Currently, TMO enables transparent memory offloading across millions of servers in our datacenters, resulting in memory savings of 20%–32%. Of this, 7%–19% is from the application containers, while ...

A research team from Sakana AI, Japan, has introduced Neural Attention Memory Models (NAMMs). NAMMs are a new class of memory management models that dynamically optimize the KV cache in transformers.

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The real-time specification for Java extends the Java platform to support real-time processing and introduces a region-based memory model, called scoped memory, which side-steps the Java garbage ...