The biggest challenge posed by AI training is in moving the massive datasets between the memory and processor.
Google researchers have revealed that memory and interconnect are the primary bottlenecks for LLM inference, not compute power, as memory bandwidth lags 4.7x behind.
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Energy and memory: A new neural network paradigm
Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations—it's a triumph of your associative memory, in which one piece of information (the first few notes ...
BEIJING, Dec. 26, 2024 /PRNewswire/ -- WiMi Hologram Cloud Inc. (WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the ...
AMD submitted a patent to the World Intellectual Property Organization (WIPO) for a groundbreaking new memory architecture that can significantly enhance the performance of the DDR5 standard. The ...
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