For modern workloads, performance is increasingly constrained not by CPU speeds, but by DRAM capacity. On top of that, DRAM is one of the most expensive computing resources. For such a costly resource, the expectation would be that it would be well-utilized. In many environments, however, that is not the case. Studies from major cloud providers have shown that utilization often drops to 50% or lower—over half of the memory can be considered cold. This means that organizations are deploying much larger DRAM footprints than they truly need—resulting in potentially millions of dollars in wasted spend.

MEXT is tackling the memory utilization problem with an unprecedented approach: transparent, AI-powered memory tiering. MEXT begins by offloading cold memory pages from DRAM to a 20x lower-cost tier, flash. The MEXT Predictive Memory™ Engine leverages the power of AI to continually predict which memory pages in flash are likely to be requested by the application, and transparently moves them back to DRAM—before the application even requests them. From the application's perspective, all relevant memory pages are always findable in DRAM, maintaining performance.

Through this AI-powered prediction, MEXT can keep application performance intact within a much smaller DRAM footprint—yielding substantially lower costs. Alternatively, MEXT can instantly enable 2-4X more memory capacity on existing systems (through flash-as-memory), yielding superior performance for memory-bound workloads.