What does this equation mean?

is the condition that actually governs whether an allocation succeeds, and it can fail even when $S_{\mathrm{request}}$ $\le$ $\sum_i$ $\mathrm{free}_i$ holds comfortably — the requested size fits inside total free memory but not inside any one free block. This is precisely the problem the smartphone inference system PowerInfer-2 was built to manage: it introduces a segmented neuron cache with a least-recently-used eviction policy specifically to keep the working set of “hot” and “cold” neuron clusters from fragmenting a mobile device’s limited DRAM, allowing models “whose sizes exceed the device’s memory capacity” to run without the allocator failures that naive loading produces, while cutting memory usage by roughly 40% relative to prior mobile inference engines at comparable speed [ 3 ] . The fix is not more free memory; it is memory management that treats fragmentation as the binding constraint rather than total capacity.