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interleaved): matmul 38.18 to 36.10 ms with 4.5% fewer instructions (segments in its nested rounds), knapsack's per-batch cost 0.68 to 0.63 us but knapsack 10.35 to 10.51 ms with 1% fewer instructions (its per-element loops placed elsewhere), sum0 1,743 instructions a batch: short of 025's stage-2 bars (9.2 ms, 0.45 us, 33 ms): 025 priced a segment's instruction at 50 cycles, the counts show about 25 instructions, and a batch's cost sits in finds, bounds, read records, lane setup, masks and the deferred store's check; a list's cells once a batch measured at 3% and not made; next, per element: stage 3's four-byte MUL (matmul 21 ms)
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interleaved): knapsack's per-batch cost 0.90 to 0.68 us and knapsack 11.48 to 10.34 ms, short of 025's bars (0.60 us, 10.3 ms): 025 counted the pass's per-instruction head as lookups; sum0 2,330 to 1,822 instructions a batch (bar 1,550); matmul 40.0 to 38.2 ms with the same instructions and BFS 24.04 to 24.31 with 0.2% fewer (placement); sum0's 8.69 to 6.13 ms mostly the compiler now vectorizing the reductions' first loop; the executor alone the same instructions; what is left a batch is the pass's Val handling (stage 2); 041 runs.sh pairs, pairs and counts data
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over one round's batches, 3x too high; about 2,300 instructions (0.33 us) in a small block, 0.90 us in knapsack's (38% of its time, not 20%)
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bar on roots (0.71x the compiled code's cycles a step), not on knapsack (4x) or BFS (2.4x), as NEON has no gather and a tile's lanes go out and in one by one; tight passes of the batch executor's own shape in the same run at 1.2x (BFS) and 0.4x (knapsack, clang): the shape is right and the 3x is implementation, so 132's A (a batch program made once at load, loops tight by type, width and stride, fewer passes) is the way; tiles kept aside for chains of arithmetic; 132, 024 and CHECKPOINT say so
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passes through memory; a batch's fixed cost about 6,500 instructions, 1 us, measured by 1024 against 256 lanes: fewer lanes are slower, so 024's L1 sizing was the wrong lever; a candidate's tail about 250), what the database literature measured of the same shape (X100, Kersten 2018's cycles and instructions a tuple, Sompolski 2011, Gubner 2017's in-register aggregation, Photon, Ertl and Gregg), the ways judged by the philosophy (a batch program made once at load; register tiles with threaded dispatch as the one general way past the floor; a table of fused operations and AOT C out), and the deciding experiment with its bar first (three bodies in tiles of 4, 8, 16: within 1.3x the compiled code's cycles an element, or it is not the answer); 041 lanes data
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general way over a table of fused operations: values computed by the same code taken from the first, if !c one branch, selections (an arm's few lanes alone), keys as bits asked in one loop, L.first + i affine, a slice's bounds at once: the suite's BFS 211 to 112 instructions an edge, 41 to 24 ms (the compiled code 38.5, 7.7); where the rest goes and the floor of the general way (about twice the compiled code); knapsack and matmul 10% slower, cause not fully told; 024 and CHECKPOINT say so
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batch's rounds together or spread into lanes, filters asked as a batch opens and again at its end): the suite's BFS batched, 93 to 41 ms (the compiled code 7.7, C 10); where it goes (211 instructions an edge against 38.5: a filter's code over every lane the most); the floor of operations each a pass over the lanes (about 50 an edge, 1.3x the compiled code) and what would pass it (fused operations from a table, 024's); the choice left: a table of them, or the compiled code kept for such work; 024 and CHECKPOINT say so
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ms, a recurrence's steps as numbered values and one loop of actions 44.4 to 21.8, reductions' ends in any order where it cannot tell 9.80 to 4.00): knapsack 10.8, matmul 36.4, join 118, sort 55.5 ms without machine code; where each work's time goes now; BFS's arithmetic (a tail of about a tenth of the edges, done batch-side; edges spread into lanes, not walked together) and the three pieces it needs; the view-workers check's flake; 024 and CHECKPOINT say so
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walks (join 423 to 161 ms without machine code, the tier 74) and what a batch pays for, measured apart: an instruction about 20 ns a batch (0.02 ns a round at 1024 lanes), a reduction's end 4-9 ns a round, an append about 100 ns (the executor's), join's recurrence about 60 ns a round; BFS not batched (a count that grows, a filter that only grows, nested walks), so the JIT stays for now; the next in that order: appends at once, the recurrence's steps in registers, reductions' ends; 022 and 024 and CHECKPOINT say so
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stage 2 under ASan and UBSan (139 programs, the executor's output)
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together lane by lane, breaks, reductions folded in the rounds' order) and the measured passes after it (finite checks in the arithmetic's loop, tests as four-byte masks, the loop's value made once): roots 9.13 ms without machine code, below the tier's 9.57; matmul 50 (the tier 14.3: its table's loop and 15 instructions a nested round left); 685 random programs alike; 024 and CHECKPOINT say so
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knapsack 1,041 to 13.6 ms in the executor (the compiled code 7.5; its inner loop 1.17x the tier's, the stage's criterion missed; the table's adds left to stage 4), the executor without batch loops unchanged; what measuring overturned (a call among the steps cost 20% of the instructions, so two copies; run aligned to 64 for its cycles; results apart from operands for vector code); tests; 1024 lanes, 134 KB a thread; 024 and CHECKPOINT say so
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generic code's (steps 0.1%), what the tier needs for it (a list's count as a changing value); 023 cites words at e2e56dd
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knapsack 1.19, sort 1.37, join 2.54, words 5.58, matmul 1.85, BFS 1.61; geometric mean 1.92, from 3-300x at 6b45806), what each change did, the forms measured in assembly, the apps unchanged, what is left (text in the executor, BFS's appends, spills); CHECKPOINT says so
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without), the suite of seven kinds of work at 3-300x C, floors at 0.90x C with the meaning's checks hoisted to 0-3%; CHECKPOINT says so
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forms by hand beat C only packed, narrow and read ahead (123)
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and a Mac (121); 019 points at 020's view workers
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meanwhile, and queue=N's busy and its places coming back (020)
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shared, two askers 1.95 times one (122)
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fingers found and undone (121)
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what a request does (120)
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show a subscriber costs writes nothing (019)
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research 119)
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Requests to an app that checks tokens go 2.92% slower than to an open
one on 64 keep-alive connections, 2.2% of it the head the token makes
longer (an open app sent the same head is as slow); hashing every
request on a new connection costs 0.91%. 031 measures the three in
turns.
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The use after free in local_done and the owner's lock made after another
app's outlet used it were found reading the code, not by the check,
which passed with both before it was made to change senders (115, 017).
The usage now says changed lines change in place unless their store
moved; and 115 names the path no check takes: a module refused while
changing in place.
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Changing an app in place keeps a million items' app answering but for
1.12 ms (a host restart: 150 ms; stopping and starting it again from its
store, as first built, 150.4 ms), 171.5 ms when its records change shape
(332 ms). Another app's p99 stays 0.97 times as it was while one changes
every 0.2 s; a host of one app is as it was (TPC-C +0.7%, instructions
at most +0.02%); each module change leaves 19 KB. 030 holds the windows
of both builds, the isolation, the pairs, the counts and the memory.
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The same events make byte-identical stores on the x86_64 WSL2 (4 KiB
pages) as on the Pi and the Mac, and a store made on either of the Pi
and the WSL2 opens on the other and goes on the same.
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The same modules and inputs give the same outputs, failures and store
bytes on the Pi, an x86_64 WSL2 and an M3 Mac; other compilers found an
argument read before it was set, and the core and store build on macOS
again. WSL2's wall clock steps back about 2 s every 32 s. The Pi froze
twice under a measuring tool that held its output: it now streams it,
and experiments run under research/guard.py.
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The loop alone slowed four links to half: woken by every record queued,
it chased the owner a record at a time. Pushing once a turn made links
1.6 times as fast, with threads or the loop alike; the loop's own cost
is within the noise. Twenty outputs now add two threads, not 21.
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Two apps of one host, src sending one message for each of 1,000 items
in a burst event, 2,000 bursts a run, five rounds with the ways in
turns: the local outlet stores 1,141,642 sends a second at 1.17 us of
the host's CPU each, a loopback pure:// link to the host's own port
578,879 at 2.93 us (1.97 times the sends, 0.40 times the CPU). 017's
second stage asked for at least the link's rate at half its CPU or
less: it goes in. Every run checks dst's sum: each send came once.
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017's first stage met its four criteria on the Pi (RAM stores, five
rounds, the order of the ways turned): app B's 99th percentile while
app A is flooded by 64 connections is 168 us, half of two processes'
336 us; the two apps busy together write 146.1k a second against
146.2k, with the same 1.4 ms tail; an app costs a host 120 KiB of its
own memory (a process: 1,311 KiB PSS) and 100 apps still run on three
threads; a host of one app keeps its speed (TPC-C +1.2% at the median
of six pairs, two of them interfered and kept; the bank's queries
within 2.6%) and its instructions (+0.94% at most).
On the way: apps hopped between workers each turn (fixed in db4ee9c),
connections of one app spread over all connection threads made the
host a third more expensive a request and its tail a kernel tick
(fixed by home threads, d24881d), and the work budget's counting cost
every table row 26 instructions (fixed in be297ea). The earlier runs
are kept apart (db4ee9c's isolation, d24881d's pairs and counts, the
interrupted first try).
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The six pairs rerun once the Pi had been quiet for a minute, on the same
binaries. Two pairs were still interfered (the first's before at an
owner share of 0.54, the sixth at 0.73 on both sides); the four clean
ones are -1.7%, -0.4%, +1.8% and +1.1%, CPU per transaction 43.25 to
42.9 us. The bank's queries are as fast or faster after, though the
interference fell more on the before runs; the instruction counts stay
the comparison to trust.
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016's second stage passed its criterion: six interleaved pairs against
ee21aec gave TPC-C (RAM, W=1) -0.6% at the median and the bank's
queries 0.0% to +2.2%, no run interfered. The ranks query was slower
all six times, and chasing it showed that on this Pi timing cannot
separate 1-3%: two servers asked in turns disagree with themselves
(ee21aec to e02bfc9 +1.6%, e02bfc9 to 481642f -1.2%, ee21aec to 481642f
+2.8%), and a query whose instructions grew 0.6% ran 3.5% faster.
Instructions do not move so: pcount.c counts the server's user-mode
instructions with perf_event_open (no perf here), and psample.c samples
where they go. ranks had grown 0.4% in instructions (the rest was where
code and data landed), per_branch 3.6% and tables 20 instructions a row,
which 07047c3 halved. The six pairs of 07047c3 were interfered (another
session's build, load 4-12) and are kept apart, unused.
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Fetching a found item's cells, a leaf's keys and each level's keys ahead
made finding and reading items 20% faster on 100,000 items in a micro
benchmark, but TPC-C's clean pairs moved 1% at most and finding alone got
48% slower, so it is not in. The owner's finding samples were the descent,
not the fields: a write right after a read copies the leaf whole anyway,
and what costs is walking structures larger than the caches at random.
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(015, 108)
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check (108)
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Most of it was the allocator: leaves past glibc's thread cache, freed by
whichever thread let the last snapshot go. jemalloc was 11-14% faster
at more memory; reusing the nodes in Pure gave a median +9.4% over six
pairs, 4-8% less CPU a transaction in all six, and 1.97x the state bytes
resident where it was 2.18x. TPC-C in RAM is now 4.0x a tuned SQLite at
W=1 and 3.5x at W=4; finding items is the owner's largest part now.
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transaction
The 90x of 092 was against SQLite's defaults committing each
transaction; tuned for the card and grouped as Pure groups, SQLite is
4-11x behind, the bytes it writes a transaction being the difference.
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warehouses (106)
SQLite tuned first, by the criteria committed before (and, beyond them,
checkpoints each 40 MB of WAL, in its favour). On the SD card Pure stays
4.2-10.8x ahead at equal terminals, SQLite writing 8-18x the bytes a
transaction; in RAM 3.2-3.5x. All tables equal at W=1 and W=4, and
every run consistent. In RAM the one owner is the limit (0.94 of a core
at W=4, no gain from 16 to 64 terminals), a third of its busy time
copying nodes the snapshots share; checkpoints and memory are within
their criteria.
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The board is Vega's examples/shared-board.aup, and Vega's shared_board
check runs its two nodes: changes on either agree, and a partition
healed agrees on the later change. Reading a named field list once a
delivery would save part of 310 ns a record during upgrades alone: not
worth an API. What review 004 asked that is left is 103's third item,
broader performance comparisons under conditions stated first.
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aup spreads an item or a message into a send or a record, and sets an
item whole (c69682e): the board sends { ..at } and applies cards[k] =
Card { ..remote }, and a new field is written in two places, the record
and the output. v6 on both nodes, cut apart and joined again, agrees on
the later change; its module is byte for byte the one with every field
written.
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A board record of five fields (38 B) sent with v3's output fields took
310 ns to lay out for v4's input, reading the field list each time.
Only streams of another shape pay it, and only while nodes are upgraded
one after the other: less than a delivery's own work.
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