Qomu Development Kit
Supported by 100% Open Source Hardware Development Kit and Software Tools
Buy NowArm® 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.
Qomu Dev Board Features
QuickLogic EOS S3 SoC
Arm® Cortex®-M4F MCU with eFPGA, combining high performance and flexibility.
Powerful Processing
80 MHz Arm® Cortex®-M4F with 512 KB memory and two dedicated multipliers for math-intensive tasks.
Customizable eFPGA
2,400 logic cells, 64 Kbits RAM, and 16-channel DMA for optimized data handling and design flexibility.
Efficient Connectivity
Configurable SPI and I²C interfaces for seamless integration with peripherals.
Ultra Low Power Consumption
Operates at µW levels, ideal for energy-sensitive applications.
Integrated Storage
16 Mbit SPI NOR flash for additional memory needs.
Complete Development Ecosystem
Supports TensorFlow Lite, SensiML, Zephyr RTOS, FreeRTOS, SymbiFlow, and Renode for comprehensive software and FPGA development.
Software Features
Machine Learning
Supports TensorFlow Lite and SensiML for AI applications.
Real-Time Operating Systems
Compatible with Zephyr RTOS and FreeRTOS for real-time control.
FPGA Tools
Use SymbiFlow and Renode for FPGA development.
Benefits
Develop Anywhere
Leverage the EOS S3 SoC with Arm Cortex-M4F and eFPGA core anywhere you go.
Learn and Optimize
Begin with Cortex-M4F, then offload demanding tasks to the eFPGA.
Plug-and-Play Simplicity
No setup needed—just plug into any USB Type-A port.
100% Open Source
Access fully open-source hardware and software tools for complete control.
Applications
Edge IoT Applications
IoT Designs Using MCUs and FPGAs
Ultra-Low Power IoT Applications
AI and Machine Learning Applications
