| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | /* | ||
| 2 | * Copyright © 2025, Niklas Haas | ||
| 3 | * All rights reserved. | ||
| 4 | * | ||
| 5 | * Redistribution and use in source and binary forms, with or without | ||
| 6 | * modification, are permitted provided that the following conditions are met: | ||
| 7 | * | ||
| 8 | * 1. Redistributions of source code must retain the above copyright notice, this | ||
| 9 | * list of conditions and the following disclaimer. | ||
| 10 | * | ||
| 11 | * 2. Redistributions in binary form must reproduce the above copyright notice, | ||
| 12 | * this list of conditions and the following disclaimer in the documentation | ||
| 13 | * and/or other materials provided with the distribution. | ||
| 14 | * | ||
| 15 | * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND | ||
| 16 | * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | ||
| 17 | * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | ||
| 18 | * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR | ||
| 19 | * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | ||
| 20 | * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
| 21 | * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND | ||
| 22 | * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | ||
| 23 | * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | ||
| 24 | * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | ||
| 25 | */ | ||
| 26 | |||
| 27 | #ifndef CHECKASM_STATS_H | ||
| 28 | #define CHECKASM_STATS_H | ||
| 29 | |||
| 30 | #include <assert.h> | ||
| 31 | #include <math.h> | ||
| 32 | #include <stdint.h> | ||
| 33 | #include <string.h> | ||
| 34 | |||
| 35 | typedef struct CheckasmVar { | ||
| 36 | double lmean, lvar; /* log mean and variance */ | ||
| 37 | } CheckasmVar; | ||
| 38 | |||
| 39 | /* Sample the PDF of a random variable at the given quantile */ | ||
| 40 | ✗ | static inline double checkasm_sample(const CheckasmVar x, const double q) | |
| 41 | { | ||
| 42 | ✗ | return exp(x.lmean + q * sqrt(x.lvar)); | |
| 43 | } | ||
| 44 | |||
| 45 | ✗ | static inline double checkasm_median(const CheckasmVar x) | |
| 46 | { | ||
| 47 | ✗ | return exp(x.lmean); | |
| 48 | } | ||
| 49 | |||
| 50 | ✗ | static inline double checkasm_mode(const CheckasmVar x) | |
| 51 | { | ||
| 52 | ✗ | return exp(x.lmean - x.lvar); | |
| 53 | } | ||
| 54 | |||
| 55 | ✗ | static inline double checkasm_mean(const CheckasmVar x) | |
| 56 | { | ||
| 57 | ✗ | return exp(x.lmean + 0.5 * x.lvar); | |
| 58 | } | ||
| 59 | |||
| 60 | ✗ | static inline double checkasm_stddev(const CheckasmVar x) | |
| 61 | { | ||
| 62 | ✗ | return exp(x.lmean + 0.5 * x.lvar) * sqrt(exp(x.lvar) - 1.0); | |
| 63 | } | ||
| 64 | |||
| 65 | ✗ | static inline CheckasmVar checkasm_var_const(double x) | |
| 66 | { | ||
| 67 | ✗ | return (CheckasmVar) { log(x), 0.0 }; | |
| 68 | } | ||
| 69 | |||
| 70 | /* Assumes independent random variables */ | ||
| 71 | CheckasmVar checkasm_var_scale(CheckasmVar a, double s); | ||
| 72 | CheckasmVar checkasm_var_pow(CheckasmVar a, double exp); | ||
| 73 | CheckasmVar checkasm_var_add(CheckasmVar a, CheckasmVar b); /* approximation */ | ||
| 74 | CheckasmVar checkasm_var_sub(CheckasmVar a, CheckasmVar b); /* approximation */ | ||
| 75 | CheckasmVar checkasm_var_mul(CheckasmVar a, CheckasmVar b); | ||
| 76 | CheckasmVar checkasm_var_div(CheckasmVar a, CheckasmVar b); | ||
| 77 | CheckasmVar checkasm_var_inv(CheckasmVar a); | ||
| 78 | |||
| 79 | /* Statistical analysis helpers */ | ||
| 80 | typedef struct CheckasmSample { | ||
| 81 | uint64_t sum; /* batched sum of data points */ | ||
| 82 | int count; /* number of data points in batch */ | ||
| 83 | } CheckasmSample; | ||
| 84 | |||
| 85 | typedef struct CheckasmStats { | ||
| 86 | /* With a ~12% exponential growth on the number of data points per sample, | ||
| 87 | * 256 samples can effectively represent many billions of data points */ | ||
| 88 | #define CHECKASM_STATS_SAMPLES 256 | ||
| 89 | CheckasmSample samples[CHECKASM_STATS_SAMPLES]; | ||
| 90 | int nb_samples; | ||
| 91 | int next_count; | ||
| 92 | } CheckasmStats; | ||
| 93 | |||
| 94 | ✗ | static inline void checkasm_stats_reset(CheckasmStats *const stats) | |
| 95 | { | ||
| 96 | ✗ | stats->nb_samples = 0; | |
| 97 | ✗ | stats->next_count = 1; | |
| 98 | ✗ | } | |
| 99 | |||
| 100 | ✗ | static inline void checkasm_stats_add(CheckasmStats *const stats, const CheckasmSample s) | |
| 101 | { | ||
| 102 | ✗ | if (s.sum > 0 && s.count > 0) { | |
| 103 | ✗ | assert(stats->nb_samples < CHECKASM_STATS_SAMPLES); | |
| 104 | ✗ | stats->samples[stats->nb_samples++] = s; | |
| 105 | } | ||
| 106 | ✗ | } | |
| 107 | |||
| 108 | ✗ | static inline void checkasm_stats_count_grow(CheckasmStats *const stats, uint64_t cycles, | |
| 109 | uint64_t target_cycles) | ||
| 110 | { | ||
| 111 | ✗ | if (cycles < target_cycles >> 10) { /* sum[(1+1/64)^n | n < 200] */ | |
| 112 | /* Function is very fast, increase iteration count dramatically */ | ||
| 113 | ✗ | stats->next_count <<= 1; | |
| 114 | ✗ | } else if (stats->next_count < 1 << 25) { | |
| 115 | /* Grow more slowly at 1/64 = ~1.5% growth */ | ||
| 116 | ✗ | stats->next_count = ((stats->next_count << 6) + stats->next_count + 63) >> 6; | |
| 117 | } | ||
| 118 | ✗ | } | |
| 119 | |||
| 120 | CheckasmVar checkasm_stats_estimate(const CheckasmStats *stats); | ||
| 121 | |||
| 122 | typedef struct CheckasmMeasurement { | ||
| 123 | CheckasmVar product; | ||
| 124 | int nb_measurements; | ||
| 125 | CheckasmStats stats; /* last measurement run */ | ||
| 126 | } CheckasmMeasurement; | ||
| 127 | |||
| 128 | ✗ | static inline void checkasm_measurement_init(CheckasmMeasurement *measurement) | |
| 129 | { | ||
| 130 | ✗ | measurement->product = checkasm_var_const(1.0); | |
| 131 | ✗ | measurement->nb_measurements = 0; | |
| 132 | ✗ | measurement->stats.nb_samples = 0; | |
| 133 | ✗ | } | |
| 134 | |||
| 135 | ✗ | static inline void checkasm_measurement_update(CheckasmMeasurement *measurement, | |
| 136 | const CheckasmStats stats) | ||
| 137 | { | ||
| 138 | ✗ | const CheckasmVar est = checkasm_stats_estimate(&stats); | |
| 139 | ✗ | measurement->product = checkasm_var_mul(measurement->product, est); | |
| 140 | ✗ | measurement->nb_measurements++; | |
| 141 | ✗ | measurement->stats.nb_samples = stats.nb_samples; | |
| 142 | ✗ | memcpy(measurement->stats.samples, stats.samples, | |
| 143 | ✗ | sizeof(stats.samples[0]) * stats.nb_samples); | |
| 144 | ✗ | } | |
| 145 | |||
| 146 | static inline CheckasmVar | ||
| 147 | ✗ | checkasm_measurement_result(const CheckasmMeasurement measurement) | |
| 148 | { | ||
| 149 | ✗ | return checkasm_var_pow(measurement.product, 1.0 / measurement.nb_measurements); | |
| 150 | } | ||
| 151 | |||
| 152 | #endif /* CHECKASM_STATS_H */ | ||
| 153 |