Vsora raises €13m for AI chiplet accelerator
Vsora in Paris has raised €13m for the development and deployment of its hardware accelerator for AI inference, advanced signal processing and complex algorithms.
Vsora was one of 47 companies from a total of 648 candidates receiving grants from the European Innovation Council (EIC) and the funding will be used for a project for a unified architecture called ‘Superchip’..
Vsora has developed a chiplet-based accelerator called Jotunn that can handle both generative AI inference and compute-intensive algorithms. This provides up to 3.2 petaflops at FP8 8bit resolution with power up to 180W. This has compute efficiency of more than 50% for GPT-3.5 or the full GPT-4, compared to a typical efficiency range of about 2-4% of the current industry approaches.
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“We are proud that the EIC endorsed our vision and ambition to enable a new computing hardware paradigm,” said Khaled Maalej, founder and CEO of Vsora.
Vsora has also developed Tyr family of PetaFLOPS computational companion chips to accelerate Level 3 (L3) through Level 5 (L5) autonomous driving and advanced driver-assistance systems (ADAS). This uses its AD1028 architecture that can provide from 400TOPS at 10W to 1200TOPS and alongside CNN and RNN neural networks it also handles newer types of algorithms, such as Transformers, BEVformer and Federated Learning for Software Defined Vehicle (SDV) development environments.
The company raised $4.2m back in January from Otium Capital and angel investors for the Tyr development. “We’re exceedingly proud of the Tyr family and are pleased that Otium Capital and our other investors believe in what we’re doing,” said Maalej . “Tyr has the ability to provide up to two PetaFlops processing power with superior implementation efficiency reaching more than 80%, combined with a power consumption less than 10W, something no other company can claim.”
Vsora was founded in 2015 by a team of DSP and AI scientists and engineers and has offices in Meudon-La-Forêt, France, Taiwan, Korea and Japan.
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