The use of escape analysis to eliminate some allocations results in even faster average allocation times, reduced memory footprint, and fewer cache misses.
The memory footprint for the aspect oriented runtime has been reduced for applications and additionally the memory footprint and file storage size for probes metering snapshots has been reduced.
The advantage to LKMs is that you can minimize the memory footprint for a kernel, loading only those elements that are needed (which can be an important feature in embedded systems).
The larger memory footprint means you should very likely plan on adding additional RAM to your server.
This is achieved by packing more data into smaller memory footprint, thereby giving space for storing more data.
The grey highlight shows the warm-up phase where the native memory footprint increases and then flattens-off as the process reaches steady state.
This leads to applications occupying a larger memory footprint than they strictly require.
Despite all these enhancements the memory footprint remains impressively small.
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