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How to efficiently scale AI compute?

Chips that do better math, faster

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SciSci Research is an accelerated computing chip design company with a novel architecture for radically faster and stronger arithmetic, the kind needed to drastically scale AI compute.

 

SciSci has a novel instruction set architecture (ISA) for what it calls an Exact Processing Unit (EPU), an accelerator chip whose operations are based not on floating-point or fixed-point, but on a procedure from modern number theory called p-adic arithmetic.

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This modern way of doing arithmetic will deliver speeds that are 15-50× faster than floating-point on average, and a 50× energy efficiency gain for the EPU.

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For over 10 years, GPU FLOPS have scaled, not because or Moore's law, but thanks to efficient number representations, namely lower-precision floating-point and INT. Now it's gotten down to 4-bit... The bits are running out; a new paradigm for arithmetic is desperately needed. SciSci has it.

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Better Arithmetic for Scalable AI

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