#include "test/jemalloc_test.h" /******************************************************************************/ /* * General purpose tool for examining random number distributions. * * Input - * (a) a random number generator, and * (b) the buckets: * (1) number of buckets, * (2) width of each bucket, in log scale, * (3) expected mean and stddev of the count of random numbers in each * bucket, and * (c) number of iterations to invoke the generator. * * The program generates the specified amount of random numbers, and assess how * well they conform to the expectations: for each bucket, output - * (a) the (given) expected mean and stddev, * (b) the actual count and any interesting level of deviation: * (1) ~68% buckets should show no interesting deviation, meaning a * deviation less than stddev from the expectation; * (2) ~27% buckets should show '+' / '-', meaning a deviation in the range * of [stddev, 2 * stddev) from the expectation; * (3) ~4% buckets should show '++' / '--', meaning a deviation in the * range of [2 * stddev, 3 * stddev) from the expectation; and * (4) less than 0.3% buckets should show more than two '+'s / '-'s. * * Technical remarks: * (a) The generator is expected to output uint64_t numbers, so you might need * to define a wrapper. * (b) The buckets must be of equal width and the lowest bucket starts at * [0, 2^lg_bucket_width - 1). * (c) Any generated number >= n_bucket * 2^lg_bucket_width will be counted * towards the last bucket; the expected mean and stddev provided should * also reflect that. * (d) The number of iterations is advised to be determined so that the bucket * with the minimal expected proportion gets a sufficient count. */ static void fill(size_t a[], const size_t n, const size_t k) { for (size_t i = 0; i < n; ++i) { a[i] = k; } } static void collect_buckets(uint64_t (*gen)(void *), void *opaque, size_t buckets[], const size_t n_bucket, const size_t lg_bucket_width, const size_t n_iter) { for (size_t i = 0; i < n_iter; ++i) { uint64_t num = gen(opaque); uint64_t bucket_id = num >> lg_bucket_width; if (bucket_id >= n_bucket) { bucket_id = n_bucket - 1; } ++buckets[bucket_id]; } } static void print_buckets(const size_t buckets[], const size_t means[], const size_t stddevs[], const size_t n_bucket) { for (size_t i = 0; i < n_bucket; ++i) { malloc_printf("%zu:\tmean = %zu,\tstddev = %zu,\tbucket = %zu", i, means[i], stddevs[i], buckets[i]); /* Make sure there's no overflow. */ assert(buckets[i] + stddevs[i] >= stddevs[i]); assert(means[i] + stddevs[i] >= stddevs[i]); if (buckets[i] + stddevs[i] <= means[i]) { malloc_write(" "); for (size_t t = means[i] - buckets[i]; t >= stddevs[i]; t -= stddevs[i]) { malloc_write("-"); } } else if (buckets[i] >= means[i] + stddevs[i]) { malloc_write(" "); for (size_t t = buckets[i] - means[i]; t >= stddevs[i]; t -= stddevs[i]) { malloc_write("+"); } } malloc_write("\n"); } } static void bucket_analysis(uint64_t (*gen)(void *), void *opaque, size_t buckets[], const size_t means[], const size_t stddevs[], const size_t n_bucket, const size_t lg_bucket_width, const size_t n_iter) { for (size_t i = 1; i <= 3; ++i) { malloc_printf("round %zu\n", i); fill(buckets, n_bucket, 0); collect_buckets(gen, opaque, buckets, n_bucket, lg_bucket_width, n_iter); print_buckets(buckets, means, stddevs, n_bucket); } } /* (Recommended) minimal bucket mean. */ #define MIN_BUCKET_MEAN 10000 /******************************************************************************/ /* Uniform random number generator. */ typedef struct uniform_gen_arg_s uniform_gen_arg_t; struct uniform_gen_arg_s { uint64_t state; const unsigned lg_range; }; static uint64_t uniform_gen(void *opaque) { uniform_gen_arg_t *arg = (uniform_gen_arg_t *)opaque; return prng_lg_range_u64(&arg->state, arg->lg_range); } TEST_BEGIN(test_uniform) { #define LG_N_BUCKET 5 #define N_BUCKET (1 << LG_N_BUCKET) #define QUOTIENT_CEIL(n, d) (((n) - 1) / (d) + 1) const unsigned lg_range_test = 25; /* * Mathematical tricks to guarantee that both mean and stddev are * integers, and that the minimal bucket mean is at least * MIN_BUCKET_MEAN. */ const size_t q = 1 << QUOTIENT_CEIL(LG_CEIL(QUOTIENT_CEIL( MIN_BUCKET_MEAN, N_BUCKET * (N_BUCKET - 1))), 2); const size_t stddev = (N_BUCKET - 1) * q; const size_t mean = N_BUCKET * stddev * q; const size_t n_iter = N_BUCKET * mean; size_t means[N_BUCKET]; fill(means, N_BUCKET, mean); size_t stddevs[N_BUCKET]; fill(stddevs, N_BUCKET, stddev); uniform_gen_arg_t arg = {(uint64_t)(uintptr_t)&lg_range_test, lg_range_test}; size_t buckets[N_BUCKET]; assert_zu_ge(lg_range_test, LG_N_BUCKET, ""); const size_t lg_bucket_width = lg_range_test - LG_N_BUCKET; bucket_analysis(uniform_gen, &arg, buckets, means, stddevs, N_BUCKET, lg_bucket_width, n_iter); #undef LG_N_BUCKET #undef N_BUCKET #undef QUOTIENT_CEIL } TEST_END /******************************************************************************/ /* Geometric random number generator; compiled only when prof is on. */ #ifdef JEMALLOC_PROF /* * Fills geometric proportions and returns the minimal proportion. See * comments in test_prof_sample for explanations for n_divide. */ static double fill_geometric_proportions(double proportions[], const size_t n_bucket, const size_t n_divide) { assert(n_bucket > 0); assert(n_divide > 0); double x = 1.; for (size_t i = 0; i < n_bucket; ++i) { if (i == n_bucket - 1) { proportions[i] = x; } else { double y = x * exp(-1. / n_divide); proportions[i] = x - y; x = y; } } /* * The minimal proportion is the smaller one of the last two * proportions for geometric distribution. */ double min_proportion = proportions[n_bucket - 1]; if (n_bucket >= 2 && proportions[n_bucket - 2] < min_proportion) { min_proportion = proportions[n_bucket - 2]; } return min_proportion; } static size_t round_to_nearest(const double x) { return (size_t)(x + .5); } static void fill_references(size_t means[], size_t stddevs[], const double proportions[], const size_t n_bucket, const size_t n_iter) { for (size_t i = 0; i < n_bucket; ++i) { double x = n_iter * proportions[i]; means[i] = round_to_nearest(x); stddevs[i] = round_to_nearest(sqrt(x * (1. - proportions[i]))); } } static uint64_t prof_sample_gen(void *opaque) { return prof_sample_new_event_wait((tsd_t *)opaque) - 1; } #endif /* JEMALLOC_PROF */ TEST_BEGIN(test_prof_sample) { test_skip_if(!config_prof); #ifdef JEMALLOC_PROF /* Number of divisions within [0, mean). */ #define LG_N_DIVIDE 3 #define N_DIVIDE (1 << LG_N_DIVIDE) /* Coverage of buckets in terms of multiples of mean. */ #define LG_N_MULTIPLY 2 #define N_GEO_BUCKET (N_DIVIDE << LG_N_MULTIPLY) test_skip_if(!opt_prof); size_t lg_prof_sample_test = 25; size_t lg_prof_sample_orig = lg_prof_sample; assert_d_eq(mallctl("prof.reset", NULL, NULL, &lg_prof_sample_test, sizeof(size_t)), 0, ""); malloc_printf("lg_prof_sample = %zu\n", lg_prof_sample_test); double proportions[N_GEO_BUCKET + 1]; const double min_proportion = fill_geometric_proportions(proportions, N_GEO_BUCKET + 1, N_DIVIDE); const size_t n_iter = round_to_nearest(MIN_BUCKET_MEAN / min_proportion); size_t means[N_GEO_BUCKET + 1]; size_t stddevs[N_GEO_BUCKET + 1]; fill_references(means, stddevs, proportions, N_GEO_BUCKET + 1, n_iter); tsd_t *tsd = tsd_fetch(); assert_ptr_not_null(tsd, ""); size_t buckets[N_GEO_BUCKET + 1]; assert_zu_ge(lg_prof_sample, LG_N_DIVIDE, ""); const size_t lg_bucket_width = lg_prof_sample - LG_N_DIVIDE; bucket_analysis(prof_sample_gen, tsd, buckets, means, stddevs, N_GEO_BUCKET + 1, lg_bucket_width, n_iter); assert_d_eq(mallctl("prof.reset", NULL, NULL, &lg_prof_sample_orig, sizeof(size_t)), 0, ""); #undef LG_N_DIVIDE #undef N_DIVIDE #undef LG_N_MULTIPLY #undef N_GEO_BUCKET #endif /* JEMALLOC_PROF */ } TEST_END /******************************************************************************/ int main(void) { return test_no_reentrancy( test_uniform, test_prof_sample); }