// 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/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
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_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
