- QuickLogic recently announced the QuickLogic Open Reconfigurable Computing (QORC) initiative
- This alliance is a consortium advancing common and open hardware for interfaces, processors and systems
QuickLogic Corporation, a developer of ultra-low power multi-core voice-enabled SoCs, embedded FPGA IP, and Endpoint AI solutions announced that it has joined the CHIPS Alliance. This alliance is a consortium advancing common and open hardware for interfaces, processors, and systems.
Brian Faith, president, and CEO at QuickLogic said, “Over the past few years, the electronics industry has seen a big shift toward open source hardware and software, and we’re proud to be one of the companies at the forefront of that movement. We have already been working closely with several CHIPS Alliance members to make FPGA tools and devices more accessible, and we look forward to continuing these efforts as an official member of the organisation.”
QuickLogic Open Reconfigurable Computing
QuickLogic recently announced the QuickLogic Open Reconfigurable Computing (QORC) initiative. It aims to broaden access to open FPGA technology for embedded systems developers. QuickLogic’s initial open source development tools, developed in collaboration with CHIPS Alliance members Google and Antmicro consist of complete support for QuickLogic’s EOS S3 low power voice and sensor processing MCU with an integrated embedded FPGA (eFPGA), and its PolarPro 3E FPGA family.
Dr. Zvonimir Bandić, chairman of the CHIPS Alliance said, “The CHIPS Alliance is continuing to focus on expanding its member base with organizations from a diverse set of industries. QuickLogic, a leader in open source eFPGA IP and FPGA tooling, will help us drive innovation in the FPGA sector and further our mission to remove barriers for open hardware design.”
QuickLogic and Antmicro also launched the open source Arm Cortex M4 MCU + eFPGA SoC dev kit, QuickFeather. Antmicro added support for the QuickFeather dev kit into the Zephyr Real Time Operating System (RTOS) and in its open source Renode simulation framework. It is ideal for low-power machine learning (ML) capable IoT devices.
