Cortex-MO FPGA

Field Programmable Gate Arrays (FPGAs) based on ARM Cortex-M processor cores, also known as Cortex-MO FPGAs, are reconfigurable integrated circuits that combine the flexibility of an FPGA with the processing power and ecosystem of the ARM architecture. Cortex-MO allows developers to integrate custom hardware accelerators while leveraging the efficiency, toolchain and software investments of Cortex-M.

Overview of Cortex-MO FPGAs

The key characteristics of Cortex-MO FPGAs include:

• ARM Cortex-M processor cores – Cortex-MO FPGAs incorporate ARM Cortex-M cores which are optimized for embedded and IoT applications. The cores are 32-bit, RISC architecture with DSP extensions and memory protection unit.
• Programmable logic fabric – In addition to processor cores, Cortex-MO chips contain FPGA fabric that can be programmed to create custom hardware accelerators. Popular options are based on flash or SRAM cells.
• Tight coupling between logic and processor – The programmable fabric is tightly integrated with the processor over high-bandwidth, low-latency interconnects to enable hardware acceleration.
• Development tools – Cortex-MO FPGAs can be programmed using the ARM DesignStartTM FPGA tools or vendor specific SDKs that integrate ARM cores with FPGA design.
• Interface options – A wide variety of peripheral interfaces are offered including Ethernet, USB, CAN, timers, ADCs, high-speed SERDES and support for external memories.
• Small form factors – Cortex-MO FPGAs range from ultra low power miniature packages to modules with multiple high performance cores and abundant programmable logic.

Benefits of Cortex-MO

The major benefits of using Cortex-MO FPGAs include:

• Flexibility – The combination of processor cores and FPGA fabric provides enormous flexibility to optimize systems. Developers can adapt the hardware function and performance.
• Accelerated time-to-market – The ability to create custom hardware accelerators significantly speeds up development compared to software alone.
• Power efficiency – Cortex-MO enables developers to create system architectures that maximize performance within tight power budgets.
• Co-processor approach – Computationally intensive software tasks can be offloaded to custom hardware co-processors.
• Scalability – Cortex-MO offers a scalable range of options from low cost FPGAs to multicore SoC FPGAs for complex applications.
• Ecosystem – Cortex-MO benefits from the mature Cortex-M software ecosystem including RTOS, stacks, models and tools.

Use Cases

Here are some common use cases where Cortex-MO FPGAs excel:

• IoT Endpoint – Cortex-MO enables integration of sensors, radars, security engines, analytics accelerators in a small low power envelope with wireless connectivity.
• Industrial Automation – Real-time control, functional safety, motor drives, advanced HMI, analytics at the edge are facilitated by Cortex-MO.
• 5G Networks – Beamforming, encryption/decryption, network accelerators, smart backhaul radio can be implemented efficiently.
• Aerospace and Defense – Radar processing, sensor fusion, communications and avionics are applications leveraging Cortex-MO capabilities.
• Automotive – ADAS, computer vision, sensor processing for autonomy, functional safety are enabled by Cortex-MO.
• Medical – Low power body worn devices, patient monitors, medical imaging can integrate signal processing and analytics using Cortex-MO.

Design Considerations

Here are some key considerations when designing with Cortex-MO FPGAs:

• Partitioning – Determining which functions to implement in hardware vs software is an important early decision.
• Dataflow – The interface and dataflow between software and hardware accelerators needs to be designed for optimal throughput.
• Tools – Hardware design tools like Vitis, Vivado, LabVIEW work with Cortex-MO and enable high productivity.
• Simulation – Extensive simulation and emulation should be performed to verify hardware and software operation before fabrication.
• Debug – Effective debug of hardware and software requires FPGA-adaptive debuggers and logic analyzers.
• Observability – Well defined control and observation capability should be built-in for production testing.

Development Process

A typical Cortex-MO FPGA design flow involves:

1. Creating requirements, partitioning hardware/software functions
2. Developing hardware IP blocks in HDL
3. Developing software application code
4. Performing high level synthesis to convert HDL to bitstream
5. Integrating hardware IP blocks with ARM processor subsystem
6. Developing complete FPGA image via vendor tools
7. Debugging and optimizing the system via simulation, emulation and prototyping
8. Validating functionality, performance, power
9. Preparing production grade image for volume manufacturing

Vendor and Tools Ecosystem

The major FPGA vendors providing Cortex-MO based offerings include:

• Microchip – Microsemi SmartFusion2, IGLOO2, PolarFire devices
• QuickLogic – EOS S3, Multi-Core devices
• Lattice – LatticeMico and CrossLink FPGAs
• GOWIN – LittleBee and F5 based FPGAs
• SiliconBlue – iCE40 UltraPlus FPGAs

These vendors provide design tools such as:

• Softconsole – Eclipse based IDE for ARM
• Mentor Embedded Multicore Tools – RTOS, stacks, middleware
• ChipVision Pro – Debugger for Cortex-M
• Keil MDK – Compiler toolchain for ARM Cortex-M
• Synopsys ARC optmizing C/C++ compiler
• LabVIEW FPGA – Graphical design tools from National Instruments

Third party embedded software partners also offer thousands of ARM compatible solutions to accelerate Cortex-MO FPGA development.

Future Directions

Emerging trends in Cortex-MO FPGA technology include:

• More integrated heterogeneous SoC FPGAs
• Multi-core Cortex-A class processors on FPGA fabric
• Integrated RF capability with software defined radios
• Embedded machine learning processing blocks
• Tight coupling with specialized I/O like high speed A/D
• Advanced 3D packaging and chiplets
• Higher bandwidth interconnect fabrics (CCIX, CXL, ACE…)
• Abundant hardened DSP blocks, transceivers, memory

With continuing improvements in process nodes, power consumption, and software integration, Cortex-MO FPGAs are becoming a compelling compute platform for the most demanding embedded applications across industries.