Moved benchmarks into a seperate file and exe
This commit is contained in:
adrien
parent
a518a86fb2
commit
1fd86a5807
428
src/Scalar.zig
428
src/Scalar.zig
@ -197,48 +197,39 @@ test "Add" {
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const added = distance.add(distance2);
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try std.testing.expectEqual(30, added.value);
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try std.testing.expectEqual(1, @TypeOf(added).dims.get(.L));
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std.debug.print("KiloMeter {d} + {d} = {d} OK\n", .{ distance, distance2, added });
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const KiloMeter = Scalar(i128, Dimensions.init(.{ .L = 1 }), Scales.init(.{ .L = .k }));
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const distance3 = KiloMeter{ .value = 2 };
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const added2 = distance.add(distance3);
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try std.testing.expectEqual(2010, added2.value);
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try std.testing.expectEqual(1, @TypeOf(added2).dims.get(.L));
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std.debug.print("KiloMeter {d} + {d} = {d} OK\n", .{ distance, distance3, added2 });
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const added3 = distance3.add(distance).to(KiloMeter);
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try std.testing.expectEqual(2, added3.value);
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try std.testing.expectEqual(1, @TypeOf(added3).dims.get(.L));
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std.debug.print("KiloMeter {d} + {d} = {d} OK\n", .{ distance3, distance, added3 });
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const KiloMeter_f = Scalar(f64, Dimensions.init(.{ .L = 1 }), Scales.init(.{ .L = .k }));
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const distance4 = KiloMeter_f{ .value = 2 };
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const added4 = distance4.add(distance).to(KiloMeter_f);
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try std.testing.expectApproxEqAbs(2.01, added4.value, 0.000001);
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try std.testing.expectEqual(1, @TypeOf(added4).dims.get(.L));
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std.debug.print("KiloMeter_f {d} + {d} = {d:.2} OK\n", .{ distance4, distance, added4 });
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}
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test "Sub" {
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const Meter = Scalar(i128, Dimensions.init(.{ .L = 1 }), Scales.init(.{}));
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const KiloMeter = Scalar(i128, Dimensions.init(.{ .L = 1 }), Scales.init(.{ .L = .k }));
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const KiloMeter_f = Scalar(f64, Dimensions.init(.{ .L = 1 }), Scales.init(.{ .L = .k }));
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const a = Meter{ .value = 500 };
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const b = Meter{ .value = 200 };
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const diff = a.sub(b);
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try std.testing.expectEqual(300, diff.value);
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std.debug.print("Sub: {d} - {d} = {d} OK\n", .{ a, b, diff });
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const km = KiloMeter{ .value = 1 };
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const diff2 = a.sub(km);
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std.debug.print("Sub cross-scale: {d} - {d} = {d}\n", .{ a, km, diff2 });
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const diff2 = b.sub(a);
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try std.testing.expectEqual(-300, diff2.value);
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const km_f = KiloMeter_f{ .value = 2.5 };
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const m_f = Meter{ .value = 500 };
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const diff3 = km_f.sub(m_f);
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try std.testing.expectApproxEqAbs(2000, diff3.value, 1e-4);
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std.debug.print("Sub float cross-scale: {d} - {d} = {d} OK\n", .{ km_f, m_f, diff3 });
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}
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test "MulBy" {
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@ -252,14 +243,12 @@ test "MulBy" {
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try std.testing.expectEqual(12, area_time.value);
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try std.testing.expectEqual(1, @TypeOf(area_time).dims.get(.L));
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try std.testing.expectEqual(1, @TypeOf(area_time).dims.get(.T));
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std.debug.print("MulBy: {d} * {d} = {d} OK\n", .{ d, t, area_time });
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const d2 = Meter{ .value = 5.0 };
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const area = d.mulBy(d2);
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try std.testing.expectEqual(15, area.value);
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try std.testing.expectEqual(2, @TypeOf(area).dims.get(.L));
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try std.testing.expectEqual(0, @TypeOf(area).dims.get(.T));
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std.debug.print("MulBy: {d} * {d} = {d} OK\n", .{ d, d2, area });
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}
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test "MulBy with scale" {
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@ -271,7 +260,6 @@ test "MulBy with scale" {
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const prod = dist.mulBy(mass);
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try std.testing.expectEqual(1, @TypeOf(prod).dims.get(.L));
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try std.testing.expectEqual(1, @TypeOf(prod).dims.get(.M));
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std.debug.print("MulBy scaled: {d} * {d} = {d} OK\n", .{ dist, mass, prod });
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}
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test "MulBy with type change" {
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@ -289,7 +277,6 @@ test "MulBy with type change" {
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try std.testing.expectApproxEqAbs(12, area_time_f.value, 0.0001);
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try std.testing.expectEqual(1, @TypeOf(area_time).dims.get(.L));
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try std.testing.expectEqual(1, @TypeOf(area_time).dims.get(.T));
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std.debug.print("MulBy: {d} * {d} = {d} OK\n", .{ d, t, area_time });
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}
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test "MulBy small" {
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@ -303,7 +290,6 @@ test "MulBy small" {
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try std.testing.expectEqual(12, area_time.value);
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try std.testing.expectEqual(1, @TypeOf(area_time).dims.get(.L));
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try std.testing.expectEqual(1, @TypeOf(area_time).dims.get(.T));
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std.debug.print("MulBy: {d} * {d} = {d} OK\n", .{ d, t, area_time });
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}
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test "Scale" {
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@ -314,12 +300,10 @@ test "Scale" {
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const scaled = d.scale(3);
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try std.testing.expectEqual(21, scaled.value);
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try std.testing.expectEqual(1, @TypeOf(scaled).dims.get(.L));
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std.debug.print("Scale int: {d} * 3 = {d} OK\n", .{ d, scaled });
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const t = Second{ .value = 1.5 };
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const scaled_f = t.scale(4.0);
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try std.testing.expectApproxEqAbs(@as(f32, 6.0), scaled_f.value, 1e-4);
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std.debug.print("Scale float: {d} * 4 = {d} OK\n", .{ t, scaled_f });
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}
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test "Chained: velocity and acceleration" {
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@ -338,8 +322,6 @@ test "Chained: velocity and acceleration" {
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try std.testing.expectEqual(5, accel.value);
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try std.testing.expectEqual(1, @TypeOf(accel).dims.get(.L));
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try std.testing.expectEqual(-2, @TypeOf(accel).dims.get(.T));
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std.debug.print("Velocity: {d}, Acceleration: {d} OK\n", .{ velocity, accel });
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}
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test "DivBy integer exact" {
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@ -353,7 +335,6 @@ test "DivBy integer exact" {
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try std.testing.expectEqual(30, vel.value);
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try std.testing.expectEqual(1, @TypeOf(vel).dims.get(.L));
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try std.testing.expectEqual(-1, @TypeOf(vel).dims.get(.T));
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std.debug.print("DivBy int: {d} / {d} = {d} OK\n", .{ dist, time, vel });
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}
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test "Conversion chain: km -> m -> cm" {
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@ -367,7 +348,6 @@ test "Conversion chain: km -> m -> cm" {
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try std.testing.expectEqual(15_000, m.value);
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try std.testing.expectEqual(1_500_000, cm.value);
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std.debug.print("Chain: {d} -> {d} -> {d} OK\n", .{ km, m, cm });
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}
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test "Conversion: hours -> minutes -> seconds" {
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@ -381,7 +361,6 @@ test "Conversion: hours -> minutes -> seconds" {
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try std.testing.expectEqual(60, min.value);
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try std.testing.expectEqual(3600, sec.value);
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std.debug.print("Time chain: {d} -> {d} -> {d} OK\n", .{ h, min, sec });
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}
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test "Negative values" {
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@ -391,7 +370,6 @@ test "Negative values" {
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const b = Meter{ .value = 20 };
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const diff = a.sub(b);
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try std.testing.expectEqual(-15, diff.value);
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std.debug.print("Negative sub: {d} - {d} = {d} OK\n", .{ a, b, diff });
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}
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test "Format Scalar" {
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@ -405,396 +383,22 @@ test "Format Scalar" {
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Dimensions.init(.{ .M = 1, .L = 1, .T = -1 }),
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Scales.init(.{ .M = .k }),
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);
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const Meter = Scalar(f32, Dimensions.init(.{ .L = 1 }), Scales.init(.{}));
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const m = Meter{ .value = 1.23456 };
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const accel = MeterPerSecondSq{ .value = 9.81 };
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const momentum = KgMeterPerSecond{ .value = 42.0 };
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std.debug.print("Acceleration: {d}\n", .{accel});
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std.debug.print("Momentum: {d}\n", .{momentum});
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}
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test "Benchmark Scalar" {
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const Io = std.Io;
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const ITERS: usize = 100_000;
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const SAMPLES: usize = 10; // Number of samples for stats
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var gsink: f64 = 0;
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const io = std.testing.io;
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// Standard Zig 0.16 timestamp retrieval
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const getTime = struct {
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fn f(i: Io) Io.Timestamp {
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return Io.Clock.awake.now(i);
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}
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}.f;
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const fold = struct {
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fn f(comptime TT: type, s: *f64, v: TT) void {
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s.* += if (comptime @typeInfo(TT) == .float)
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@as(f64, @floatCast(v))
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else
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@as(f64, @floatFromInt(v));
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}
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}.f;
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const getVal = struct {
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fn f(comptime TT: type, i: usize, comptime mask: u7) TT {
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const v: u8 = @as(u8, @truncate(i & @as(usize, mask))) + 1;
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return if (comptime @typeInfo(TT) == .float) @floatFromInt(v) else @intCast(v);
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}
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}.f;
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const Stats = struct {
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median: f64,
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delta: f64,
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ops_per_sec: f64,
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};
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const computeStats = struct {
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fn f(samples: []f64, iters: usize) Stats {
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std.mem.sort(f64, samples, {}, std.sort.asc(f64));
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const mid = samples.len / 2;
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const median_ns = if (samples.len % 2 == 0) (samples[mid - 1] + samples[mid]) / 2.0 else samples[mid];
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const low = samples[0];
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const high = samples[samples.len - 1];
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const delta_ns = (high - low) / 2.0;
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const ns_per_op = median_ns / @as(f64, @floatFromInt(iters));
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return .{
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.median = ns_per_op,
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.delta = (delta_ns / @as(f64, @floatFromInt(iters))),
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.ops_per_sec = 1_000_000_000.0 / ns_per_op,
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};
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}
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}.f;
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std.debug.print(
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\\
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\\ Scalar<T> benchmark — {d} iterations, {d} samples/cell
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\\
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\\┌───────────────────┬──────┬─────────────────────┬─────────────────────┐
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\\│ Operation │ Type │ ns / op (± delta) │ Throughput (ops/s) │
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\\├───────────────────┼──────┼─────────────────────┼─────────────────────┤
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\\
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, .{ ITERS, SAMPLES });
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const Types = .{ i16, i32, i64, i128, i256, f32, f64, f128 };
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const TNames = .{ "i16", "i32", "i64", "i128", "i256", "f32", "f64", "f128" };
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const Ops = .{ "add", "sub", "mulBy", "divBy", "scale", "to" };
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var results_matrix: [Ops.len][Types.len]f64 = undefined;
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comptime var tidx: usize = 0;
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inline for (Types, TNames) |T, tname| {
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const M = Scalar(T, Dimensions.init(.{ .L = 1 }), Scales.init(.{}));
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const KM = Scalar(T, Dimensions.init(.{ .L = 1 }), Scales.init(.{ .L = .k }));
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const S = Scalar(T, Dimensions.init(.{ .T = 1 }), Scales.init(.{}));
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inline for (Ops, 0..) |op_name, oidx| {
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var samples: [SAMPLES]f64 = undefined;
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for (0..SAMPLES) |s_idx| {
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var sink: T = 0;
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const t_start = getTime(io);
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for (0..ITERS) |i| {
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const r = if (comptime std.mem.eql(u8, op_name, "add"))
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(M{ .value = getVal(T, i, 63) }).add(M{ .value = getVal(T, i +% 7, 63) })
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else if (comptime std.mem.eql(u8, op_name, "sub"))
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(M{ .value = getVal(T, i +% 10, 63) }).sub(M{ .value = getVal(T, i, 63) })
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else if (comptime std.mem.eql(u8, op_name, "mulBy"))
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(M{ .value = getVal(T, i, 63) }).mulBy(M{ .value = getVal(T, i +% 1, 63) })
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else if (comptime std.mem.eql(u8, op_name, "divBy"))
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(M{ .value = getVal(T, i +% 10, 63) }).divBy(S{ .value = getVal(T, i, 63) })
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else if (comptime std.mem.eql(u8, op_name, "scale"))
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(M{ .value = getVal(T, i, 63) }).scale(getVal(T, i +% 2, 63))
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else
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(KM{ .value = getVal(T, i, 15) }).to(M);
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if (comptime @typeInfo(T) == .float) sink += r.value else sink ^= r.value;
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}
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const t_end = getTime(io);
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samples[s_idx] = @as(f64, @floatFromInt(t_start.durationTo(t_end).toNanoseconds()));
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fold(T, &gsink, sink);
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}
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const stats = computeStats(&samples, ITERS);
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results_matrix[oidx][tidx] = stats.median;
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std.debug.print("│ {s:<17} │ {s:<4} │ {d:>8.2} ns ±{d:<6.2} │ {d:>19.0} │\n", .{ op_name, tname, stats.median, stats.delta, stats.ops_per_sec });
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}
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if (comptime tidx < Types.len - 1) {
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std.debug.print("├───────────────────┼──────┼─────────────────────┼─────────────────────┤\n", .{});
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}
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tidx += 1;
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}
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// Median Summary Table
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std.debug.print("└───────────────────┴──────┴─────────────────────┴─────────────────────┘\n\n", .{});
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std.debug.print("Median Summary (ns/op):\n", .{});
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std.debug.print("┌──────────────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┐\n", .{});
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std.debug.print("│ Operation │ i16 │ i32 │ i64 │ i128 │ i256 │ f32 │ f64 │ f128 │\n", .{});
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std.debug.print("├──────────────┼───────┼───────┼───────┼───────┼───────┼───────┼───────┼───────┤\n", .{});
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inline for (Ops, 0..) |op_name, oidx| {
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std.debug.print("│ {s:<11} │", .{op_name});
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var i: usize = 0;
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while (i < Types.len) : (i += 1) {
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std.debug.print("{d:>6.1} │", .{results_matrix[oidx][i]});
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}
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std.debug.print("\n", .{});
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}
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std.debug.print("└──────────────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┘\n", .{});
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std.debug.print("\nAnti-optimisation sink: {d:.4}\n", .{gsink});
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try std.testing.expect(gsink != 0);
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}
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test "Overhead Analysis: Scalar vs Native" {
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const Io = std.Io;
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const ITERS: usize = 100_000;
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const SAMPLES: usize = 5;
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const io = std.testing.io;
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const getTime = struct {
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fn f(i: Io) Io.Timestamp {
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return Io.Clock.awake.now(i);
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}
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}.f;
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const fold = struct {
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fn f(comptime TT: type, s: *f64, v: TT) void {
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s.* += if (comptime @typeInfo(TT) == .float)
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@as(f64, @floatCast(v))
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else
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@as(f64, @floatFromInt(v));
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}
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}.f;
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// Helper to safely get a value of type T from a loop index
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const getValT = struct {
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fn f(comptime TT: type, i: usize) TT {
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const v = (i % 100) + 1;
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return if (comptime @typeInfo(TT) == .float) @floatFromInt(v) else @intCast(v);
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}
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}.f;
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const Types = .{ i32, i64, i128, f32, f64 };
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const TNames = .{ "i32", "i64", "i128", "f32", "f64" };
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const Ops = .{ "add", "mulBy", "divBy" };
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var gsink: f64 = 0;
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std.debug.print(
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\\
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\\ Scalar vs Native Overhead Analysis
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\\
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\\┌───────────┬──────┬───────────┬───────────┬───────────┐
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\\│ Operation │ Type │ Native │ Scalar │ Slowdown │
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\\├───────────┼──────┼───────────┼───────────┼───────────┤
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\\
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, .{});
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inline for (Ops, 0..) |op_name, j| {
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inline for (Types, 0..) |T, tidx| {
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var native_total_ns: f64 = 0;
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var quantity_total_ns: f64 = 0;
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const M = Scalar(T, Dimensions.init(.{ .L = 1 }), Scales.init(.{}));
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const S = Scalar(T, Dimensions.init(.{ .T = 1 }), Scales.init(.{}));
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for (0..SAMPLES) |_| {
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// --- 1. Benchmark Native ---
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var n_sink: T = 0;
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const n_start = getTime(io);
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for (0..ITERS) |i| {
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const a = getValT(T, i);
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const b = getValT(T, 2);
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const r = if (comptime std.mem.eql(u8, op_name, "add"))
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a + b
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else if (comptime std.mem.eql(u8, op_name, "mulBy"))
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a * b
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else if (comptime @typeInfo(T) == .int) @divTrunc(a, b) else a / b;
|
||||
|
||||
if (comptime @typeInfo(T) == .float) n_sink += r else n_sink ^= r;
|
||||
}
|
||||
const n_end = getTime(io);
|
||||
native_total_ns += @as(f64, @floatFromInt(n_start.durationTo(n_end).toNanoseconds()));
|
||||
fold(T, &gsink, n_sink);
|
||||
|
||||
// --- 2. Benchmark Scalar ---
|
||||
var q_sink: T = 0;
|
||||
const q_start = getTime(io);
|
||||
for (0..ITERS) |i| {
|
||||
const qa = M{ .value = getValT(T, i) };
|
||||
const qb = if (comptime std.mem.eql(u8, op_name, "divBy")) S{ .value = getValT(T, 2) } else M{ .value = getValT(T, 2) };
|
||||
|
||||
const r = if (comptime std.mem.eql(u8, op_name, "add"))
|
||||
qa.add(qb)
|
||||
else if (comptime std.mem.eql(u8, op_name, "mulBy"))
|
||||
qa.mulBy(qb)
|
||||
else
|
||||
qa.divBy(qb);
|
||||
|
||||
if (comptime @typeInfo(T) == .float) q_sink += r.value else q_sink ^= r.value;
|
||||
}
|
||||
const q_end = getTime(io);
|
||||
quantity_total_ns += @as(f64, @floatFromInt(q_start.durationTo(q_end).toNanoseconds()));
|
||||
fold(T, &gsink, q_sink);
|
||||
}
|
||||
|
||||
const avg_n = (native_total_ns / SAMPLES) / @as(f64, @floatFromInt(ITERS));
|
||||
const avg_q = (quantity_total_ns / SAMPLES) / @as(f64, @floatFromInt(ITERS));
|
||||
const slowdown = avg_q / avg_n;
|
||||
|
||||
std.debug.print("│ {s:<9} │ {s:<4} │ {d:>7.2}ns │ {d:>7.2}ns │ {d:>8.2}x │\n", .{
|
||||
op_name, TNames[tidx], avg_n, avg_q, slowdown,
|
||||
});
|
||||
}
|
||||
if (j != Ops.len - 1) std.debug.print("├───────────┼──────┼───────────┼───────────┼───────────┤\n", .{});
|
||||
}
|
||||
|
||||
std.debug.print("└───────────┴──────┴───────────┴───────────┴───────────┘\n", .{});
|
||||
try std.testing.expect(gsink != 0);
|
||||
}
|
||||
|
||||
test "Cross-Type Overhead Analysis: Scalar vs Native" {
|
||||
const Io = std.Io;
|
||||
const ITERS: usize = 100_000;
|
||||
const SAMPLES: usize = 5;
|
||||
const io = std.testing.io;
|
||||
|
||||
const getTime = struct {
|
||||
fn f(i: Io) Io.Timestamp {
|
||||
return Io.Clock.awake.now(i);
|
||||
}
|
||||
}.f;
|
||||
|
||||
const fold = struct {
|
||||
fn f(comptime TT: type, s: *f64, v: TT) void {
|
||||
s.* += if (comptime @typeInfo(TT) == .float)
|
||||
@as(f64, @floatCast(v))
|
||||
else
|
||||
@as(f64, @floatFromInt(v));
|
||||
}
|
||||
}.f;
|
||||
|
||||
const getValT = struct {
|
||||
fn f(comptime TT: type, i: usize) TT {
|
||||
// Keep values safe and non-zero to avoid division by zero or overflows during cross-casting
|
||||
const v = (i % 50) + 1;
|
||||
return if (comptime @typeInfo(TT) == .float) @floatFromInt(v) else @intCast(v);
|
||||
}
|
||||
}.f;
|
||||
|
||||
// Helper for the Native baseline: explicitly casting T2 to T1 before the operation
|
||||
const castTo = struct {
|
||||
fn f(comptime DestT: type, comptime SrcT: type, val: SrcT) DestT {
|
||||
if (comptime DestT == SrcT) return val;
|
||||
const src_info = @typeInfo(SrcT);
|
||||
const dest_info = @typeInfo(DestT);
|
||||
|
||||
if (dest_info == .int and src_info == .int) return @intCast(val);
|
||||
if (dest_info == .float and src_info == .int) return @floatFromInt(val);
|
||||
if (dest_info == .int and src_info == .float) return @intFromFloat(val);
|
||||
if (dest_info == .float and src_info == .float) return @floatCast(val);
|
||||
unreachable;
|
||||
}
|
||||
}.f;
|
||||
|
||||
const Types = .{ i16, i64, i128, f32, f64 };
|
||||
const TNames = .{ "i16", "i64", "i128", "f32", "f64" };
|
||||
const Ops = .{ "add", "mulBy", "divBy" };
|
||||
|
||||
var gsink: f64 = 0;
|
||||
|
||||
std.debug.print(
|
||||
\\
|
||||
\\ Cross-Type Overhead Analysis: Scalar vs Native
|
||||
\\
|
||||
\\┌─────────┬──────┬──────┬───────────┬───────────┬───────────┐
|
||||
\\│ Op │ T1 │ T2 │ Native │ Scalar │ Slowdown │
|
||||
\\├─────────┼──────┼──────┼───────────┼───────────┼───────────┤
|
||||
\\
|
||||
, .{});
|
||||
|
||||
inline for (Ops, 0..) |op_name, j| {
|
||||
inline for (Types, 0..) |T1, t1_idx| {
|
||||
inline for (Types, 0..) |T2, t2_idx| {
|
||||
var native_total_ns: f64 = 0;
|
||||
var quantity_total_ns: f64 = 0;
|
||||
|
||||
const M1 = Scalar(T1, Dimensions.init(.{ .L = 1 }), Scales.init(.{}));
|
||||
const M2 = Scalar(T2, Dimensions.init(.{ .L = 1 }), Scales.init(.{}));
|
||||
const S2 = Scalar(T2, Dimensions.init(.{ .T = 1 }), Scales.init(.{}));
|
||||
|
||||
for (0..SAMPLES) |_| {
|
||||
// --- 1. Benchmark Native (Cast T2 to T1, then math) ---
|
||||
var n_sink: T1 = 0;
|
||||
const n_start = getTime(io);
|
||||
for (0..ITERS) |i| {
|
||||
const a = getValT(T1, i);
|
||||
const b_raw = getValT(T2, 2);
|
||||
const b = castTo(T1, T2, b_raw);
|
||||
|
||||
const r = if (comptime std.mem.eql(u8, op_name, "add"))
|
||||
a + b
|
||||
else if (comptime std.mem.eql(u8, op_name, "mulBy"))
|
||||
a * b
|
||||
else if (comptime @typeInfo(T1) == .int)
|
||||
@divTrunc(a, b)
|
||||
else
|
||||
a / b;
|
||||
|
||||
if (comptime @typeInfo(T1) == .float) n_sink += r else n_sink ^= r;
|
||||
}
|
||||
const n_end = getTime(io);
|
||||
native_total_ns += @as(f64, @floatFromInt(n_start.durationTo(n_end).toNanoseconds()));
|
||||
fold(T1, &gsink, n_sink);
|
||||
|
||||
// --- 2. Benchmark Scalar ---
|
||||
var q_sink: T1 = 0;
|
||||
const q_start = getTime(io);
|
||||
for (0..ITERS) |i| {
|
||||
const qa = M1{ .value = getValT(T1, i) };
|
||||
const qb = if (comptime std.mem.eql(u8, op_name, "divBy"))
|
||||
S2{ .value = getValT(T2, 2) }
|
||||
else
|
||||
M2{ .value = getValT(T2, 2) };
|
||||
|
||||
const r = if (comptime std.mem.eql(u8, op_name, "add"))
|
||||
qa.add(qb)
|
||||
else if (comptime std.mem.eql(u8, op_name, "mulBy"))
|
||||
qa.mulBy(qb)
|
||||
else
|
||||
qa.divBy(qb);
|
||||
|
||||
if (comptime @typeInfo(T1) == .float) q_sink += r.value else q_sink ^= r.value;
|
||||
}
|
||||
const q_end = getTime(io);
|
||||
quantity_total_ns += @as(f64, @floatFromInt(q_start.durationTo(q_end).toNanoseconds()));
|
||||
fold(T1, &gsink, q_sink);
|
||||
}
|
||||
|
||||
const avg_n = (native_total_ns / SAMPLES) / @as(f64, @floatFromInt(ITERS));
|
||||
const avg_q = (quantity_total_ns / SAMPLES) / @as(f64, @floatFromInt(ITERS));
|
||||
const slowdown = avg_q / avg_n;
|
||||
|
||||
std.debug.print("│ {s:<7} │ {s:<4} │ {s:<4} │ {d:>7.2}ns │ {d:>7.2}ns │ {d:>8.2}x │\n", .{
|
||||
op_name, TNames[t1_idx], TNames[t2_idx], avg_n, avg_q, slowdown,
|
||||
});
|
||||
}
|
||||
}
|
||||
if (j != Ops.len - 1) {
|
||||
std.debug.print("├─────────┼──────┼──────┼───────────┼───────────┼───────────┤\n", .{});
|
||||
}
|
||||
}
|
||||
|
||||
std.debug.print("└─────────┴──────┴──────┴───────────┴───────────┴───────────┘\n", .{});
|
||||
try std.testing.expect(gsink != 0);
|
||||
var buf: [64]u8 = undefined;
|
||||
var res = try std.fmt.bufPrint(&buf, "{d:.2}", .{m});
|
||||
try std.testing.expectEqualStrings("1.23m", res);
|
||||
|
||||
res = try std.fmt.bufPrint(&buf, "{d}", .{accel});
|
||||
try std.testing.expectEqualStrings("9.81m.ns⁻²", res);
|
||||
|
||||
res = try std.fmt.bufPrint(&buf, "{d}", .{momentum});
|
||||
try std.testing.expectEqualStrings("42m.kg.s⁻¹", res);
|
||||
|
||||
res = try std.fmt.bufPrint(&buf, "{d:_>10.1}", .{m});
|
||||
try std.testing.expectEqualStrings("_______1.2m", res);
|
||||
}
|
||||
|
||||
129
src/Vector.zig
129
src/Vector.zig
@ -204,8 +204,12 @@ test "Format VectorX" {
|
||||
const accel = MeterPerSecondSq.Vec3.initDefault(9.81);
|
||||
const momentum = KgMeterPerSecond.Vec3{ .data = .{ 43, 0, 11 } };
|
||||
|
||||
std.debug.print("Acceleration: {d}\n", .{accel});
|
||||
std.debug.print("Momentum: {d:.2}\n", .{momentum});
|
||||
var buf: [64]u8 = undefined;
|
||||
var res = try std.fmt.bufPrint(&buf, "{d}", .{accel});
|
||||
try std.testing.expectEqualStrings("(9.81, 9.81, 9.81)m.ns⁻²", res);
|
||||
|
||||
res = try std.fmt.bufPrint(&buf, "{d:.2}", .{momentum});
|
||||
try std.testing.expectEqualStrings("(43.00, 0.00, 11.00)m.kg.s⁻¹", res);
|
||||
}
|
||||
|
||||
test "VecX Init and Basic Arithmetic" {
|
||||
@ -326,124 +330,3 @@ test "VecX Length" {
|
||||
try std.testing.expectApproxEqAbs(@as(f32, 25.0), v_float.lengthSqr(), 1e-4);
|
||||
try std.testing.expectApproxEqAbs(@as(f32, 5.0), v_float.length(), 1e-4);
|
||||
}
|
||||
|
||||
test "Benchmark Vector ops" {
|
||||
const Io = std.Io;
|
||||
const ITERS: usize = 10_000;
|
||||
const SAMPLES: usize = 10;
|
||||
var gsink: f64 = 0;
|
||||
|
||||
// In Zig 0.14+, we use the testing IO for clock access in tests
|
||||
const io = std.testing.io;
|
||||
|
||||
const getTime = struct {
|
||||
fn f(i: Io) Io.Timestamp {
|
||||
return Io.Clock.awake.now(i);
|
||||
}
|
||||
}.f;
|
||||
|
||||
const getVal = struct {
|
||||
fn f(comptime TT: type, i: usize, comptime mask: u7) TT {
|
||||
const v: u8 = @as(u8, @truncate(i & @as(usize, mask))) + 1;
|
||||
return if (comptime @typeInfo(TT) == .float) @floatFromInt(v) else @intCast(v);
|
||||
}
|
||||
}.f;
|
||||
|
||||
const fold = struct {
|
||||
fn f(comptime TT: type, s: *f64, v: TT) void {
|
||||
s.* += if (comptime @typeInfo(TT) == .float)
|
||||
@as(f64, @floatCast(v))
|
||||
else
|
||||
@as(f64, @floatFromInt(v));
|
||||
}
|
||||
}.f;
|
||||
|
||||
const computeStats = struct {
|
||||
fn f(samples: []f64, iters: usize) f64 {
|
||||
std.mem.sort(f64, samples, {}, std.sort.asc(f64));
|
||||
const mid = samples.len / 2;
|
||||
const median_ns = if (samples.len % 2 == 0)
|
||||
(samples[mid - 1] + samples[mid]) / 2.0
|
||||
else
|
||||
samples[mid];
|
||||
return median_ns / @as(f64, @floatFromInt(iters));
|
||||
}
|
||||
}.f;
|
||||
|
||||
std.debug.print(
|
||||
\\
|
||||
\\ Vector<N, T> benchmark — {d} iterations, {d} samples/cell
|
||||
\\ (Results in ns/op)
|
||||
\\
|
||||
\\┌─────────────┬──────┬─────────┬─────────┬─────────┐
|
||||
\\│ Operation │ Type │ Len=3 │ Len=4 │ Len=16 │
|
||||
\\├─────────────┼──────┼─────────┼─────────┼─────────┤
|
||||
\\
|
||||
, .{ ITERS, SAMPLES });
|
||||
|
||||
const Types = .{ i32, i64, i128, f32, f64 };
|
||||
const TNames = .{ "i32", "i64", "i128", "f32", "f64" };
|
||||
const Lengths = .{ 3, 4, 16 };
|
||||
const Ops = .{ "add", "scale", "mulByScalar", "length" };
|
||||
|
||||
inline for (Ops, 0..) |op_name, o_idx| {
|
||||
inline for (Types, TNames) |T, tname| {
|
||||
std.debug.print("│ {s:<11} │ {s:<4} │", .{ op_name, tname });
|
||||
|
||||
inline for (Lengths) |len| {
|
||||
const Q_base = Scalar(T, Dimensions.init(.{ .L = 1 }), Scales.init(.{}));
|
||||
const Q_time = Scalar(T, Dimensions.init(.{ .T = 1 }), Scales.init(.{}));
|
||||
const V = Vector(len, Q_base);
|
||||
|
||||
var samples: [SAMPLES]f64 = undefined;
|
||||
|
||||
for (0..SAMPLES) |s_idx| {
|
||||
var sink: T = 0;
|
||||
|
||||
const t_start = getTime(io);
|
||||
for (0..ITERS) |i| {
|
||||
const v1 = V.initDefault(getVal(T, i, 63));
|
||||
|
||||
if (comptime std.mem.eql(u8, op_name, "add")) {
|
||||
const v2 = V.initDefault(getVal(T, i +% 7, 63));
|
||||
const res = v1.add(v2);
|
||||
for (res.data) |val| {
|
||||
if (comptime @typeInfo(T) == .float) sink += val else sink ^= val;
|
||||
}
|
||||
} else if (comptime std.mem.eql(u8, op_name, "scale")) {
|
||||
const sc = getVal(T, i +% 2, 63);
|
||||
const res = v1.scale(sc);
|
||||
for (res.data) |val| {
|
||||
if (comptime @typeInfo(T) == .float) sink += val else sink ^= val;
|
||||
}
|
||||
} else if (comptime std.mem.eql(u8, op_name, "mulByScalar")) {
|
||||
const s_val = Q_time{ .value = getVal(T, i +% 2, 63) };
|
||||
const res = v1.mulByScalar(s_val);
|
||||
for (res.data) |val| {
|
||||
if (comptime @typeInfo(T) == .float) sink += val else sink ^= val;
|
||||
}
|
||||
} else if (comptime std.mem.eql(u8, op_name, "length")) {
|
||||
const r = v1.length();
|
||||
if (comptime @typeInfo(T) == .float) sink += r else sink ^= r;
|
||||
}
|
||||
}
|
||||
const t_end = getTime(io);
|
||||
|
||||
samples[s_idx] = @as(f64, @floatFromInt(t_start.durationTo(t_end).toNanoseconds()));
|
||||
fold(T, &gsink, sink);
|
||||
}
|
||||
|
||||
const median_ns_per_op = computeStats(&samples, ITERS);
|
||||
std.debug.print(" {d:>7.1} │", .{median_ns_per_op});
|
||||
}
|
||||
std.debug.print("\n", .{});
|
||||
}
|
||||
|
||||
if (o_idx < Ops.len - 1) {
|
||||
std.debug.print("├─────────────┼──────┼─────────┼─────────┼─────────┤\n", .{});
|
||||
}
|
||||
}
|
||||
std.debug.print("└─────────────┴──────┴─────────┴─────────┴─────────┘\n", .{});
|
||||
std.debug.print("\nAnti-optimisation sink: {d:.4}\n", .{gsink});
|
||||
try std.testing.expect(gsink != 0);
|
||||
}
|
||||
|
||||
471
src/benchmark.zig
Normal file
471
src/benchmark.zig
Normal file
@ -0,0 +1,471 @@
|
||||
const std = @import("std");
|
||||
const Io = std.Io;
|
||||
const Scalar = @import("Scalar.zig").Scalar;
|
||||
const Vector = @import("Vector.zig").Vector;
|
||||
|
||||
var io: Io = undefined;
|
||||
pub fn main(init: std.process.Init) !void {
|
||||
var stdout_buf: [4096]u8 = undefined;
|
||||
var stdout_writer: std.Io.File.Writer = .init(.stdout(), init.io, &stdout_buf);
|
||||
try stdout_writer.interface.print("Starting Benchmarks...", .{});
|
||||
|
||||
io = init.io;
|
||||
|
||||
try bench_Scalar(&stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
try bench_vsNative(&stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
try bench_crossTypeVsNative(&stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
try bench_Vector(&stdout_writer.interface);
|
||||
try stdout_writer.flush();
|
||||
}
|
||||
|
||||
fn getTime() Io.Timestamp {
|
||||
return Io.Clock.awake.now(io);
|
||||
}
|
||||
|
||||
fn fold(comptime TT: type, s: *f64, v: TT) void {
|
||||
s.* += if (comptime @typeInfo(TT) == .float)
|
||||
@as(f64, @floatCast(v))
|
||||
else
|
||||
@as(f64, @floatFromInt(v));
|
||||
}
|
||||
|
||||
fn bench_Scalar(writer: *std.Io.Writer) !void {
|
||||
const ITERS: usize = 100_000;
|
||||
const SAMPLES: usize = 10;
|
||||
|
||||
var gsink: f64 = 0;
|
||||
|
||||
const getVal = struct {
|
||||
fn f(comptime TT: type, i: usize, comptime mask: u7) TT {
|
||||
const v: u8 = @as(u8, @truncate(i & @as(usize, mask))) + 1;
|
||||
return if (comptime @typeInfo(TT) == .float) @floatFromInt(v) else @intCast(v);
|
||||
}
|
||||
}.f;
|
||||
|
||||
const Stats = struct {
|
||||
median: f64,
|
||||
delta: f64,
|
||||
ops_per_sec: f64,
|
||||
};
|
||||
|
||||
const computeStats = struct {
|
||||
fn f(samples: []f64, iters: usize) Stats {
|
||||
std.mem.sort(f64, samples, {}, std.sort.asc(f64));
|
||||
const mid = samples.len / 2;
|
||||
const median_ns = if (samples.len % 2 == 0) (samples[mid - 1] + samples[mid]) / 2.0 else samples[mid];
|
||||
|
||||
const low = samples[0];
|
||||
const high = samples[samples.len - 1];
|
||||
const delta_ns = (high - low) / 2.0;
|
||||
|
||||
const ns_per_op = median_ns / @as(f64, @floatFromInt(iters));
|
||||
return .{
|
||||
.median = ns_per_op,
|
||||
.delta = (delta_ns / @as(f64, @floatFromInt(iters))),
|
||||
.ops_per_sec = 1_000_000_000.0 / ns_per_op,
|
||||
};
|
||||
}
|
||||
}.f;
|
||||
|
||||
try writer.print(
|
||||
\\
|
||||
\\ Scalar<T> benchmark — {d} iterations, {d} samples/cell
|
||||
\\
|
||||
\\┌───────────────────┬──────┬─────────────────────┬─────────────────────┐
|
||||
\\│ Operation │ Type │ ns / op (± delta) │ Throughput (ops/s) │
|
||||
\\├───────────────────┼──────┼─────────────────────┼─────────────────────┤
|
||||
\\
|
||||
, .{ ITERS, SAMPLES });
|
||||
|
||||
const Types = .{ i16, i32, i64, i128, i256, f32, f64, f128 };
|
||||
const TNames = .{ "i16", "i32", "i64", "i128", "i256", "f32", "f64", "f128" };
|
||||
const Ops = .{ "add", "sub", "mulBy", "divBy", "scale", "to" };
|
||||
|
||||
var results_matrix: [Ops.len][Types.len]f64 = undefined;
|
||||
|
||||
comptime var tidx: usize = 0;
|
||||
inline for (Types, TNames) |T, tname| {
|
||||
const M = Scalar(T, .init(.{ .L = 1 }), .init(.{}));
|
||||
const KM = Scalar(T, .init(.{ .L = 1 }), .init(.{ .L = .k }));
|
||||
const S = Scalar(T, .init(.{ .T = 1 }), .init(.{}));
|
||||
|
||||
inline for (Ops, 0..) |op_name, oidx| {
|
||||
var samples: [SAMPLES]f64 = undefined;
|
||||
|
||||
for (0..SAMPLES) |s_idx| {
|
||||
var sink: T = 0;
|
||||
const t_start = getTime();
|
||||
|
||||
for (0..ITERS) |i| {
|
||||
const r = if (comptime std.mem.eql(u8, op_name, "add"))
|
||||
(M{ .value = getVal(T, i, 63) }).add(M{ .value = getVal(T, i +% 7, 63) })
|
||||
else if (comptime std.mem.eql(u8, op_name, "sub"))
|
||||
(M{ .value = getVal(T, i +% 10, 63) }).sub(M{ .value = getVal(T, i, 63) })
|
||||
else if (comptime std.mem.eql(u8, op_name, "mulBy"))
|
||||
(M{ .value = getVal(T, i, 63) }).mulBy(M{ .value = getVal(T, i +% 1, 63) })
|
||||
else if (comptime std.mem.eql(u8, op_name, "divBy"))
|
||||
(M{ .value = getVal(T, i +% 10, 63) }).divBy(S{ .value = getVal(T, i, 63) })
|
||||
else if (comptime std.mem.eql(u8, op_name, "scale"))
|
||||
(M{ .value = getVal(T, i, 63) }).scale(getVal(T, i +% 2, 63))
|
||||
else
|
||||
(KM{ .value = getVal(T, i, 15) }).to(M);
|
||||
|
||||
if (comptime @typeInfo(T) == .float) sink += r.value else sink ^= r.value;
|
||||
}
|
||||
|
||||
const t_end = getTime();
|
||||
samples[s_idx] = @as(f64, @floatFromInt(t_start.durationTo(t_end).toNanoseconds()));
|
||||
fold(T, &gsink, sink);
|
||||
}
|
||||
|
||||
const stats = computeStats(&samples, ITERS);
|
||||
results_matrix[oidx][tidx] = stats.median;
|
||||
|
||||
try writer.print("│ {s:<17} │ {s:<4} │ {d:>8.2} ns ±{d:<6.2} │ {d:>19.0} │\n", .{ op_name, tname, stats.median, stats.delta, stats.ops_per_sec });
|
||||
}
|
||||
|
||||
if (comptime tidx < Types.len - 1) {
|
||||
try writer.print("├───────────────────┼──────┼─────────────────────┼─────────────────────┤\n", .{});
|
||||
}
|
||||
tidx += 1;
|
||||
}
|
||||
|
||||
// Median Summary Table
|
||||
try writer.print("└───────────────────┴──────┴─────────────────────┴─────────────────────┘\n\n", .{});
|
||||
try writer.print("Median Summary (ns/op):\n", .{});
|
||||
|
||||
try writer.print("┌──────────────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┬───────┐\n", .{});
|
||||
try writer.print("│ Operation │ i16 │ i32 │ i64 │ i128 │ i256 │ f32 │ f64 │ f128 │\n", .{});
|
||||
try writer.print("├──────────────┼───────┼───────┼───────┼───────┼───────┼───────┼───────┼───────┤\n", .{});
|
||||
|
||||
inline for (Ops, 0..) |op_name, oidx| {
|
||||
try writer.print("│ {s:<11} │", .{op_name});
|
||||
var i: usize = 0;
|
||||
while (i < Types.len) : (i += 1)
|
||||
try writer.print("{d:>6.1} │", .{results_matrix[oidx][i]});
|
||||
|
||||
try writer.print("\n", .{});
|
||||
}
|
||||
|
||||
try writer.print("└──────────────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┴───────┘\n", .{});
|
||||
|
||||
try writer.print("\nAnti-optimisation sink: {d:.4}\n", .{gsink});
|
||||
try std.testing.expect(gsink != 0);
|
||||
}
|
||||
|
||||
fn bench_vsNative(writer: *std.Io.Writer) !void {
|
||||
const ITERS: usize = 100_000;
|
||||
const SAMPLES: usize = 5;
|
||||
|
||||
// Helper to safely get a value of type T from a loop index
|
||||
const getValT = struct {
|
||||
fn f(comptime TT: type, i: usize) TT {
|
||||
const v = (i % 100) + 1;
|
||||
return if (comptime @typeInfo(TT) == .float) @floatFromInt(v) else @intCast(v);
|
||||
}
|
||||
}.f;
|
||||
|
||||
const Types = .{ i32, i64, i128, f32, f64 };
|
||||
const TNames = .{ "i32", "i64", "i128", "f32", "f64" };
|
||||
const Ops = .{ "add", "mulBy", "divBy" };
|
||||
|
||||
var gsink: f64 = 0;
|
||||
|
||||
try writer.print(
|
||||
\\
|
||||
\\ Scalar vs Native Overhead Analysis
|
||||
\\
|
||||
\\┌───────────┬──────┬───────────┬───────────┬───────────┐
|
||||
\\│ Operation │ Type │ Native │ Scalar │ Slowdown │
|
||||
\\├───────────┼──────┼───────────┼───────────┼───────────┤
|
||||
\\
|
||||
, .{});
|
||||
|
||||
inline for (Ops, 0..) |op_name, j| {
|
||||
inline for (Types, 0..) |T, tidx| {
|
||||
var native_total_ns: f64 = 0;
|
||||
var quantity_total_ns: f64 = 0;
|
||||
|
||||
const M = Scalar(T, .init(.{ .L = 1 }), .init(.{}));
|
||||
const S = Scalar(T, .init(.{ .T = 1 }), .init(.{}));
|
||||
|
||||
for (0..SAMPLES) |_| {
|
||||
// --- 1. Benchmark Native ---
|
||||
var n_sink: T = 0;
|
||||
const n_start = getTime();
|
||||
for (0..ITERS) |i| {
|
||||
const a = getValT(T, i);
|
||||
const b = getValT(T, 2);
|
||||
const r = if (comptime std.mem.eql(u8, op_name, "add"))
|
||||
a + b
|
||||
else if (comptime std.mem.eql(u8, op_name, "mulBy"))
|
||||
a * b
|
||||
else if (comptime @typeInfo(T) == .int) @divTrunc(a, b) else a / b;
|
||||
|
||||
if (comptime @typeInfo(T) == .float) n_sink += r else n_sink ^= r;
|
||||
}
|
||||
const n_end = getTime();
|
||||
native_total_ns += @as(f64, @floatFromInt(n_start.durationTo(n_end).toNanoseconds()));
|
||||
fold(T, &gsink, n_sink);
|
||||
|
||||
// --- 2. Benchmark Scalar ---
|
||||
var q_sink: T = 0;
|
||||
const q_start = getTime();
|
||||
for (0..ITERS) |i| {
|
||||
const qa = M{ .value = getValT(T, i) };
|
||||
const qb = if (comptime std.mem.eql(u8, op_name, "divBy")) S{ .value = getValT(T, 2) } else M{ .value = getValT(T, 2) };
|
||||
|
||||
const r = if (comptime std.mem.eql(u8, op_name, "add"))
|
||||
qa.add(qb)
|
||||
else if (comptime std.mem.eql(u8, op_name, "mulBy"))
|
||||
qa.mulBy(qb)
|
||||
else
|
||||
qa.divBy(qb);
|
||||
|
||||
if (comptime @typeInfo(T) == .float) q_sink += r.value else q_sink ^= r.value;
|
||||
}
|
||||
const q_end = getTime();
|
||||
quantity_total_ns += @as(f64, @floatFromInt(q_start.durationTo(q_end).toNanoseconds()));
|
||||
fold(T, &gsink, q_sink);
|
||||
}
|
||||
|
||||
const avg_n = (native_total_ns / SAMPLES) / @as(f64, @floatFromInt(ITERS));
|
||||
const avg_q = (quantity_total_ns / SAMPLES) / @as(f64, @floatFromInt(ITERS));
|
||||
const slowdown = avg_q / avg_n;
|
||||
|
||||
try writer.print("│ {s:<9} │ {s:<4} │ {d:>7.2}ns │ {d:>7.2}ns │ {d:>8.2}x │\n", .{
|
||||
op_name, TNames[tidx], avg_n, avg_q, slowdown,
|
||||
});
|
||||
}
|
||||
if (j != Ops.len - 1) try writer.print("├───────────┼──────┼───────────┼───────────┼───────────┤\n", .{});
|
||||
}
|
||||
|
||||
try writer.print("└───────────┴──────┴───────────┴───────────┴───────────┘\n", .{});
|
||||
try writer.print("\nAnti-optimisation sink: {d:.4}\n", .{gsink});
|
||||
try std.testing.expect(gsink != 0);
|
||||
}
|
||||
|
||||
fn bench_crossTypeVsNative(writer: *std.Io.Writer) !void {
|
||||
const ITERS: usize = 100_000;
|
||||
const SAMPLES: usize = 5;
|
||||
|
||||
const getValT = struct {
|
||||
fn f(comptime TT: type, i: usize) TT {
|
||||
// Keep values safe and non-zero to avoid division by zero or overflows during cross-casting
|
||||
const v = (i % 50) + 1;
|
||||
return if (comptime @typeInfo(TT) == .float) @floatFromInt(v) else @intCast(v);
|
||||
}
|
||||
}.f;
|
||||
|
||||
// Helper for the Native baseline: explicitly casting T2 to T1 before the operation
|
||||
const castTo = struct {
|
||||
fn f(comptime DestT: type, comptime SrcT: type, val: SrcT) DestT {
|
||||
if (comptime DestT == SrcT) return val;
|
||||
const src_info = @typeInfo(SrcT);
|
||||
const dest_info = @typeInfo(DestT);
|
||||
|
||||
if (dest_info == .int and src_info == .int) return @intCast(val);
|
||||
if (dest_info == .float and src_info == .int) return @floatFromInt(val);
|
||||
if (dest_info == .int and src_info == .float) return @intFromFloat(val);
|
||||
if (dest_info == .float and src_info == .float) return @floatCast(val);
|
||||
unreachable;
|
||||
}
|
||||
}.f;
|
||||
|
||||
const Types = .{ i16, i64, i128, f32, f64 };
|
||||
const TNames = .{ "i16", "i64", "i128", "f32", "f64" };
|
||||
const Ops = .{ "add", "mulBy", "divBy" };
|
||||
|
||||
var gsink: f64 = 0;
|
||||
|
||||
try writer.print(
|
||||
\\
|
||||
\\ Cross-Type Overhead Analysis: Scalar vs Native
|
||||
\\
|
||||
\\┌─────────┬──────┬──────┬───────────┬───────────┬───────────┐
|
||||
\\│ Op │ T1 │ T2 │ Native │ Scalar │ Slowdown │
|
||||
\\├─────────┼──────┼──────┼───────────┼───────────┼───────────┤
|
||||
\\
|
||||
, .{});
|
||||
|
||||
inline for (Ops, 0..) |op_name, j| {
|
||||
inline for (Types, 0..) |T1, t1_idx| {
|
||||
inline for (Types, 0..) |T2, t2_idx| {
|
||||
var native_total_ns: f64 = 0;
|
||||
var quantity_total_ns: f64 = 0;
|
||||
|
||||
const M1 = Scalar(T1, .init(.{ .L = 1 }), .init(.{}));
|
||||
const M2 = Scalar(T2, .init(.{ .L = 1 }), .init(.{}));
|
||||
const S2 = Scalar(T2, .init(.{ .T = 1 }), .init(.{}));
|
||||
|
||||
for (0..SAMPLES) |_| {
|
||||
// --- 1. Benchmark Native (Cast T2 to T1, then math) ---
|
||||
var n_sink: T1 = 0;
|
||||
const n_start = getTime();
|
||||
for (0..ITERS) |i| {
|
||||
const a = getValT(T1, i);
|
||||
const b_raw = getValT(T2, 2);
|
||||
const b = castTo(T1, T2, b_raw);
|
||||
|
||||
const r = if (comptime std.mem.eql(u8, op_name, "add"))
|
||||
a + b
|
||||
else if (comptime std.mem.eql(u8, op_name, "mulBy"))
|
||||
a * b
|
||||
else if (comptime @typeInfo(T1) == .int)
|
||||
@divTrunc(a, b)
|
||||
else
|
||||
a / b;
|
||||
|
||||
if (comptime @typeInfo(T1) == .float) n_sink += r else n_sink ^= r;
|
||||
}
|
||||
const n_end = getTime();
|
||||
native_total_ns += @as(f64, @floatFromInt(n_start.durationTo(n_end).toNanoseconds()));
|
||||
fold(T1, &gsink, n_sink);
|
||||
|
||||
// --- 2. Benchmark Scalar ---
|
||||
var q_sink: T1 = 0;
|
||||
const q_start = getTime();
|
||||
for (0..ITERS) |i| {
|
||||
const qa = M1{ .value = getValT(T1, i) };
|
||||
const qb = if (comptime std.mem.eql(u8, op_name, "divBy"))
|
||||
S2{ .value = getValT(T2, 2) }
|
||||
else
|
||||
M2{ .value = getValT(T2, 2) };
|
||||
|
||||
const r = if (comptime std.mem.eql(u8, op_name, "add"))
|
||||
qa.add(qb)
|
||||
else if (comptime std.mem.eql(u8, op_name, "mulBy"))
|
||||
qa.mulBy(qb)
|
||||
else
|
||||
qa.divBy(qb);
|
||||
|
||||
if (comptime @typeInfo(T1) == .float) q_sink += r.value else q_sink ^= r.value;
|
||||
}
|
||||
const q_end = getTime();
|
||||
quantity_total_ns += @as(f64, @floatFromInt(q_start.durationTo(q_end).toNanoseconds()));
|
||||
fold(T1, &gsink, q_sink);
|
||||
}
|
||||
|
||||
const avg_n = (native_total_ns / SAMPLES) / @as(f64, @floatFromInt(ITERS));
|
||||
const avg_q = (quantity_total_ns / SAMPLES) / @as(f64, @floatFromInt(ITERS));
|
||||
const slowdown = avg_q / avg_n;
|
||||
|
||||
try writer.print("│ {s:<7} │ {s:<4} │ {s:<4} │ {d:>7.2}ns │ {d:>7.2}ns │ {d:>8.2}x │\n", .{
|
||||
op_name, TNames[t1_idx], TNames[t2_idx], avg_n, avg_q, slowdown,
|
||||
});
|
||||
}
|
||||
}
|
||||
if (j != Ops.len - 1) {
|
||||
try writer.print("├─────────┼──────┼──────┼───────────┼───────────┼───────────┤\n", .{});
|
||||
}
|
||||
}
|
||||
|
||||
try writer.print("└─────────┴──────┴──────┴───────────┴───────────┴───────────┘\n", .{});
|
||||
try writer.print("\nAnti-optimisation sink: {d:.4}\n", .{gsink});
|
||||
try std.testing.expect(gsink != 0);
|
||||
}
|
||||
|
||||
fn bench_Vector(writer: *std.Io.Writer) !void {
|
||||
const ITERS: usize = 10_000;
|
||||
const SAMPLES: usize = 10;
|
||||
var gsink: f64 = 0;
|
||||
|
||||
const getVal = struct {
|
||||
fn f(comptime TT: type, i: usize, comptime mask: u7) TT {
|
||||
const v: u8 = @as(u8, @truncate(i & @as(usize, mask))) + 1;
|
||||
return if (comptime @typeInfo(TT) == .float) @floatFromInt(v) else @intCast(v);
|
||||
}
|
||||
}.f;
|
||||
|
||||
const computeStats = struct {
|
||||
fn f(samples: []f64, iters: usize) f64 {
|
||||
std.mem.sort(f64, samples, {}, std.sort.asc(f64));
|
||||
const mid = samples.len / 2;
|
||||
const median_ns = if (samples.len % 2 == 0)
|
||||
(samples[mid - 1] + samples[mid]) / 2.0
|
||||
else
|
||||
samples[mid];
|
||||
return median_ns / @as(f64, @floatFromInt(iters));
|
||||
}
|
||||
}.f;
|
||||
|
||||
try writer.print(
|
||||
\\
|
||||
\\ Vector<N, T> benchmark — {d} iterations, {d} samples/cell
|
||||
\\ (Results in ns/op)
|
||||
\\
|
||||
\\┌─────────────┬──────┬─────────┬─────────┬─────────┐
|
||||
\\│ Operation │ Type │ Len=3 │ Len=4 │ Len=16 │
|
||||
\\├─────────────┼──────┼─────────┼─────────┼─────────┤
|
||||
\\
|
||||
, .{ ITERS, SAMPLES });
|
||||
|
||||
const Types = .{ i32, i64, i128, f32, f64 };
|
||||
const TNames = .{ "i32", "i64", "i128", "f32", "f64" };
|
||||
const Lengths = .{ 3, 4, 16 };
|
||||
const Ops = .{ "add", "scale", "mulByScalar", "length" };
|
||||
|
||||
inline for (Ops, 0..) |op_name, o_idx| {
|
||||
inline for (Types, TNames) |T, tname| {
|
||||
try writer.print("│ {s:<11} │ {s:<4} │", .{ op_name, tname });
|
||||
|
||||
inline for (Lengths) |len| {
|
||||
const Q_base = Scalar(T, .init(.{ .L = 1 }), .init(.{}));
|
||||
const Q_time = Scalar(T, .init(.{ .T = 1 }), .init(.{}));
|
||||
const V = Vector(len, Q_base);
|
||||
|
||||
var samples: [SAMPLES]f64 = undefined;
|
||||
|
||||
for (0..SAMPLES) |s_idx| {
|
||||
var sink: T = 0;
|
||||
|
||||
const t_start = getTime();
|
||||
for (0..ITERS) |i| {
|
||||
const v1 = V.initDefault(getVal(T, i, 63));
|
||||
|
||||
if (comptime std.mem.eql(u8, op_name, "add")) {
|
||||
const v2 = V.initDefault(getVal(T, i +% 7, 63));
|
||||
const res = v1.add(v2);
|
||||
for (res.data) |val| {
|
||||
if (comptime @typeInfo(T) == .float) sink += val else sink ^= val;
|
||||
}
|
||||
} else if (comptime std.mem.eql(u8, op_name, "scale")) {
|
||||
const sc = getVal(T, i +% 2, 63);
|
||||
const res = v1.scale(sc);
|
||||
for (res.data) |val| {
|
||||
if (comptime @typeInfo(T) == .float) sink += val else sink ^= val;
|
||||
}
|
||||
} else if (comptime std.mem.eql(u8, op_name, "mulByScalar")) {
|
||||
const s_val = Q_time{ .value = getVal(T, i +% 2, 63) };
|
||||
const res = v1.mulByScalar(s_val);
|
||||
for (res.data) |val| {
|
||||
if (comptime @typeInfo(T) == .float) sink += val else sink ^= val;
|
||||
}
|
||||
} else if (comptime std.mem.eql(u8, op_name, "length")) {
|
||||
const r = v1.length();
|
||||
if (comptime @typeInfo(T) == .float) sink += r else sink ^= r;
|
||||
}
|
||||
}
|
||||
const t_end = getTime();
|
||||
|
||||
samples[s_idx] = @as(f64, @floatFromInt(t_start.durationTo(t_end).toNanoseconds()));
|
||||
fold(T, &gsink, sink);
|
||||
}
|
||||
|
||||
const median_ns_per_op = computeStats(&samples, ITERS);
|
||||
try writer.print(" {d:>7.1} │", .{median_ns_per_op});
|
||||
}
|
||||
try writer.print("\n", .{});
|
||||
}
|
||||
|
||||
if (o_idx < Ops.len - 1) {
|
||||
try writer.print("├─────────────┼──────┼─────────┼─────────┼─────────┤\n", .{});
|
||||
}
|
||||
}
|
||||
try writer.print("└─────────────┴──────┴─────────┴─────────┴─────────┘\n", .{});
|
||||
try writer.print("\nAnti-optimisation sink: {d:.4}\n", .{gsink});
|
||||
try std.testing.expect(gsink != 0);
|
||||
}
|
||||
Loading…
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Reference in New Issue
Block a user