Tensordyne makes a big bet on log math to beat Nvidia
Who needs compute hungry multiplications when you can just add logarithms
AI infrastructure startup Tensordyne has taped out its first commercial accelerator, with fabrication on TSMC’s 3nm process already underway.
Developed in collaboration with Juniper Networks and Broadcom, Tensordyne’s systems promise higher throughput and lower power consumption than GPUs. It claims to achieve this using an unorthodox approach to mathematics that uses logarithms — which you might recall from high school arithmetic — to make matrix multiplication heavy AI workloads less computationally intensive to run.
In conventional computing, addition is cheap, multiplication is expensive. Logarithms flip this on its head. Using logs, multiplication essentially becomes an additional problem. a*b becomes log(a) + log(b).
The trick is converting those values to logs and back again efficiently. There are a couple of ways of dealing with this. One of the easier options would have been to use a look up table (LUT)....
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