Adapteva, a Lexington, Massachusetts-based manufacturer of multicore processor chips, designed for parallel computing, has closed a $3.6M Series-B funding round from Carmel Ventures and Ericsson.
The funding will be used for delivering transformative technology for semiconductor chips and computing boards that enable the next generation of parallel computing.
Parallel processing and high performance computing (HPC) are of huge interest to Adapteva. Both these markets are transforming dramatically.
Technology like Adapteva’s can significantly advance the use of parallel programming and processing in communications equipment, Adapteva said.
Says Ori Bendori, partner at Carmel Ventures, “Adapteva’s approach is very different than the traditional silicon vendor model and we believe this could lead an industry transformation – just the type of innovation we like to invest in.”
Ericsson took interest in this venture as it has realized there is potential for major returns in energy efficiency and performance gained from parallel processing. This will hugely support the growth of telecom industry, said Sebastian Tolstoy, Ericsson VP Business Development, PA Radio, BNET.
Founded in 2008, Adapteva has developed a unique, scalable and energy-efficient architecture and IP for parallel processing, delivering two parallel processing accelerator chips in 2011. To bring Adapteva’s solution to a wider audience Adapteva launched the Parallella Project in 2012. It also raised $898,921 Kickstarter crowd-funding campaign.
“Adapteva’s open source, community-driven approach to parallel programming and processing is a breakthrough for the computing industry,” said Andreas Olofsson, CEO and founder of Adapteva.
“Even prior to shipping all our initial orders, we have more than 5,000 active followers in our community. With this investment and the upcoming fulfillment of our Kickstarter shipments, we expect the momentum to continue to snowball,” Olofsson added.
The flexibility of Adapteva’s parallel co-processor architecture lends itself for integration into complex appliances and battery powered devices with more computational needs, such as telecommunications and embedded vision.
