perf(data): absolute-space pyramid so acquire() is O(produced), not O(window)
Frame cost was O(capacity x levels) once the ring saturated: acquire() saw the window base move (it always moves once the ring wraps), cleared the pyramid and re-appended all 1,048,576 retained samples, and append() walked every live level with no early stop -- 13,647,936 bucket merges and 73.8 ms per frame at a 1M-sample window, scaling with the window, which is what capped the 1 MS/s demo at 32-58 ms/frame while it was still filling. Index the pyramid in absolute bucket space instead. Level l bucket k covers the samples [k * (kBucket << l), (k + 1) * (kBucket << l)), so a bucket's span never depends on where the window starts and the window can slide over the aggregate instead of forcing it to be rebuilt. Each level keeps its complete buckets in a deque plus the absolute base of its first entry; append() folds a sample into the single in-progress level-0 bucket and, only when that bucket completes, cascades upward, stopping at the first level that gains no new entry; a new drop_before() slides the window by discarding leading buckets and remembers where the window begins. acquire() is now: drop to the new base, then append exactly what was produced -- 256 merges and 0.034 ms per frame for 8192 new samples, independent of the window, and memory bounded by the window (32,767 entries after 50M samples through a 1M ring, the same as after 10M). A producer that laps the consumer by more than capacity() between two acquires restarts the window rather than splicing a gap. Interface: `level(l) -> std::span<const MinMax>` cannot survive a ring and is replaced by level_base/level_size/bucket in absolute bucket coordinates, plus window_base/window_end/drop_before. The *_buckets queries stay in window coordinates (index 0 = oldest retained sample), so Series keeps its window semantics for callers; its exactness split now aligns in absolute space (window_base() + the ceil/floor) because the bucket grid is absolute. The sums move from per-level prefix sums to per-bucket ones -- the only representation a sliding front can keep exact -- and StreamSeries::y_bounds() becomes reduce(0, size()), exact in O(log n + kBucket) per frame instead of a scan of the window. The pyramid owns the published window now, so there is no second copy of base/end to keep in step, and gather() emits only buckets that are both complete and wholly retained. Tests: test-only merge counters (mirroring PLOT_PYRAMID_COUNT_COVERS, absent from every non-test build) pin an acquire proportional to production and independent of capacity, an append cost amortised over 16 live levels, and bounded memory; brute-force checks pin absolute bucket aggregates across slides, sliding-window reduce/sum/sumsq over unaligned ranges, and the level-1 gather mapping. The demo now draws 946 samples/px at 1.03 ms/frame (967 fps) where the saturated window cost 54.96 ms/frame (18 fps).
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@@ -40,9 +40,10 @@ add_executable(plot_tests
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egl_headless.cpp
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)
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target_link_libraries(plot_tests PRIVATE plot::core ${plot_egl_library} Threads::Threads)
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# Same switch the library is built with: the decomposition-cost test reads the
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# counter behind it (see include/plot/data/detail/cover_count.hpp).
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target_compile_definitions(plot_tests PRIVATE PLOT_PYRAMID_COUNT_COVERS)
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# Same switches the library is built with: the cost tests read the counters
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# behind them (see include/plot/data/detail/{cover,merge}_count.hpp).
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target_compile_definitions(plot_tests PRIVATE PLOT_PYRAMID_COUNT_COVERS
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PLOT_PYRAMID_COUNT_MERGES)
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plot_apply_warnings(plot_tests)
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add_test(NAME plot_tests COMMAND plot_tests)
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@@ -1,12 +1,36 @@
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#include "harness.hpp"
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#include <plot/data/detail/cover_count.hpp>
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#include <plot/data/detail/merge_count.hpp>
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#include <plot/data/minmax_pyramid.hpp>
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#include <algorithm>
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#include <random>
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using plot::data::kBucket;
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using plot::data::MinMax;
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using plot::data::MinMaxPyramid;
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using plot::Range;
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namespace {
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/// Brute-force aggregate of the absolute span of level-`l` bucket `b`, from the
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/// same value function the pyramid was fed. This is the oracle the absolute
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/// bucket indexing is judged against: a bucket that has slid inside the window
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/// must still aggregate exactly its own absolute samples.
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template <typename ValueFn>
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MinMax brute_bucket(u32 l, u64 b, const ValueFn& value) {
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const u64 span = u64{kBucket} << l;
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const u64 first = b * span;
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MinMax m{value(first), value(first)};
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for (u64 i = first + 1; i < first + span; ++i) {
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const f32 v = value(i);
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m.min = std::min(m.min, v);
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m.max = std::max(m.max, v);
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}
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return m;
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}
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} // namespace
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PLOT_TEST(pyramid_bucket_extremes_preserved) {
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MinMaxPyramid p;
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p.reserve(1000);
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@@ -107,7 +131,8 @@ PLOT_TEST(pyramid_clear_and_rebuild) {
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// bucket and ask the bucket-grained query for its extrema.
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for (u32 i = 1; i < kBucket; ++i) p.append(1.0f);
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PLOT_CHECK(p.size() == kBucket);
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PLOT_CHECK(p.level(0).size() == 1);
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PLOT_CHECK(p.level_base(0) == 0);
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PLOT_CHECK(p.level_size(0) == 1);
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PLOT_CHECK_NEAR(p.reduce_buckets(0, kBucket).max, 7.0, 1e-6);
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PLOT_CHECK_NEAR(p.reduce_buckets(0, kBucket).min, 1.0, 1e-6);
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}
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@@ -121,7 +146,7 @@ PLOT_TEST(pyramid_cover_cost_is_logarithmic_for_unaligned_starts) {
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MinMaxPyramid p;
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p.reserve(1'000'000);
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for (u64 i = 0; i < 1'000'000; ++i) p.append(0.0f);
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PLOT_CHECK(p.level(0).size() == 1'000'000 / kBucket); // 15625, no partial bucket
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PLOT_CHECK(p.level_size(0) == 1'000'000 / kBucket); // 15625, no partial bucket
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auto folds_for = [&](u64 begin, u64 end) {
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plot::data::detail::cover_entry_count().store(0, std::memory_order_relaxed);
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@@ -134,3 +159,131 @@ PLOT_TEST(pyramid_cover_cost_is_logarithmic_for_unaligned_starts) {
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PLOT_CHECK(unaligned < 100);
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PLOT_CHECK(unaligned <= u64{4} * aligned); // misalignment costs entries, not a scan
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}
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PLOT_TEST(pyramid_drop_before_slides_the_window) {
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MinMaxPyramid p;
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for (u64 i = 0; i < 4096; ++i) p.append(f32(i % 13));
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PLOT_CHECK(p.window_base() == 0);
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PLOT_CHECK(p.window_end() == 4096);
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PLOT_CHECK(p.size() == 4096);
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p.drop_before(1000);
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PLOT_CHECK(p.window_base() == 1000);
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PLOT_CHECK(p.size() == 3096);
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// The window's first *whole* bucket starts at 1024: the bucket the drop cut
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// into is not representable as a whole bucket and is never queried.
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PLOT_CHECK(p.level_base(0) == 1024 / kBucket);
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PLOT_CHECK(p.level_base(0) + p.level_size(0) == 4096 / kBucket);
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f32 lo = 1.0f, hi = -1.0f;
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for (u64 i = 1024; i < 4096; ++i) {
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lo = std::min(lo, f32(i % 13));
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hi = std::max(hi, f32(i % 13));
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}
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const Range r = p.reduce_buckets(0, p.size());
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PLOT_CHECK_NEAR(r.min, lo, 1e-6);
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PLOT_CHECK_NEAR(r.max, hi, 1e-6);
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// Window [1000, 1024) holds no whole bucket at all: an empty answer, not one
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// that quietly reaches into the dropped samples.
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PLOT_CHECK(p.reduce_buckets(0, 24).span() == 0.0);
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PLOT_CHECK(p.sum_buckets(0, 24) == 0.0);
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PLOT_CHECK(p.sumsq_buckets(0, 24) == 0.0);
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p.drop_before(1000); // at the base: no-op
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PLOT_CHECK(p.window_base() == 1000);
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p.drop_before(4096); // at the end: the window is empty
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PLOT_CHECK(p.size() == 0);
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p.append(5.0f); // and appending starts a fresh window
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PLOT_CHECK(p.size() == 1);
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PLOT_CHECK(p.window_base() == 4096);
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}
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PLOT_TEST(pyramid_bucket_aggregates_stay_absolute_across_slides) {
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// The invariant the sliding window rests on: a bucket that has slid inside the
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// window is never recomputed, so it must already hold the aggregate of its own
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// absolute span -- at every level, after any number of drops.
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MinMaxPyramid p;
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const auto value = [](u64 i) { return f32((i * 37u) % 101u) - 50.0f; };
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constexpr u64 kTotal = 20'000;
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constexpr u64 kWindow = 4'000;
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for (u64 i = 0; i < kTotal; ++i) {
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p.append(value(i));
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if ((i + 1) % 997 == 0 && i + 1 > kWindow) p.drop_before(i + 1 - kWindow);
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}
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// The last drop is the last multiple of 997 at or below kTotal.
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PLOT_CHECK(p.window_base() == (kTotal / 997) * 997 - kWindow);
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for (u32 l = 0; l < p.level_count(); ++l) {
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PLOT_CHECK(p.level_size(l) > 0);
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const u64 span = u64{kBucket} << l;
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for (u64 b = p.level_base(l); b < p.level_base(l) + p.level_size(l); ++b) {
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const MinMax want = brute_bucket(l, b, value);
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const MinMax got = p.bucket(l, b);
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PLOT_CHECK_NEAR(got.min, want.min, 1e-6);
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PLOT_CHECK_NEAR(got.max, want.max, 1e-6);
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PLOT_CHECK(b * span >= p.window_base()); // wholly inside the window
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PLOT_CHECK((b + 1) * span <= p.window_end()); // and complete
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}
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}
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}
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PLOT_TEST(pyramid_sliding_window_bucket_queries_match_bruteforce) {
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MinMaxPyramid p;
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const auto value = [](u64 i) { return f32(i % 89) * 0.25f - 5.0f; };
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constexpr u64 kTotal = 12'000;
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constexpr u64 kWindow = 3'000;
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for (u64 i = 0; i < kTotal; ++i) {
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p.append(value(i));
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if ((i + 1) % 613 != 0) continue;
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const u64 abs0 = i + 1 > kWindow ? i + 1 - kWindow : 0;
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p.drop_before(abs0);
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const u64 n = p.size();
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// Window coordinates: window index j is absolute abs0 + j.
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const u64 first = abs0 / kBucket + (abs0 % kBucket == 0 ? u64{0} : u64{1});
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const u64 last = (abs0 + n) / kBucket;
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if (last <= first) continue;
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f32 lo = 1e30f, hi = -1e30f;
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f64 sum = 0.0, sq = 0.0;
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for (u64 a = first * kBucket; a < last * kBucket; ++a) {
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const f32 v = value(a);
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lo = std::min(lo, v);
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hi = std::max(hi, v);
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sum += f64(v);
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sq += f64(v) * f64(v);
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}
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const u64 wb = first * kBucket - abs0;
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const u64 we = last * kBucket - abs0;
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const Range r = p.reduce_buckets(wb, we);
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PLOT_CHECK_NEAR(r.min, lo, 1e-6);
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PLOT_CHECK_NEAR(r.max, hi, 1e-6);
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PLOT_CHECK_NEAR(p.sum_buckets(wb, we), sum, 1e-3);
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PLOT_CHECK_NEAR(p.sumsq_buckets(wb, we), sq, 1e-1);
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}
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}
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PLOT_TEST(pyramid_append_cost_is_amortised_constant) {
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// A sample must not walk the live levels: level l gains an entry once per
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// kBucket << l samples, so N appends perform ~N/32 merges however many levels
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// the pyramid holds. Walking every level per append costs ~N * levels.
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MinMaxPyramid p;
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p.reserve(1u << 20);
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constexpr u64 kAppends = 1u << 20;
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for (u64 i = 0; i < kAppends; ++i) p.append(0.5f);
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PLOT_CHECK(p.level_count() >= 10); // 2^20 samples: 16384 level-0 buckets
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plot::data::detail::merge_count().store(0, std::memory_order_relaxed);
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for (u64 i = 0; i < kAppends; ++i) p.append(0.5f);
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const u64 merges = plot::data::detail::merge_count().load(std::memory_order_relaxed);
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// ~N/64 + N/128 + ... = ~N/32; the bound leaves 2x room, and is four orders of
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// magnitude below the N * live_levels an unbounded walk would perform.
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PLOT_CHECK(merges <= kAppends / 16);
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// Sliding must not add per-sample work either: the appends below run against a
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// window whose base moves with every sample.
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plot::data::detail::merge_count().store(0, std::memory_order_relaxed);
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for (u64 i = 0; i < kAppends; ++i) {
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p.drop_before(i + 1);
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p.append(0.5f);
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}
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const u64 slid = plot::data::detail::merge_count().load(std::memory_order_relaxed);
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PLOT_CHECK(slid <= kAppends / 16);
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}
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@@ -1,13 +1,18 @@
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#include "harness.hpp"
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#include <plot/data/array_series.hpp>
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#include <plot/data/detail/merge_count.hpp>
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#include <plot/data/stream_series.hpp>
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#include <algorithm>
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#include <array>
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#include <atomic>
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#include <chrono>
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#include <cmath>
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#include <random>
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#include <thread>
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#include <vector>
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using plot::data::kBucket;
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PLOT_TEST(array_series_bounds_and_gather) {
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std::vector<f32> y{1, 5, -2, 3};
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plot::data::ArraySeries s(std::move(y), /*x0=*/10.0, /*dx=*/0.5);
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@@ -159,3 +164,184 @@ PLOT_TEST(stream_series_push_and_read_are_race_free) {
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PLOT_CHECK(reads >= 1);
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PLOT_CHECK(sizes_ok);
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}
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namespace {
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/// Buckets the pyramid holds across every level: its footprint, not its window.
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u64 pyramid_entries(const plot::data::MinMaxPyramid& p) {
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u64 total = 0;
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for (u32 l = 0; l < p.level_count(); ++l) total += p.level_size(l);
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return total;
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}
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} // namespace
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PLOT_TEST(stream_series_sliding_window_queries_match_bruteforce) {
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// After the base has moved many times, an exact query must still match a scan
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// of exactly the retained samples. The pyramid's buckets live in absolute
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// sample space while the window's base is arbitrary, and that meeting point is
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// where an off-by-one hides -- so test the sliding case, not just the static
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// ArraySeries one.
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constexpr u64 kCapacity = 1u << 14;
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constexpr u64 kPushes = 60'000;
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const auto value = [](u64 i) { return f32((i * 29u) % 173u) - 86.0f; };
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plot::data::StreamSeries s(kCapacity, 0.0, 1e-6);
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for (u64 i = 0; i < kPushes; i += 337) {
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const u64 n = std::min<u64>(337, kPushes - i);
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for (u64 k = 0; k < n; ++k) s.push(value(i + k));
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s.acquire(); // the window's base moves on every one of these
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}
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const u64 n = s.size();
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const u64 base = s.produced() - n;
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PLOT_CHECK(n == kCapacity);
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PLOT_CHECK(base > 2 * kCapacity); // the window really did slide
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PLOT_CHECK(s.pyramid().size() == n); // pyramid() indexes the window
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PLOT_CHECK(s.pyramid().window_base() == base);
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PLOT_CHECK(s.pyramid().window_end() == s.produced());
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PLOT_CHECK_NEAR(s.x0(), f64(base) * 1e-6, 1e-12);
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PLOT_CHECK(s.x_bounds().min == s.x0());
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PLOT_CHECK_NEAR(s.x_bounds().max, f64(base + n - 1) * 1e-6, 1e-9);
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// Brute force in window coordinates over the retained samples only.
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const auto brute = [&](u64 a, u64 b) {
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f64 lo = f64(value(base + a)), hi = lo;
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f64 sum = 0.0, sq = 0.0;
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for (u64 i = a; i < b; ++i) {
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const f64 v = f64(value(base + i));
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lo = std::min(lo, v);
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hi = std::max(hi, v);
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sum += v;
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sq += v * v;
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}
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return std::array<f64, 4>{lo, hi, sum, sq};
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};
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const u64 starts[] = {0, 1, 63, 64, 65, 1000, 7919, n - 200};
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for (const u64 a : starts) {
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for (u64 b = a + 1; b <= n; b += 1301) {
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const std::array<f64, 4> want = brute(a, b);
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const plot::Range r = s.reduce(a, b);
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PLOT_CHECK_NEAR(r.min, want[0], 1e-4);
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PLOT_CHECK_NEAR(r.max, want[1], 1e-4);
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PLOT_CHECK_NEAR(s.sum(a, b), want[2], 1e-2);
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PLOT_CHECK_NEAR(s.sumsq(a, b), want[3], 1e-1);
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}
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}
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const std::array<f64, 4> whole = brute(0, n);
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PLOT_CHECK_NEAR(s.y_bounds().min, whole[0], 1e-6);
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PLOT_CHECK_NEAR(s.y_bounds().max, whole[1], 1e-6);
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// The level accessors are in absolute bucket coordinates: a stored bucket must
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// aggregate its own absolute span, the sliding window included.
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const u64 span = u64{kBucket} << 1;
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const u64 lbase = s.pyramid().level_base(1);
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const u64 lsize = s.pyramid().level_size(1);
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PLOT_CHECK(lsize >= 2);
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for (u64 b = lbase; b < lbase + std::min<u64>(lsize, 4); ++b) {
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const std::array<f64, 4> want = brute(b * span - base, (b + 1) * span - base);
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const plot::data::MinMax m = s.pyramid().bucket(1, b);
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PLOT_CHECK_NEAR(m.min, want[0], 1e-6);
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PLOT_CHECK_NEAR(m.max, want[1], 1e-6);
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}
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// level-1 gather: one envelope pair per retained bucket the range overlaps, x
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// at the bucket's own first and last sample. This is the mapping the renderer
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// draws from.
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std::vector<f32> out;
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s.gather(1, 0, n, out);
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const u64 first = std::max(base / span, lbase);
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const u64 last = std::min((base + n - 1) / span + 1, lbase + lsize);
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PLOT_CHECK(out.size() == 4 * (last - first));
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for (u64 bi = first; bi < last; ++bi) {
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const std::array<f64, 4> want = brute(bi * span - base, (bi + 1) * span - base);
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const plot::usize k = static_cast<plot::usize>(bi - first);
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const u64 first_sample = bi * span - base;
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const u64 last_sample = std::min((bi + 1) * span, base + n) - 1 - base;
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// x is in data coordinates: x0() is the retained window's first sample, so
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// window index j plots at (base + j) * dx.
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PLOT_CHECK_NEAR(out[4 * k], f32(f64(base + first_sample) * 1e-6), 1e-9);
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PLOT_CHECK_NEAR(out[4 * k + 1], want[0], 1e-6);
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PLOT_CHECK_NEAR(out[4 * k + 2], f32(f64(base + last_sample) * 1e-6), 1e-9);
|
||||
PLOT_CHECK_NEAR(out[4 * k + 3], want[1], 1e-6);
|
||||
}
|
||||
}
|
||||
|
||||
PLOT_TEST(stream_series_steady_state_acquire_is_proportional_to_produced) {
|
||||
// The defect this pins: a saturated ring whose base moved every frame used to
|
||||
// rebuild the whole window, costing O(capacity * live_levels) merges per
|
||||
// acquire. It must cost O(samples produced since the last acquire) instead, so
|
||||
// the same production through a 16x larger window must cost the same.
|
||||
const auto merges_for = [](u64 capacity) {
|
||||
plot::data::StreamSeries s(capacity, 0.0, 1.0);
|
||||
constexpr u64 kSaturate = 1u << 20;
|
||||
for (u64 i = 0; i < kSaturate; ++i) s.push(f32(i % 977));
|
||||
s.acquire();
|
||||
PLOT_CHECK(s.size() == capacity);
|
||||
|
||||
constexpr u64 kFrames = 64;
|
||||
constexpr u64 kFrame = 1u << 13; // 8192 samples: 1 MS/s at ~122 fps
|
||||
plot::data::detail::merge_count().store(0, std::memory_order_relaxed);
|
||||
for (u64 f = 0; f < kFrames; ++f) {
|
||||
for (u64 k = 0; k < kFrame; ++k) s.push(f32((kSaturate + f * kFrame + k) % 977));
|
||||
s.acquire();
|
||||
}
|
||||
return plot::data::detail::merge_count().load(std::memory_order_relaxed);
|
||||
};
|
||||
|
||||
constexpr u64 kProduced = 64 * (1u << 13);
|
||||
const u64 small = merges_for(1u << 16); // 64k-sample window
|
||||
const u64 big = merges_for(1u << 20); // 1M-sample window: 16x to rebuild
|
||||
// ~kProduced/32 in practice; rebuilding the 1M window alone would merge
|
||||
// kCapacity/64 * live_levels ~ 245'000 buckets per acquire.
|
||||
PLOT_CHECK(small <= kProduced / 16);
|
||||
PLOT_CHECK(big <= kProduced / 16);
|
||||
PLOT_CHECK(big <= 2 * small + kBucket);
|
||||
}
|
||||
|
||||
PLOT_TEST(stream_series_steady_state_acquire_is_fast) {
|
||||
// Wall-clock backstop for the merge count above: rebuilding the 1M-sample
|
||||
// window measured ~44 ms, so 128 such frames would need ~5.6 s. The sliding
|
||||
// path does the same work in a few milliseconds; the bound is two orders of
|
||||
// magnitude clear of both, so it is not a thin timing margin.
|
||||
plot::data::StreamSeries s(1u << 20, 0.0, 1.0);
|
||||
constexpr u64 kSaturate = 1u << 20;
|
||||
for (u64 i = 0; i < kSaturate; ++i) s.push(f32(i % 977));
|
||||
s.acquire();
|
||||
|
||||
constexpr u64 kFrames = 128;
|
||||
constexpr u64 kFrame = 1u << 13;
|
||||
const auto t0 = std::chrono::steady_clock::now();
|
||||
for (u64 f = 0; f < kFrames; ++f) {
|
||||
for (u64 k = 0; k < kFrame; ++k) s.push(f32((kSaturate + f * kFrame + k) % 977));
|
||||
s.acquire();
|
||||
}
|
||||
const f64 ms =
|
||||
std::chrono::duration<f64>(std::chrono::steady_clock::now() - t0).count() * 1.0e3;
|
||||
PLOT_CHECK(s.size() == 1u << 20);
|
||||
PLOT_CHECK(ms < 250.0);
|
||||
}
|
||||
|
||||
PLOT_TEST(stream_series_pyramid_memory_is_bounded_by_the_window) {
|
||||
// 50M samples through a 1M-sample ring: the pyramid's footprint must track the
|
||||
// retained window (n/64 level-0 buckets plus the levels over them), not the
|
||||
// samples ever pushed.
|
||||
constexpr u64 kCapacity = 1u << 20;
|
||||
constexpr u64 kTotal = 50u * (1u << 20);
|
||||
constexpr u64 kChunk = 1u << 19;
|
||||
plot::data::StreamSeries s(kCapacity, 0.0, 1.0);
|
||||
u64 entries_after_10m = 0;
|
||||
for (u64 p = 0; p < kTotal; p += kChunk) {
|
||||
for (u64 i = 0; i < kChunk; ++i) s.push(f32((p + i) % 251));
|
||||
s.acquire();
|
||||
if (p + kChunk == 10u * (1u << 20)) entries_after_10m = pyramid_entries(s.pyramid());
|
||||
}
|
||||
const u64 entries = pyramid_entries(s.pyramid());
|
||||
const u64 bound = 2 * (kCapacity / kBucket) + kBucket;
|
||||
PLOT_CHECK(s.produced() == kTotal);
|
||||
PLOT_CHECK(s.size() == kCapacity);
|
||||
PLOT_CHECK(entries <= bound);
|
||||
// 5x the samples pushed, same footprint: levels deeper than one chunk can
|
||||
// differ by a bucket each, hence the slack.
|
||||
PLOT_CHECK(entries <= entries_after_10m + kBucket);
|
||||
}
|
||||
Reference in new issue
Block a user