@DeusXVI@menhguin@bubbleboi CMXT's capacity is fully booked for the next ~2 years just with local chinese costumers. Also, see below (although this may just be US building leverage in preparatio to the next fall's Xi-Trump meeting)
Will China still allow InP exports to the U.S.? Iโm very bearish on AXTI. Now Iโm starting to wonder whether U.S. companies will even be able to use CXMT DRAM.
Not financial advice. Do your own research.
If you push this argument to its logical extreme, you arrive at the following conclusion:
GPUs are getting three times faster every two years, while storage is failing to keep pace.
โThe criterion for selecting storage media has expanded from $/TB to $/GPU-hour.โ
Traditional high-capacity storage has primarily been evaluated in terms of $/TBโin other words, how cheaply it can store large volumes of data.
But in AI training infrastructure, where GPU availability, power, and latency are critical constraints, that metric alone is no longer sufficient. If data arrives too slowly from storage and leaves GPUs idle, the cost of wasted GPU time may exceed any savings achieved on storage.
In simplified terms:
Incremental cost of flash < GPU idle time eliminated by flash ร cost per GPU-hour
For workloads where this condition holds, using flash is economically rational despite its higher cost per terabyte. GPU-adjacent storage tiers should therefore be evaluated not only by $/TB, but also by the total system cost per effective GPU-hour.
In other words, up to a certain ceiling, it could make economic sense to spend several times more on flash than we do today.
@bubbleboi Translation:
"Iโm trying to pull off a genius, outside-the-box breakthrough in flash memory that humans in the field wouldnโt normally consider"
- DogBoiGO
SK HYNIX CEO: NEXT YEAR IS EXPECTED TO BE THE WORST YEAR IN THE INDUSTRYโS HISTORY FROM A SUPPLY PERSPECTIVE โ RTRS
SK HYNIX CEO: DESPITE AGGRESSIVE CAPACITY EXPANSION, MEMORY DEMAND WILL CONTINUE TO EXCEED THE COMPANYโS PRODUCTION CAPACITY OVER THE NEXT DECADE โ RTRS