasks between different processors, heterogeneous system designs cover multiple requirements such as energy efficiency, performance and safety, and make them fit for real-time critical applications.
A growing need
The need for database management in mixed criticality and other systems that utilize AMP hardware is quite wide-spread: power grid controllers must share their sensor readings and other real-time data collected by a FreeRTOS-based low-latency application running atop of the Cortex-M clusters with the fast yet complex processing on the Linux side running atop of the Cortex-A clusters; an AMP-based drone system utilizes different clusters for navigation parameters acquisition and for real-time processing running different real-time operating systems on each cluster.
To learn more about this topic we invite you to review the white paper, “Shared Data in Asymmetric Multiprocessing (AMP) Configurations”.
Using platform independent eXtremeDB for Asymmetric MultiProcessing (AMP)
One CPU architecture for real-time and another for analytics.
- Used in systems such as mixed criticality sensor data fusion
- Single database
– Populated by the real-time side
– Queried for AI/ML by the analytics side.
More suitable than Symmetric MultiProcessing (SMP).
eXtremeDB for HPC
– Columnar and row-oriented storage to optimize time series data
– A library of more than 150 built-in functions
– Sharding for elastic scalability
– Distributed query processing
eXtremeDB Embedded
– Interoperability
– ACID-compliant transactions
– Type-safe API
– Transaction logging
– Tiny footprint
– High availability options
– Bidirectional Replication
– Mitigates loss of data due to connectivity issues
– Multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud)
– Compression to maximize limited bandwidth networks
eXtremeDB/rt
– Deterministic ACID-compliant transactions
– Adaptable real-time transaction managers
– No restrictions on execution patterns
– A highly configurable database kernel
– Support for all major commercial RTOS
– Ideal for ADAS or SCADA