Startup Lemurian raises US$9 million to develop AI processor
Lemurian Labs Inc. (Menlo Park, Calif.) has raised US$9 million seed funding to develop a computing platform tailored for AI applications.
The round was led by Oval Park Capital, with participation from Good Growth Capital, Raptor Group and Alumni Ventures among others.
The company was co-founded in 2018 by Jay Dawani (CEO) and Vassil Dimtrov (chief scientist) and includes a core team with experience gained at Google, Microsoft, Nvidia, AMD and Intel.
To address the challenges of AI the company has developed a novel datatype – the parallel adaptive logarithm (PAL). Conventionally digital AI processing is delivered using integer and floating-point datatypes. The use of a logarithmic datatype can deliver a factor of 20x improvement in throughput compared with GPU-based AI and at 10 percent of the cost, Lemurian claims.
“AI models have grown in complexity and adoption at a rate so rapid that it is now stressing our current hardware infrastructure to the point of fracture,” said Dawani, in a statment. “Models will continue to grow so we need fundamental changes in hardware in order to keep pace. We reimagined accelerated computing around the needs of AI models and its developers to bring down the cost and power consumption by 10X.”
In addition, the company has taken a software-first approach to hardware design. The company created a dynamic compiler that supports the PAL datatype. The compiler dynamically places tasks to maximize hardware utilization. And it was around this compiler that the company is designing its hardware architecture.
The architecture is a relatively fine-grained array of processing cores with local memory to create a near-memory, distributed dataflow architecture. The company claims the tiered memory architecture optimizes data flow for throughput and efficiency without sacrificing generality.
The company does not appear to have discussed its timeline or business model in detail.
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