Computer memory capacity has expanded greatly, allowing machines to access data and perform tasks very quickly, but accessing the computer's central processing unit, or CPU, for each task slows the ...
So far, so futile. Both these approaches are doomed by their respective medium being orders of magnitude slower to access and ...
The dynamic interplay between processor speed and memory access times has rendered cache performance a critical determinant of computing efficiency. As modern systems increasingly rely on hierarchical ...
In the early days of computing, everything ran quite a bit slower than what we see today. This was not only because the computers' central processing units – CPUs – were slow, but also because ...
Morning Overview on MSN
Google’s TurboQuant claims big AI memory cuts without hurting model quality
Google researchers have proposed TurboQuant, a two-stage quantization method that, according to a recent arXiv preprint, can ...
Tom's Hardware on MSN
Google's TurboQuant reduces AI LLM cache memory capacity requirements by at least six times
The algorithm achieves up to an eight-times performance boost over unquantized keys on Nvidia H100 GPUs.
The cache is soldered to the board, so yer out of luck there. In theory, the Aladdin 5 could cache up to 512, but the early chipsets had a flaw in the cache tag RAM that caused the 128 MB limitation.
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