HBF for High-Throughput LLM Serving (UC Berkeley, FuriosaAI)

T2Covered by 1 source · first reported by Semiconductor Engineering / SemiWiki / EE Times / EE Journal / Electronics Weekly at 02 Oct, 20:15 UTC

Researchers at the UC Berkeley and FuriosaAI published a technical paper titled “Characterizing High Bandwidth Flash for LLM Serving.” Abstract: “Large language model (LLM) serving requires substantial memory to store model weights and KV caches. As models grow larger and contexts become longer…

aihardwarescience

Sources

• T2HBF for High-Throughput LLM Serving (UC Berkeley, FuriosaAI)Semiconductor Engineering / SemiWiki / EE Times / EE Journal / Electronics Weekly02 Oct, 20:15