NVIDIA is investigating new non-volatile memory options to increase the SSD speeds
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- NVIDIA pushes SSD -Makers to 100 million IOps storage objective
- But CEO of Silicon Motion says that industry is missing memory technology to meet AI requirements
- New memory may be necessary to unlock ultrasnelle AI storage
As GPUs grow faster and memory tire width scales in the terabytes per second, storage has become the next large bottleneck in AI Computing.
Nvidia Want to push storage to meet the requirements of AI models by getting an ambitious target for random read of small blocks.
“At the moment they strive for 100 million IOPs – which is huge,” said Wallace C. Kuo, CEO of Silicon Motion, said Tom’s hardware.
Today’s fastest PCIE 5 SSDs are top at around 14.5 GB/s and 2 to 3 million IOPs in workloads with regard to 4k and 512-byte reads.
While larger blocks prefer bandwidth, AI inference usually attracts small, scattered pieces of data. That makes 512B random reads more relevant and much harder to accelerate.
Kioxia is already preparing an “AI SSD” based on XL-Flash, that is it is expected to be more than 10 million IOPs. Next year, in addition to Nvidia’s upcoming Vera Rubin platform, it could launch. But the scaling further can require more than just faster controllers or nand adjustments.
“I believe they are looking for a media change,” said Kuo. “Optane was supposed to be the ideal solution, but it has now disappeared. Kioxia is trying to bring XL-Nand and improve its performance. Sandisk tries to introduce a high bandwidth flash, but to be honest I don’t really believe in it.”
Power, costs and latency All Pose challenges. “The industry really needs something fundamental news,” Kuo added. “Otherwise it will be very difficult to reach 100 million IOPs and still be cost -effective.”
Micron, Sandisk and others race to invent new forms of non-fledged memory.
Whether one of them will arrive on time for the next wave of hardware from Nvidia is the big unknown.
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