The investment was led by provider of All Programmable semiconductor products, Xilinx, and Hong Kong X Technology Fund (HKX), an investment fund supported by Sequoia Capital China and focusing on fast-growing technology companies. In addition, Samsung Ventures Investment Corporation, Samsung Electronics’ investment arm, also joined the funding round, as well as Hong Kong Inno Capital and Brizan Investments.
The investment will accelerate the market deployment of the company’s Quantum programmable technology with a focus on deep learning and compute acceleration.
“High-volume applications and markets are prime targets for our Quantum-accelerated products,” said Sammy Cheung, co-founder, CEO, and president of Efinix. “Combining our Quantum programmable technology and Efinity Integrated Design Environment, we will be launching a number of joint development projects and a new line of silicon product platforms in the coming months thanks to the funding announced today.”
Efinix’s Quantum programmable technology delivers a 4X Power-Performance-Area advantage over traditional programmable technologies. This disruptive advantage enables products accelerated by the Quantum technology to compete in high-growth markets such as custom logic, deep learning and compute acceleration.
“Efinix’s solution can address a wide variety of applications that are typically not served by today’s FPGAs,” said Salil Raje, senior vice president of Software and IP Products Group at Xilinx. “We are excited to be an investor and look forward to working with them.”
“We are thrilled to support Efinix’s growth as it accumulates design wins and grows its customer base,” said Prof. Guanhua Chen, co-founder of HKX. “The truly disruptive Quantum programmable technology addresses needs in many markets especially mobile devices and artificial intelligence.”
“Efinix’s Quantum programmable technology brings opportunity for diverse range of applications,” said representative from Samsung Ventures. “We envision many applications that feature Quantum technology embedded inside ASICs, ASSPs, or FPGAs.”