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| author | blasty <blasty@local> | 2026-08-07 15:07:09 +0200 |
|---|---|---|
| committer | blasty <blasty@local> | 2026-08-07 15:07:09 +0200 |
| commit | be42c4ffa039440caf674c12f4343f08d4c48b9d (patch) | |
| tree | 6bcc4544ce71e03636f19e0af91f3c4d105c01d1 /idatui/worker.py | |
| parent | SPEED.md: record the post-fix backend numbers and the 2ms round-trip floor (diff) | |
| download | ida-tui-be42c4ffa039440caf674c12f4343f08d4c48b9d.tar.gz ida-tui-be42c4ffa039440caf674c12f4343f08d4c48b9d.tar.xz ida-tui-be42c4ffa039440caf674c12f4343f08d4c48b9d.zip | |
SPEED.md: where the last 2ms goes, and why batching is not worth building
Measured so nobody re-derives it: HTTP is 0.165ms of the 2.0ms floor and
execute_sync marshalling onto IDA's main thread is the other 1.86ms, inside
IDA's own serve() loop. Call volume is already minimal (8 calls to scroll 2000
rows, 4 for a 1060-block graph), so a batch endpoint would save single-digit ms
on flows costing hundreds. The largest single operation in the app -- decompiling
a 17KB function -- is 10806ms here and 10723ms on the worker: pure Hex-Rays,
0.8% apart, no transport in it.
Diffstat (limited to 'idatui/worker.py')
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