The size of the funding round was not disclosed but is being led by High-Tech Gründerfonds.
The company was founded by Manu Nair, Alessandro Aimar and Iulia-Alexandra Lungu and is a spin-off from the UZH-ETH Institute of Neuroinformatics (INI) in Zurich, Switzerland.
The company is developing a dual-core RISC-V ASIC with an integrated Adaptiva accelerator for AI workloads. The chip is called AdaptiveStorm. No indication is given of what manufacturing process node the company might be aiming at. In a watchdog mode the Adaptiva power consumption will be less than 1mW and less than 1-microwatt in some use cases and when running offer up to 10TOPS/W, according to the company’s website.
Adaptiva is designed to support convolutional neural networks such as resNet, VGG and MobileNet and recurrent neural networks with multiple layers. The chip will be designed to support sensor fusion and interpretation with standard audio and video interfaces including MIPI, I2C, SPI and direct interfaces to raw sensor data such as microphones, audio and accelerometers.
Synthara is also going to engineering lengths to make sure its chip is easy to use and program. Synthara is preparing compiler libraries that optimize for energy-efficiency. Developers can use popular AI libraries such as PyTorch or Tensorflow to train neural networks. These networks will be ported to Adaptiva by compilers, which also handles workload planning to ensure maximum energy-efficiency. Direct writing to Adaptiva of machine learning algorithms can be performed by Synthara staff.
Aimar, CTO of the company, said Adaptiva makes use of both sparsity-aware processing and in-memory computation “Our algorithm-aware chips are designed to deliver up to 500 times better performance for the next generation of smart sensor applications that use inertial measurement units, audio and image sensors,” said Nair, CEO of Synthara, in a statement.
It is notable that Synthara is aiming for applications in wearables, IoT, and smart monitoring such as medical apparatus.
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