RISC-V AI Chips Are Joining GPU Race for AI Processing: CDO Trends
In CDO Trends, see Paul Mah’s article on how “RISC-V AI Chips Are Joining GPU Race for AI Processing.”
He writes:
“The future has RISC-V in it
One such startup, Esperanto Technologies, utilized a modified RISC-V design with 1,092 cores into a system-on-a-chip (SoC) half the size of the popular A100 GPU from Nvidia.
As reported on IEEE Spectrum, the team created their own vector instructions to complement RISC-V’s efficient 47 instructions (A typical Intel desktop processor has close to a thousand instructions) to support machine learning math such as matrix multiplication.
The ET-SoC-1 from Esperanto is envisioned to accelerate AI in power-constrained data centers through expansion boards that fit into a standard peripheral component interconnect express (PCIe) slot. According to the report, each board can deliver 800 trillion operations per second.
What sets Esperanto’s solution apart is how each board uses multiple low-power SoC chips instead of a giant SoC. According to the AI chip maker, each ET-SoC-1 chip consumes 20 watts when performing a recommender-system benchmark neural network, or less than one-tenth of what the A100 GPU draws.
This allowed the team to place six chips for over 6,000 cores on a single AI accelerator card and still stay at around 120 watts.
And according to a report on All About Circuits last year, Esperanto claims an ET-SoC-1 outperforms the Nvidia A100 in both relative performance and energy efficiency running the MLPerf Deep Learning Recommendation Model benchmark.”
