tvl-depot/absl/random/internal/nanobenchmark.cc
Abseil Team a4b757b5d4 Export of internal Abseil changes
--
693f81830b9f9cc8b24a1f38492b8dfcdd1d0e24 by Abseil Team <absl-team@google.com>:

Check that absl::int128 works as a std::chrono::duration::rep.

In particular, validate that ...
  std::chrono::time_point<std::chrono::system_clock,
                          std::chrono::duration<absl::int128,
                                                std::atto>>
is a superset (range and resolution) of absl::Time.

PiperOrigin-RevId: 283370280

--
df6073b686bd44223c6f9070fcceec918c728871 by Gennadiy Rozental <rogeeff@google.com>:

Changes thread annotations to use DataGuard() function instead of a specific Mutex.
Remove unused declaration of InvokeCallback.

PiperOrigin-RevId: 283361188

--
b49eb2dd2ee1a0b4c8a7bb1a94e368b81ce5f861 by Abseil Team <absl-team@google.com>:

Rewrite GetNominalCPUFrequency to use advapi32 instead of shlwapi

Using shlwapi.dll means that gdi32.dll is loaded which then makes process destruction more expensive, which is unacceptable for some uses. There may be other places that pull in gdi32.dll - this just fixes the one.

PiperOrigin-RevId: 282960698

--
b5508afec5099a0fdbb55e39a7cd2993259ed860 by Abseil Team <absl-team@google.com>:

Small typo fix in comments: initiazliation -> initialization

PiperOrigin-RevId: 282891800

--
4319cc419584e91ee74f6ae1a32d88a412fc5c01 by Abseil Team <absl-team@google.com>:

Update c_find_first_of() comment to remove the mention of an ordered container.

PiperOrigin-RevId: 282836540

--
5fcabc0a834dff39a505d5a5fc5403ddeb96028e by Derek Mauro <dmauro@google.com>:

Fix NaCl build, where format checking is broken

PiperOrigin-RevId: 282826202

--
aaf9ad3274c056a2f68e9b8ccada45c9802e2f1e by Derek Mauro <dmauro@google.com>:

Fix more -Wundef warnings

PiperOrigin-RevId: 282799820

--
1fb06150a70ffe98bf4b2d42b2a39d083bf44f8c by Derek Mauro <dmauro@google.com>:

Release support for additional platforms

PiperOrigin-RevId: 282793384

--
fa947fc28624a316fa872d7045b3838b88a0d69b by Derek Mauro <dmauro@google.com>:

Cleanup inconsistent usage of __has_attribute

PiperOrigin-RevId: 282793296

--
990030ad282263d6303c83b780a55fdec8e90d43 by Gennadiy Rozental <rogeeff@google.com>:

Eliminate the pointer in absl::Flag, which points to n space where we were storing flag's default value. We also eliminate additional (now unnecessary) allocation for flag's default value.
Instead we'll initialize the flags value directly from the value specified in ABSL_FLAG.
If the default value is updated via the call to SetCommandLineOptionWithMode we are replacing pointer to initialization routine to pointer to new default value.

PiperOrigin-RevId: 282637616
GitOrigin-RevId: 693f81830b9f9cc8b24a1f38492b8dfcdd1d0e24
Change-Id: I6f2edd8ef844de09aa2c182a7ca3133a22364792
2019-12-02 15:53:43 -05:00

802 lines
27 KiB
C++

// Copyright 2017 Google Inc. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/random/internal/nanobenchmark.h"
#include <sys/types.h>
#include <algorithm> // sort
#include <atomic>
#include <cstddef>
#include <cstdint>
#include <cstdlib>
#include <cstring> // memcpy
#include <limits>
#include <string>
#include <utility>
#include <vector>
#include "absl/base/attributes.h"
#include "absl/base/internal/raw_logging.h"
#include "absl/random/internal/platform.h"
#include "absl/random/internal/randen_engine.h"
// OS
#if defined(_WIN32) || defined(_WIN64)
#define ABSL_OS_WIN
#include <windows.h> // NOLINT
#elif defined(__ANDROID__)
#define ABSL_OS_ANDROID
#elif defined(__linux__)
#define ABSL_OS_LINUX
#include <sched.h> // NOLINT
#include <sys/syscall.h> // NOLINT
#endif
#if defined(ABSL_ARCH_X86_64) && !defined(ABSL_OS_WIN)
#include <cpuid.h> // NOLINT
#endif
// __ppc_get_timebase_freq
#if defined(ABSL_ARCH_PPC)
#include <sys/platform/ppc.h> // NOLINT
#endif
// clock_gettime
#if defined(ABSL_ARCH_ARM) || defined(ABSL_ARCH_AARCH64)
#include <time.h> // NOLINT
#endif
// ABSL_RANDOM_INTERNAL_ATTRIBUTE_NEVER_INLINE prevents inlining of the method.
#if ABSL_HAVE_ATTRIBUTE(noinline) || (defined(__GNUC__) && !defined(__clang__))
#define ABSL_RANDOM_INTERNAL_ATTRIBUTE_NEVER_INLINE __attribute__((noinline))
#elif defined(_MSC_VER)
#define ABSL_RANDOM_INTERNAL_ATTRIBUTE_NEVER_INLINE __declspec(noinline)
#else
#define ABSL_RANDOM_INTERNAL_ATTRIBUTE_NEVER_INLINE
#endif
namespace absl {
namespace random_internal_nanobenchmark {
namespace {
// For code folding.
namespace platform {
#if defined(ABSL_ARCH_X86_64)
// TODO(janwas): Merge with the one in randen_hwaes.cc?
void Cpuid(const uint32_t level, const uint32_t count,
uint32_t* ABSL_RANDOM_INTERNAL_RESTRICT abcd) {
#if defined(ABSL_OS_WIN)
int regs[4];
__cpuidex(regs, level, count);
for (int i = 0; i < 4; ++i) {
abcd[i] = regs[i];
}
#else
uint32_t a, b, c, d;
__cpuid_count(level, count, a, b, c, d);
abcd[0] = a;
abcd[1] = b;
abcd[2] = c;
abcd[3] = d;
#endif
}
std::string BrandString() {
char brand_string[49];
uint32_t abcd[4];
// Check if brand std::string is supported (it is on all reasonable Intel/AMD)
Cpuid(0x80000000U, 0, abcd);
if (abcd[0] < 0x80000004U) {
return std::string();
}
for (int i = 0; i < 3; ++i) {
Cpuid(0x80000002U + i, 0, abcd);
memcpy(brand_string + i * 16, &abcd, sizeof(abcd));
}
brand_string[48] = 0;
return brand_string;
}
// Returns the frequency quoted inside the brand string. This does not
// account for throttling nor Turbo Boost.
double NominalClockRate() {
const std::string& brand_string = BrandString();
// Brand strings include the maximum configured frequency. These prefixes are
// defined by Intel CPUID documentation.
const char* prefixes[3] = {"MHz", "GHz", "THz"};
const double multipliers[3] = {1E6, 1E9, 1E12};
for (size_t i = 0; i < 3; ++i) {
const size_t pos_prefix = brand_string.find(prefixes[i]);
if (pos_prefix != std::string::npos) {
const size_t pos_space = brand_string.rfind(' ', pos_prefix - 1);
if (pos_space != std::string::npos) {
const std::string digits =
brand_string.substr(pos_space + 1, pos_prefix - pos_space - 1);
return std::stod(digits) * multipliers[i];
}
}
}
return 0.0;
}
#endif // ABSL_ARCH_X86_64
} // namespace platform
// Prevents the compiler from eliding the computations that led to "output".
template <class T>
inline void PreventElision(T&& output) {
#ifndef ABSL_OS_WIN
// Works by indicating to the compiler that "output" is being read and
// modified. The +r constraint avoids unnecessary writes to memory, but only
// works for built-in types (typically FuncOutput).
asm volatile("" : "+r"(output) : : "memory");
#else
// MSVC does not support inline assembly anymore (and never supported GCC's
// RTL constraints). Self-assignment with #pragma optimize("off") might be
// expected to prevent elision, but it does not with MSVC 2015. Type-punning
// with volatile pointers generates inefficient code on MSVC 2017.
static std::atomic<T> dummy(T{});
dummy.store(output, std::memory_order_relaxed);
#endif
}
namespace timer {
// Start/Stop return absolute timestamps and must be placed immediately before
// and after the region to measure. We provide separate Start/Stop functions
// because they use different fences.
//
// Background: RDTSC is not 'serializing'; earlier instructions may complete
// after it, and/or later instructions may complete before it. 'Fences' ensure
// regions' elapsed times are independent of such reordering. The only
// documented unprivileged serializing instruction is CPUID, which acts as a
// full fence (no reordering across it in either direction). Unfortunately
// the latency of CPUID varies wildly (perhaps made worse by not initializing
// its EAX input). Because it cannot reliably be deducted from the region's
// elapsed time, it must not be included in the region to measure (i.e.
// between the two RDTSC).
//
// The newer RDTSCP is sometimes described as serializing, but it actually
// only serves as a half-fence with release semantics. Although all
// instructions in the region will complete before the final timestamp is
// captured, subsequent instructions may leak into the region and increase the
// elapsed time. Inserting another fence after the final RDTSCP would prevent
// such reordering without affecting the measured region.
//
// Fortunately, such a fence exists. The LFENCE instruction is only documented
// to delay later loads until earlier loads are visible. However, Intel's
// reference manual says it acts as a full fence (waiting until all earlier
// instructions have completed, and delaying later instructions until it
// completes). AMD assigns the same behavior to MFENCE.
//
// We need a fence before the initial RDTSC to prevent earlier instructions
// from leaking into the region, and arguably another after RDTSC to avoid
// region instructions from completing before the timestamp is recorded.
// When surrounded by fences, the additional RDTSCP half-fence provides no
// benefit, so the initial timestamp can be recorded via RDTSC, which has
// lower overhead than RDTSCP because it does not read TSC_AUX. In summary,
// we define Start = LFENCE/RDTSC/LFENCE; Stop = RDTSCP/LFENCE.
//
// Using Start+Start leads to higher variance and overhead than Stop+Stop.
// However, Stop+Stop includes an LFENCE in the region measurements, which
// adds a delay dependent on earlier loads. The combination of Start+Stop
// is faster than Start+Start and more consistent than Stop+Stop because
// the first LFENCE already delayed subsequent loads before the measured
// region. This combination seems not to have been considered in prior work:
// http://akaros.cs.berkeley.edu/lxr/akaros/kern/arch/x86/rdtsc_test.c
//
// Note: performance counters can measure 'exact' instructions-retired or
// (unhalted) cycle counts. The RDPMC instruction is not serializing and also
// requires fences. Unfortunately, it is not accessible on all OSes and we
// prefer to avoid kernel-mode drivers. Performance counters are also affected
// by several under/over-count errata, so we use the TSC instead.
// Returns a 64-bit timestamp in unit of 'ticks'; to convert to seconds,
// divide by InvariantTicksPerSecond.
inline uint64_t Start64() {
uint64_t t;
#if defined(ABSL_ARCH_PPC)
asm volatile("mfspr %0, %1" : "=r"(t) : "i"(268));
#elif defined(ABSL_ARCH_X86_64)
#if defined(ABSL_OS_WIN)
_ReadWriteBarrier();
_mm_lfence();
_ReadWriteBarrier();
t = __rdtsc();
_ReadWriteBarrier();
_mm_lfence();
_ReadWriteBarrier();
#else
asm volatile(
"lfence\n\t"
"rdtsc\n\t"
"shl $32, %%rdx\n\t"
"or %%rdx, %0\n\t"
"lfence"
: "=a"(t)
:
// "memory" avoids reordering. rdx = TSC >> 32.
// "cc" = flags modified by SHL.
: "rdx", "memory", "cc");
#endif
#else
// Fall back to OS - unsure how to reliably query cntvct_el0 frequency.
timespec ts;
clock_gettime(CLOCK_REALTIME, &ts);
t = ts.tv_sec * 1000000000LL + ts.tv_nsec;
#endif
return t;
}
inline uint64_t Stop64() {
uint64_t t;
#if defined(ABSL_ARCH_X86_64)
#if defined(ABSL_OS_WIN)
_ReadWriteBarrier();
unsigned aux;
t = __rdtscp(&aux);
_ReadWriteBarrier();
_mm_lfence();
_ReadWriteBarrier();
#else
// Use inline asm because __rdtscp generates code to store TSC_AUX (ecx).
asm volatile(
"rdtscp\n\t"
"shl $32, %%rdx\n\t"
"or %%rdx, %0\n\t"
"lfence"
: "=a"(t)
:
// "memory" avoids reordering. rcx = TSC_AUX. rdx = TSC >> 32.
// "cc" = flags modified by SHL.
: "rcx", "rdx", "memory", "cc");
#endif
#else
t = Start64();
#endif
return t;
}
// Returns a 32-bit timestamp with about 4 cycles less overhead than
// Start64. Only suitable for measuring very short regions because the
// timestamp overflows about once a second.
inline uint32_t Start32() {
uint32_t t;
#if defined(ABSL_ARCH_X86_64)
#if defined(ABSL_OS_WIN)
_ReadWriteBarrier();
_mm_lfence();
_ReadWriteBarrier();
t = static_cast<uint32_t>(__rdtsc());
_ReadWriteBarrier();
_mm_lfence();
_ReadWriteBarrier();
#else
asm volatile(
"lfence\n\t"
"rdtsc\n\t"
"lfence"
: "=a"(t)
:
// "memory" avoids reordering. rdx = TSC >> 32.
: "rdx", "memory");
#endif
#else
t = static_cast<uint32_t>(Start64());
#endif
return t;
}
inline uint32_t Stop32() {
uint32_t t;
#if defined(ABSL_ARCH_X86_64)
#if defined(ABSL_OS_WIN)
_ReadWriteBarrier();
unsigned aux;
t = static_cast<uint32_t>(__rdtscp(&aux));
_ReadWriteBarrier();
_mm_lfence();
_ReadWriteBarrier();
#else
// Use inline asm because __rdtscp generates code to store TSC_AUX (ecx).
asm volatile(
"rdtscp\n\t"
"lfence"
: "=a"(t)
:
// "memory" avoids reordering. rcx = TSC_AUX. rdx = TSC >> 32.
: "rcx", "rdx", "memory");
#endif
#else
t = static_cast<uint32_t>(Stop64());
#endif
return t;
}
} // namespace timer
namespace robust_statistics {
// Sorts integral values in ascending order (e.g. for Mode). About 3x faster
// than std::sort for input distributions with very few unique values.
template <class T>
void CountingSort(T* values, size_t num_values) {
// Unique values and their frequency (similar to flat_map).
using Unique = std::pair<T, int>;
std::vector<Unique> unique;
for (size_t i = 0; i < num_values; ++i) {
const T value = values[i];
const auto pos =
std::find_if(unique.begin(), unique.end(),
[value](const Unique u) { return u.first == value; });
if (pos == unique.end()) {
unique.push_back(std::make_pair(value, 1));
} else {
++pos->second;
}
}
// Sort in ascending order of value (pair.first).
std::sort(unique.begin(), unique.end());
// Write that many copies of each unique value to the array.
T* ABSL_RANDOM_INTERNAL_RESTRICT p = values;
for (const auto& value_count : unique) {
std::fill(p, p + value_count.second, value_count.first);
p += value_count.second;
}
ABSL_RAW_CHECK(p == values + num_values, "Did not produce enough output");
}
// @return i in [idx_begin, idx_begin + half_count) that minimizes
// sorted[i + half_count] - sorted[i].
template <typename T>
size_t MinRange(const T* const ABSL_RANDOM_INTERNAL_RESTRICT sorted,
const size_t idx_begin, const size_t half_count) {
T min_range = (std::numeric_limits<T>::max)();
size_t min_idx = 0;
for (size_t idx = idx_begin; idx < idx_begin + half_count; ++idx) {
ABSL_RAW_CHECK(sorted[idx] <= sorted[idx + half_count], "Not sorted");
const T range = sorted[idx + half_count] - sorted[idx];
if (range < min_range) {
min_range = range;
min_idx = idx;
}
}
return min_idx;
}
// Returns an estimate of the mode by calling MinRange on successively
// halved intervals. "sorted" must be in ascending order. This is the
// Half Sample Mode estimator proposed by Bickel in "On a fast, robust
// estimator of the mode", with complexity O(N log N). The mode is less
// affected by outliers in highly-skewed distributions than the median.
// The averaging operation below assumes "T" is an unsigned integer type.
template <typename T>
T ModeOfSorted(const T* const ABSL_RANDOM_INTERNAL_RESTRICT sorted,
const size_t num_values) {
size_t idx_begin = 0;
size_t half_count = num_values / 2;
while (half_count > 1) {
idx_begin = MinRange(sorted, idx_begin, half_count);
half_count >>= 1;
}
const T x = sorted[idx_begin + 0];
if (half_count == 0) {
return x;
}
ABSL_RAW_CHECK(half_count == 1, "Should stop at half_count=1");
const T average = (x + sorted[idx_begin + 1] + 1) / 2;
return average;
}
// Returns the mode. Side effect: sorts "values".
template <typename T>
T Mode(T* values, const size_t num_values) {
CountingSort(values, num_values);
return ModeOfSorted(values, num_values);
}
template <typename T, size_t N>
T Mode(T (&values)[N]) {
return Mode(&values[0], N);
}
// Returns the median value. Side effect: sorts "values".
template <typename T>
T Median(T* values, const size_t num_values) {
ABSL_RAW_CHECK(num_values != 0, "Empty input");
std::sort(values, values + num_values);
const size_t half = num_values / 2;
// Odd count: return middle
if (num_values % 2) {
return values[half];
}
// Even count: return average of middle two.
return (values[half] + values[half - 1] + 1) / 2;
}
// Returns a robust measure of variability.
template <typename T>
T MedianAbsoluteDeviation(const T* values, const size_t num_values,
const T median) {
ABSL_RAW_CHECK(num_values != 0, "Empty input");
std::vector<T> abs_deviations;
abs_deviations.reserve(num_values);
for (size_t i = 0; i < num_values; ++i) {
const int64_t abs = std::abs(int64_t(values[i]) - int64_t(median));
abs_deviations.push_back(static_cast<T>(abs));
}
return Median(abs_deviations.data(), num_values);
}
} // namespace robust_statistics
// Ticks := platform-specific timer values (CPU cycles on x86). Must be
// unsigned to guarantee wraparound on overflow. 32 bit timers are faster to
// read than 64 bit.
using Ticks = uint32_t;
// Returns timer overhead / minimum measurable difference.
Ticks TimerResolution() {
// Nested loop avoids exceeding stack/L1 capacity.
Ticks repetitions[Params::kTimerSamples];
for (size_t rep = 0; rep < Params::kTimerSamples; ++rep) {
Ticks samples[Params::kTimerSamples];
for (size_t i = 0; i < Params::kTimerSamples; ++i) {
const Ticks t0 = timer::Start32();
const Ticks t1 = timer::Stop32();
samples[i] = t1 - t0;
}
repetitions[rep] = robust_statistics::Mode(samples);
}
return robust_statistics::Mode(repetitions);
}
static const Ticks timer_resolution = TimerResolution();
// Estimates the expected value of "lambda" values with a variable number of
// samples until the variability "rel_mad" is less than "max_rel_mad".
template <class Lambda>
Ticks SampleUntilStable(const double max_rel_mad, double* rel_mad,
const Params& p, const Lambda& lambda) {
auto measure_duration = [&lambda]() -> Ticks {
const Ticks t0 = timer::Start32();
lambda();
const Ticks t1 = timer::Stop32();
return t1 - t0;
};
// Choose initial samples_per_eval based on a single estimated duration.
Ticks est = measure_duration();
static const double ticks_per_second = InvariantTicksPerSecond();
const size_t ticks_per_eval = ticks_per_second * p.seconds_per_eval;
size_t samples_per_eval = ticks_per_eval / est;
samples_per_eval = (std::max)(samples_per_eval, p.min_samples_per_eval);
std::vector<Ticks> samples;
samples.reserve(1 + samples_per_eval);
samples.push_back(est);
// Percentage is too strict for tiny differences, so also allow a small
// absolute "median absolute deviation".
const Ticks max_abs_mad = (timer_resolution + 99) / 100;
*rel_mad = 0.0; // ensure initialized
for (size_t eval = 0; eval < p.max_evals; ++eval, samples_per_eval *= 2) {
samples.reserve(samples.size() + samples_per_eval);
for (size_t i = 0; i < samples_per_eval; ++i) {
const Ticks r = measure_duration();
samples.push_back(r);
}
if (samples.size() >= p.min_mode_samples) {
est = robust_statistics::Mode(samples.data(), samples.size());
} else {
// For "few" (depends also on the variance) samples, Median is safer.
est = robust_statistics::Median(samples.data(), samples.size());
}
ABSL_RAW_CHECK(est != 0, "Estimator returned zero duration");
// Median absolute deviation (mad) is a robust measure of 'variability'.
const Ticks abs_mad = robust_statistics::MedianAbsoluteDeviation(
samples.data(), samples.size(), est);
*rel_mad = static_cast<double>(static_cast<int>(abs_mad)) / est;
if (*rel_mad <= max_rel_mad || abs_mad <= max_abs_mad) {
if (p.verbose) {
ABSL_RAW_LOG(INFO,
"%6zu samples => %5u (abs_mad=%4u, rel_mad=%4.2f%%)\n",
samples.size(), est, abs_mad, *rel_mad * 100.0);
}
return est;
}
}
if (p.verbose) {
ABSL_RAW_LOG(WARNING,
"rel_mad=%4.2f%% still exceeds %4.2f%% after %6zu samples.\n",
*rel_mad * 100.0, max_rel_mad * 100.0, samples.size());
}
return est;
}
using InputVec = std::vector<FuncInput>;
// Returns vector of unique input values.
InputVec UniqueInputs(const FuncInput* inputs, const size_t num_inputs) {
InputVec unique(inputs, inputs + num_inputs);
std::sort(unique.begin(), unique.end());
unique.erase(std::unique(unique.begin(), unique.end()), unique.end());
return unique;
}
// Returns how often we need to call func for sufficient precision, or zero
// on failure (e.g. the elapsed time is too long for a 32-bit tick count).
size_t NumSkip(const Func func, const void* arg, const InputVec& unique,
const Params& p) {
// Min elapsed ticks for any input.
Ticks min_duration = ~0u;
for (const FuncInput input : unique) {
// Make sure a 32-bit timer is sufficient.
const uint64_t t0 = timer::Start64();
PreventElision(func(arg, input));
const uint64_t t1 = timer::Stop64();
const uint64_t elapsed = t1 - t0;
if (elapsed >= (1ULL << 30)) {
ABSL_RAW_LOG(WARNING,
"Measurement failed: need 64-bit timer for input=%zu\n",
static_cast<size_t>(input));
return 0;
}
double rel_mad;
const Ticks total = SampleUntilStable(
p.target_rel_mad, &rel_mad, p,
[func, arg, input]() { PreventElision(func(arg, input)); });
min_duration = (std::min)(min_duration, total - timer_resolution);
}
// Number of repetitions required to reach the target resolution.
const size_t max_skip = p.precision_divisor;
// Number of repetitions given the estimated duration.
const size_t num_skip =
min_duration == 0 ? 0 : (max_skip + min_duration - 1) / min_duration;
if (p.verbose) {
ABSL_RAW_LOG(INFO, "res=%u max_skip=%zu min_dur=%u num_skip=%zu\n",
timer_resolution, max_skip, min_duration, num_skip);
}
return num_skip;
}
// Replicates inputs until we can omit "num_skip" occurrences of an input.
InputVec ReplicateInputs(const FuncInput* inputs, const size_t num_inputs,
const size_t num_unique, const size_t num_skip,
const Params& p) {
InputVec full;
if (num_unique == 1) {
full.assign(p.subset_ratio * num_skip, inputs[0]);
return full;
}
full.reserve(p.subset_ratio * num_skip * num_inputs);
for (size_t i = 0; i < p.subset_ratio * num_skip; ++i) {
full.insert(full.end(), inputs, inputs + num_inputs);
}
absl::random_internal::randen_engine<uint32_t> rng;
std::shuffle(full.begin(), full.end(), rng);
return full;
}
// Copies the "full" to "subset" in the same order, but with "num_skip"
// randomly selected occurrences of "input_to_skip" removed.
void FillSubset(const InputVec& full, const FuncInput input_to_skip,
const size_t num_skip, InputVec* subset) {
const size_t count = std::count(full.begin(), full.end(), input_to_skip);
// Generate num_skip random indices: which occurrence to skip.
std::vector<uint32_t> omit;
// Replacement for std::iota, not yet available in MSVC builds.
omit.reserve(count);
for (size_t i = 0; i < count; ++i) {
omit.push_back(i);
}
// omit[] is the same on every call, but that's OK because they identify the
// Nth instance of input_to_skip, so the position within full[] differs.
absl::random_internal::randen_engine<uint32_t> rng;
std::shuffle(omit.begin(), omit.end(), rng);
omit.resize(num_skip);
std::sort(omit.begin(), omit.end());
uint32_t occurrence = ~0u; // 0 after preincrement
size_t idx_omit = 0; // cursor within omit[]
size_t idx_subset = 0; // cursor within *subset
for (const FuncInput next : full) {
if (next == input_to_skip) {
++occurrence;
// Haven't removed enough already
if (idx_omit < num_skip) {
// This one is up for removal
if (occurrence == omit[idx_omit]) {
++idx_omit;
continue;
}
}
}
if (idx_subset < subset->size()) {
(*subset)[idx_subset++] = next;
}
}
ABSL_RAW_CHECK(idx_subset == subset->size(), "idx_subset not at end");
ABSL_RAW_CHECK(idx_omit == omit.size(), "idx_omit not at end");
ABSL_RAW_CHECK(occurrence == count - 1, "occurrence not at end");
}
// Returns total ticks elapsed for all inputs.
Ticks TotalDuration(const Func func, const void* arg, const InputVec* inputs,
const Params& p, double* max_rel_mad) {
double rel_mad;
const Ticks duration =
SampleUntilStable(p.target_rel_mad, &rel_mad, p, [func, arg, inputs]() {
for (const FuncInput input : *inputs) {
PreventElision(func(arg, input));
}
});
*max_rel_mad = (std::max)(*max_rel_mad, rel_mad);
return duration;
}
// (Nearly) empty Func for measuring timer overhead/resolution.
ABSL_RANDOM_INTERNAL_ATTRIBUTE_NEVER_INLINE FuncOutput
EmptyFunc(const void* arg, const FuncInput input) {
return input;
}
// Returns overhead of accessing inputs[] and calling a function; this will
// be deducted from future TotalDuration return values.
Ticks Overhead(const void* arg, const InputVec* inputs, const Params& p) {
double rel_mad;
// Zero tolerance because repeatability is crucial and EmptyFunc is fast.
return SampleUntilStable(0.0, &rel_mad, p, [arg, inputs]() {
for (const FuncInput input : *inputs) {
PreventElision(EmptyFunc(arg, input));
}
});
}
} // namespace
void PinThreadToCPU(int cpu) {
// We might migrate to another CPU before pinning below, but at least cpu
// will be one of the CPUs on which this thread ran.
#if defined(ABSL_OS_WIN)
if (cpu < 0) {
cpu = static_cast<int>(GetCurrentProcessorNumber());
ABSL_RAW_CHECK(cpu >= 0, "PinThreadToCPU detect failed");
if (cpu >= 64) {
// NOTE: On wine, at least, GetCurrentProcessorNumber() sometimes returns
// a value > 64, which is out of range. When this happens, log a message
// and don't set a cpu affinity.
ABSL_RAW_LOG(ERROR, "Invalid CPU number: %d", cpu);
return;
}
} else if (cpu >= 64) {
// User specified an explicit CPU affinity > the valid range.
ABSL_RAW_LOG(FATAL, "Invalid CPU number: %d", cpu);
}
const DWORD_PTR prev = SetThreadAffinityMask(GetCurrentThread(), 1ULL << cpu);
ABSL_RAW_CHECK(prev != 0, "SetAffinity failed");
#elif defined(ABSL_OS_LINUX) && !defined(ABSL_OS_ANDROID)
if (cpu < 0) {
cpu = sched_getcpu();
ABSL_RAW_CHECK(cpu >= 0, "PinThreadToCPU detect failed");
}
const pid_t pid = 0; // current thread
cpu_set_t set;
CPU_ZERO(&set);
CPU_SET(cpu, &set);
const int err = sched_setaffinity(pid, sizeof(set), &set);
ABSL_RAW_CHECK(err == 0, "SetAffinity failed");
#endif
}
// Returns tick rate. Invariant means the tick counter frequency is independent
// of CPU throttling or sleep. May be expensive, caller should cache the result.
double InvariantTicksPerSecond() {
#if defined(ABSL_ARCH_PPC)
return __ppc_get_timebase_freq();
#elif defined(ABSL_ARCH_X86_64)
// We assume the TSC is invariant; it is on all recent Intel/AMD CPUs.
return platform::NominalClockRate();
#else
// Fall back to clock_gettime nanoseconds.
return 1E9;
#endif
}
size_t MeasureImpl(const Func func, const void* arg, const size_t num_skip,
const InputVec& unique, const InputVec& full,
const Params& p, Result* results) {
const float mul = 1.0f / static_cast<int>(num_skip);
InputVec subset(full.size() - num_skip);
const Ticks overhead = Overhead(arg, &full, p);
const Ticks overhead_skip = Overhead(arg, &subset, p);
if (overhead < overhead_skip) {
ABSL_RAW_LOG(WARNING, "Measurement failed: overhead %u < %u\n", overhead,
overhead_skip);
return 0;
}
if (p.verbose) {
ABSL_RAW_LOG(INFO, "#inputs=%5zu,%5zu overhead=%5u,%5u\n", full.size(),
subset.size(), overhead, overhead_skip);
}
double max_rel_mad = 0.0;
const Ticks total = TotalDuration(func, arg, &full, p, &max_rel_mad);
for (size_t i = 0; i < unique.size(); ++i) {
FillSubset(full, unique[i], num_skip, &subset);
const Ticks total_skip = TotalDuration(func, arg, &subset, p, &max_rel_mad);
if (total < total_skip) {
ABSL_RAW_LOG(WARNING, "Measurement failed: total %u < %u\n", total,
total_skip);
return 0;
}
const Ticks duration = (total - overhead) - (total_skip - overhead_skip);
results[i].input = unique[i];
results[i].ticks = duration * mul;
results[i].variability = max_rel_mad;
}
return unique.size();
}
size_t Measure(const Func func, const void* arg, const FuncInput* inputs,
const size_t num_inputs, Result* results, const Params& p) {
ABSL_RAW_CHECK(num_inputs != 0, "No inputs");
const InputVec unique = UniqueInputs(inputs, num_inputs);
const size_t num_skip = NumSkip(func, arg, unique, p); // never 0
if (num_skip == 0) return 0; // NumSkip already printed error message
const InputVec full =
ReplicateInputs(inputs, num_inputs, unique.size(), num_skip, p);
// MeasureImpl may fail up to p.max_measure_retries times.
for (size_t i = 0; i < p.max_measure_retries; i++) {
auto result = MeasureImpl(func, arg, num_skip, unique, full, p, results);
if (result != 0) {
return result;
}
}
// All retries failed. (Unusual)
return 0;
}
} // namespace random_internal_nanobenchmark
} // namespace absl