KOVE
He adds : “ You can go with CXL , and go down the road of replacing all your hardware . Or you can add Kove , and get better performance and better energy savings now . Kove will support CXL hardware if / when / how / as that becomes available .
“ Memory and CPU costs are typically between 65 % and 85 % of IT investment , yet most servers only achieve between 20 % and 40 % utilisation .” AI developers frequently target only 25-30 % utilisation to avoid swapping to NVMe . This all goes away with Kove , where developers can target all local memory and create memory size needed on-demand through provisionable rules – of any size , not limited to localmemory hardware constraints .
Overton points out that Kove : SDM™ provides CPUs with ‘ local ’ memory performance , even when that memory lives in a data centre . This , he explains , delivers high CPU utilisation rates – “ even CPU saturation ” – when using remote memory .
Such unlimited dynamic-memory sizing means any-size computation can run completely in memory – and that , says Overton , is “ seismic ”.
He adds : “ Because Kove : SDM™ virtualised memory allows individual servers to draw from a common memory pool , they receive exactly the amount of memory needed , even amounts far larger than can be contained on a physical server .
“ When a job is completed , memory returns to the pool and becomes available
88 June 2024