Arm® Cortex®-M4F + eFPGA SoC tiny form factor dev kit fits in USB Type A port found on almost every computer, enabling portability and development anywhere
Qomu development kit is a tiny form factor Arm® Cortex®-M4F MCU + eFPGA combination that fits into a USB Type A port. It features QuickLogic’s EOS S3 multicore MCU + eFPGA SoC. Optimized for the QuickLogic Open Reconfigurable Computing (QORC) Initiative, the kit is supported by open source development tools, including Zephyr, FreeRTOS, SymbiFlow and Renode. Qomu also supports nMigen for a Python-to-FPGA design flow.
Features and Specifications
EOS S3 MCU + eFPGA SoC
- Arm® Cortex®-M4F Microcontroller
- up to 80 MHz operating frequency
- up to 512 KB SRAM
- Embedded FPGA (eFPGA)
- 2400 effective logic cells
- 64 Kb RAM and up to eight RAM/FIFO controllers.
- Two dedicated multipliers can be used to offload math-intensive functions
- 16-channel DMA for efficient data movement within the SoC
- Configurable SPI (Master and Slave) and I2C master interfaces
- Ultra-low Power consumption in uWatts.
- USB Type A Compatible Form Factor
- Plugs directly into your USB Type A port
- Interfaces
- SWD programming connector for use with USB-TTL converter
- USB data signals are tied to eFPGA programmable logic
- UART available via I/O headers
- I²C, I²S, SPI
- Storage: 16 Mbit SPI NOR flash - GigaDevice GD25Q16CEIGR
- User Interfaces
- RGB LED
- User pushbutton
- Reset pushbutton
- Power
- USB micro Type-C connector (regulated to 3.3 V)
- Software
- Machine Learning
- Real-time Operating Systems
- FPGA Tools
Benefits
- Enables development on the EOS S3 SoC Arm Cortex-M4F and eFPGA core ANYWHERE
- Start learning how to use embedded FPGA cores by first targeting your code on the Arm Cortex-M4F and then offloading processor/memory intensive functions from software to the eFPGA
- No hardware set up required, plugs into a USB Type A port (No need to fiddle with cables or adapters and any soldering)
- 100% Open Source hardware and software tools for the MCU and embedded FPGA core
Applications
- Edge IoT applications
- IoT designs using MCUs and FPGAs
- IoT applications requiring ultra-low power consumption and AI or machine learning ML applications such as with SensiML’s AI Software Platform and Google’s TensorFlow Lite
Qomu Development Kit Diagram
