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perf: make the benchmark able to answer the question, then ask it

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PERF_PLAN phase 0, plus B1/B2 which turned out to cost seconds rather
than the minutes budgeted for them. No library code is touched.

The harness could not support the conclusions drawn from it. items_for()
shrank the sample as work per item grew, so exactly the rows under
investigation -- chain-16 and chain-32 -- ran 50 to 200 items and swung
4-8x between passes. Sample size now derives from a time budget with a
floor, using work_us * stages / units as the per-item cost. The old
ladder's error was treating depth as a throughput cost: past the core
count it is, below it depth costs only latency.

Rows now report median of N repetitions after a discarded warm-up, with
IQR and range, so an unreliable row says so instead of being averaged
into a table. The CSV header records nproc, governor and AC state, which
immediately caught this laptop running on battery under powersave.

A3 needed no experiment in the end: ru_nivcsw and ru_nvcsw are captured
around every timed region and reported per item, so involuntary switches
against depth is a column rather than a run.

bench_dispatch answers B1 and B2 without instrumenting the scheduler.
Sleeping is inferred from ru_nvcsw, since a thread blocking on a
condition variable books a voluntary context switch. B1: a ThreadPool(1)
dispatch is 291 ns null, 466 ns with a payload, against the ~290 ns the
plan estimated -- so the abandon criterion is not met and workstream B
stays alive.

B2's answer is not the one the question expected. It is not whether
workers sleep but which pool: on a private ThreadPool(1) the worker never
sleeps, because it resubmits into its own queue and finds the work
already there; on any pool of two or more it sleeps exactly once per
task, because submit() round-robins to a different worker, which is
asleep. That is the whole 466 ns to 1.7 us difference, and it inverts
half the plan. B5 (bounded spin) buys nothing in the default
configuration, and A5 must not make a shared pool the default until the
wake cost is fixed, or every graph that already fits its cores gets 3-4x
worse per dispatch.

G1 lands as tests/soak_wedge.cpp, superseding benchmarks/repro_wedge.cpp,
which was never wired into any build. Always compiled so it cannot rot;
its CTest cases register only under -DKPN_ENABLE_SOAK_TESTS=ON, so the
default test count is unchanged. A wedge is a hang, and a hang under
CTest is an unattributable timeout, so it carries a watchdog that aborts
naming the iteration and phase.

Phase 0's gate is not yet cleared: the acceptance run belongs on the
reference machine, not here. A 3-pass check lands every row within 0.7%
against the 4-8x swings described above, which is encouraging and is not
the same thing.

Provisional, recorded so it can be checked: chain-16 came out 6% behind
TBB rather than 28.5%. If that survives a proper run, the deep-chain
deficit is substantially an artefact of the N=200 rows.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
dtourolle
2026-08-08 12:13:11 +02:00
co-authored by Claude Opus 5
parent 771b9f8593
commit a3f61fcb3c
9 changed files with 1587 additions and 124 deletions
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benchmarks/bench_dispatch.cpp
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// Dispatch microbenchmark — PERF_PLAN B1 and B2.
//
// B1 asks what a single ThreadPool dispatch costs. B2 asks whether a worker
// actually sleeps per item, because the whole spin-window hypothesis (B5)
// depends on the answer: if workers are not sleeping, a spin window buys
// nothing and drops off the list.
//
// Both are answered here without touching the library. Sleeping is inferred
// from ru_nvcsw — a thread blocking on a condition variable books a voluntary
// context switch — so `vcsw/task` near 1.0 means a sleep per dispatch and near
// 0 means the worker never went to sleep at all.
//
// Three modes, because "the cost of a dispatch" is three different numbers:
//
// latency — one task in flight, pool idle in between. The worker is asleep
// at every submission, so this is dispatch cost *including* a
// wake. Worst case, and the case a spin window would attack.
//
// batch — submit K no-op tasks flat out, then drain. The worker is never
// idle, so this is the amortised floor: queue and heap operations
// with no wake at all. Reports the producer-side submit() cost
// separately from end-to-end throughput.
//
// steady — the task resubmits its successor, one in flight, each doing
// --work-us of work. This is what a KPN node actually does:
// fire_once processes a token and resubmits. On ThreadPool(1) the
// worker resubmits to its own queue; on ThreadPool(4) round-robin
// hands the task to a *different* worker, which may be asleep.
// That difference is the fanout cost wide-4 pays ~5x per item.
//
// Usage: ./bench_dispatch [--threads=1,2,4] [--mode=latency,batch,steady]
// [--tasks=200000] [--work-us=0] [--reps=5] [--warmup=1]
#include <kpn/kpn.hpp>
#include "bench_env.hpp"
#include <atomic>
#include <chrono>
#include <condition_variable>
#include <cstdio>
#include <cstdlib>
#include <mutex>
#include <string>
#include <vector>
using namespace kpn;
using sclock = std::chrono::steady_clock;
struct Opts {
std::vector<int> threads {1, 2, 4};
std::vector<std::string> modes {"latency", "batch", "steady"};
long tasks = 200000;
int work_us = 0;
int reps = 5;
int warmup = 1;
};
static Opts g_opts;
static void busy_us(int us) {
if (us <= 0) return;
auto end = sclock::now() + std::chrono::microseconds(us);
while (sclock::now() < end);
}
struct Sample {
double ns_per_dispatch = 0; // end-to-end, minus the work payload
double submit_ns = 0; // producer side only (batch mode)
double vcsw_per_task = 0; // B2: sleeps per dispatch
double ivcsw_per_task = 0;
};
// ── latency: one task at a time, worker asleep between submissions ────────────
static Sample run_latency(int threads, long tasks) {
ThreadPool pool(threads);
pool.start();
std::mutex mx;
std::condition_variable cv;
bool done = false;
bench::RusageDelta ru; ru.start();
auto t0 = sclock::now();
for (long i = 0; i < tasks; ++i) {
{ std::lock_guard lk(mx); done = false; }
pool.submit([&] {
busy_us(g_opts.work_us);
{ std::lock_guard lk(mx); done = true; }
cv.notify_one();
});
std::unique_lock lk(mx);
cv.wait(lk, [&] { return done; });
}
auto t1 = sclock::now();
Sample s;
long iv = 0, vc = 0;
ru.finish(iv, vc);
pool.stop();
double elapsed_ns = std::chrono::duration<double, std::nano>(t1 - t0).count();
s.ns_per_dispatch = elapsed_ns / tasks - g_opts.work_us * 1000.0;
// The requesting thread blocks once per task too, so it books a voluntary
// switch of its own; halve to attribute per side rather than per process.
s.vcsw_per_task = static_cast<double>(vc) / tasks / 2.0;
s.ivcsw_per_task = static_cast<double>(iv) / tasks;
return s;
}
// ── batch: submit flat out, drain once. No wake in the steady state ───────────
static Sample run_batch(int threads, long tasks) {
ThreadPool pool(threads);
pool.start();
std::atomic<long> ran{0};
bench::RusageDelta ru; ru.start();
auto t0 = sclock::now();
for (long i = 0; i < tasks; ++i)
pool.submit([&] {
busy_us(g_opts.work_us);
ran.fetch_add(1, std::memory_order_relaxed);
});
auto t_submitted = sclock::now();
pool.drain();
auto t1 = sclock::now();
Sample s;
long iv = 0, vc = 0;
ru.finish(iv, vc);
pool.stop();
if (ran.load() != tasks)
std::fprintf(stderr, "WARNING: batch ran %ld of %ld tasks\n",
ran.load(), tasks);
double elapsed_ns = std::chrono::duration<double, std::nano>(t1 - t0).count();
s.ns_per_dispatch = elapsed_ns / tasks - g_opts.work_us * 1000.0;
s.submit_ns = std::chrono::duration<double, std::nano>(t_submitted - t0).count() / tasks;
s.vcsw_per_task = static_cast<double>(vc) / tasks;
s.ivcsw_per_task = static_cast<double>(iv) / tasks;
return s;
}
// ── steady: the task resubmits its successor, as fire_once does ──────────────
static Sample run_steady(int threads, long tasks) {
ThreadPool pool(threads);
pool.start();
std::mutex mx;
std::condition_variable cv;
std::atomic<long> count{0};
bool finished = false;
// Recursive submission: hold the chain in a std::function so the task can
// resubmit itself. Captured by reference; it outlives the drain below.
//
// The counter is atomic rather than mutex-guarded so that this loop
// measures the pool's dispatch path and not a lock of the benchmark's own.
std::function<void()> step = [&] {
busy_us(g_opts.work_us);
long n = count.fetch_add(1, std::memory_order_relaxed) + 1;
if (n < tasks) {
pool.submit(step);
} else {
{ std::lock_guard lk(mx); finished = true; }
cv.notify_one();
}
};
bench::RusageDelta ru; ru.start();
auto t0 = sclock::now();
pool.submit(step);
{
std::unique_lock lk(mx);
cv.wait(lk, [&] { return finished; });
}
auto t1 = sclock::now();
Sample s;
long iv = 0, vc = 0;
ru.finish(iv, vc);
pool.stop();
double elapsed_ns = std::chrono::duration<double, std::nano>(t1 - t0).count();
s.ns_per_dispatch = elapsed_ns / tasks - g_opts.work_us * 1000.0;
s.vcsw_per_task = static_cast<double>(vc) / tasks;
s.ivcsw_per_task = static_cast<double>(iv) / tasks;
return s;
}
// ── driver ────────────────────────────────────────────────────────────────────
static void run_row(const std::string& mode, int threads, long tasks) {
auto once = [&] {
if (mode == "latency") return run_latency(threads, tasks);
if (mode == "batch") return run_batch(threads, tasks);
return run_steady(threads, tasks);
};
for (int i = 0; i < g_opts.warmup; ++i) (void)once();
std::vector<double> ns, sub, vcsw, ivcsw;
for (int i = 0; i < g_opts.reps; ++i) {
Sample s = once();
ns.push_back(s.ns_per_dispatch);
sub.push_back(s.submit_ns);
vcsw.push_back(s.vcsw_per_task);
ivcsw.push_back(s.ivcsw_per_task);
}
const double med = bench::percentile(ns, 0.5);
const double q1 = bench::percentile(ns, 0.25);
const double q3 = bench::percentile(ns, 0.75);
const double iqr = med > 0 ? 100.0 * (q3 - q1) / med : 0.0;
const double sleeps = bench::percentile(vcsw, 0.5);
std::fprintf(stderr, "%-9s %-8d %-8d %-10ld %-12.0f %-7.1f %-11.0f %-10.2f %-10.2f\n",
mode.c_str(), threads, g_opts.work_us, tasks, med, iqr,
bench::percentile(sub, 0.5), sleeps,
bench::percentile(ivcsw, 0.5));
// Column names deliberately match bench_pipeline's key columns so that
// scripts/bench_repro_check.py can gate this benchmark too.
std::printf("%s,%d,%d,%d,%ld,%d,%.1f,%.2f,%.1f,%.3f,%.3f\n",
mode.c_str(), threads, g_opts.work_us, threads, tasks,
g_opts.reps, med, iqr, bench::percentile(sub, 0.5),
sleeps, bench::percentile(ivcsw, 0.5));
std::fflush(stdout);
}
static std::vector<int> parse_int_list(const char* s) {
std::vector<int> out;
const char* p = s;
while (*p) {
char* end = nullptr;
long v = std::strtol(p, &end, 10);
if (end == p) break;
out.push_back(static_cast<int>(v));
p = end;
while (*p == ',' || *p == ' ') ++p;
}
return out;
}
static std::vector<std::string> parse_word_list(const std::string& s) {
std::vector<std::string> out;
std::size_t pos = 0;
while (pos <= s.size()) {
std::size_t c = s.find(',', pos);
if (c == std::string::npos) c = s.size();
if (c > pos) out.push_back(s.substr(pos, c - pos));
pos = c + 1;
}
return out;
}
static void usage() {
std::fprintf(stderr,
"usage: bench_dispatch [options]\n"
" --threads=1,2,4 pool sizes\n"
" --mode=latency,batch,steady which measurements to run\n"
" --tasks=200000 dispatches per repetition\n"
" --work-us=0 payload per task\n"
" --reps=5 --warmup=1\n");
}
int main(int argc, char** argv) {
for (int i = 1; i < argc; ++i) {
std::string a = argv[i];
auto eq = a.find('=');
std::string key = a.substr(0, eq);
std::string val = eq == std::string::npos ? "" : a.substr(eq + 1);
if (key == "--help" || key == "-h") { usage(); return 0; }
else if (key == "--threads") g_opts.threads = parse_int_list(val.c_str());
else if (key == "--mode") g_opts.modes = parse_word_list(val);
else if (key == "--tasks") g_opts.tasks = std::atol(val.c_str());
else if (key == "--work-us") g_opts.work_us = std::atoi(val.c_str());
else if (key == "--reps") g_opts.reps = std::atoi(val.c_str());
else if (key == "--warmup") g_opts.warmup = std::atoi(val.c_str());
else { std::fprintf(stderr, "unknown option: %s\n", a.c_str()); usage(); return 2; }
}
if (g_opts.reps < 1) g_opts.reps = 1;
if (g_opts.warmup < 0) g_opts.warmup = 0;
char cfg[160];
std::snprintf(cfg, sizeof cfg, "tasks=%ld work_us=%d reps=%d warmup=%d",
g_opts.tasks, g_opts.work_us, g_opts.reps, g_opts.warmup);
bench::print_environment(cfg);
std::fprintf(stderr, "\n%-9s %-8s %-8s %-10s %-12s %-7s %-11s %-10s %-10s\n",
"mode", "threads", "work_us", "tasks", "ns/dispatch", "iqr%",
"submit_ns", "vcsw/task", "ivcsw/task");
std::fprintf(stderr, "%s\n", std::string(96, '-').c_str());
std::printf("topology,size,work_us,threads,items,reps,ns_per_dispatch,"
"iqr_pct,submit_ns,vcsw_per_task,ivcsw_per_task\n");
// latency is a round trip per task, so it is far slower per dispatch than
// the other modes; scale it down rather than run for minutes.
for (const auto& mode : g_opts.modes)
for (int t : g_opts.threads) {
long tasks = mode == "latency"
? std::max(2000L, g_opts.tasks / 20)
: g_opts.tasks;
run_row(mode, t, tasks);
}
}