diff options
author | Vincent Ambo <mail@tazj.in> | 2022-02-07T23·05+0300 |
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committer | clbot <clbot@tvl.fyi> | 2022-02-07T23·09+0000 |
commit | 5aa5d282eac56a21e74611c1cdbaa97bb5db2dca (patch) | |
tree | 8cc5dce8157a1470ff76719dd15d65f648a05522 /third_party/abseil_cpp/absl/random/internal/nanobenchmark.h | |
parent | a25675804c4f429fab5ee5201fe25e89865dfd13 (diff) |
chore(3p/abseil_cpp): unvendor abseil_cpp r/3786
we weren't actually using these sources anymore, okay? Change-Id: If701571d9716de308d3512e1eb22c35db0877a66 Reviewed-on: https://cl.tvl.fyi/c/depot/+/5248 Tested-by: BuildkiteCI Reviewed-by: grfn <grfn@gws.fyi> Autosubmit: tazjin <tazjin@tvl.su>
Diffstat (limited to 'third_party/abseil_cpp/absl/random/internal/nanobenchmark.h')
-rw-r--r-- | third_party/abseil_cpp/absl/random/internal/nanobenchmark.h | 172 |
1 files changed, 0 insertions, 172 deletions
diff --git a/third_party/abseil_cpp/absl/random/internal/nanobenchmark.h b/third_party/abseil_cpp/absl/random/internal/nanobenchmark.h deleted file mode 100644 index a5097ba27b0f..000000000000 --- a/third_party/abseil_cpp/absl/random/internal/nanobenchmark.h +++ /dev/null @@ -1,172 +0,0 @@ -// 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. - -#ifndef ABSL_RANDOM_INTERNAL_NANOBENCHMARK_H_ -#define ABSL_RANDOM_INTERNAL_NANOBENCHMARK_H_ - -// Benchmarks functions of a single integer argument with realistic branch -// prediction hit rates. Uses a robust estimator to summarize the measurements. -// The precision is about 0.2%. -// -// Examples: see nanobenchmark_test.cc. -// -// Background: Microbenchmarks such as http://github.com/google/benchmark -// can measure elapsed times on the order of a microsecond. Shorter functions -// are typically measured by repeating them thousands of times and dividing -// the total elapsed time by this count. Unfortunately, repetition (especially -// with the same input parameter!) influences the runtime. In time-critical -// code, it is reasonable to expect warm instruction/data caches and TLBs, -// but a perfect record of which branches will be taken is unrealistic. -// Unless the application also repeatedly invokes the measured function with -// the same parameter, the benchmark is measuring something very different - -// a best-case result, almost as if the parameter were made a compile-time -// constant. This may lead to erroneous conclusions about branch-heavy -// algorithms outperforming branch-free alternatives. -// -// Our approach differs in three ways. Adding fences to the timer functions -// reduces variability due to instruction reordering, improving the timer -// resolution to about 40 CPU cycles. However, shorter functions must still -// be invoked repeatedly. For more realistic branch prediction performance, -// we vary the input parameter according to a user-specified distribution. -// Thus, instead of VaryInputs(Measure(Repeat(func))), we change the -// loop nesting to Measure(Repeat(VaryInputs(func))). We also estimate the -// central tendency of the measurement samples with the "half sample mode", -// which is more robust to outliers and skewed data than the mean or median. - -// NOTE: for compatibility with multiple translation units compiled with -// distinct flags, avoid #including headers that define functions. - -#include <stddef.h> -#include <stdint.h> - -#include "absl/base/config.h" - -namespace absl { -ABSL_NAMESPACE_BEGIN -namespace random_internal_nanobenchmark { - -// Input influencing the function being measured (e.g. number of bytes to copy). -using FuncInput = size_t; - -// "Proof of work" returned by Func to ensure the compiler does not elide it. -using FuncOutput = uint64_t; - -// Function to measure: either 1) a captureless lambda or function with two -// arguments or 2) a lambda with capture, in which case the first argument -// is reserved for use by MeasureClosure. -using Func = FuncOutput (*)(const void*, FuncInput); - -// Internal parameters that determine precision/resolution/measuring time. -struct Params { - // For measuring timer overhead/resolution. Used in a nested loop => - // quadratic time, acceptable because we know timer overhead is "low". - // constexpr because this is used to define array bounds. - static constexpr size_t kTimerSamples = 256; - - // Best-case precision, expressed as a divisor of the timer resolution. - // Larger => more calls to Func and higher precision. - size_t precision_divisor = 1024; - - // Ratio between full and subset input distribution sizes. Cannot be less - // than 2; larger values increase measurement time but more faithfully - // model the given input distribution. - size_t subset_ratio = 2; - - // Together with the estimated Func duration, determines how many times to - // call Func before checking the sample variability. Larger values increase - // measurement time, memory/cache use and precision. - double seconds_per_eval = 4E-3; - - // The minimum number of samples before estimating the central tendency. - size_t min_samples_per_eval = 7; - - // The mode is better than median for estimating the central tendency of - // skewed/fat-tailed distributions, but it requires sufficient samples - // relative to the width of half-ranges. - size_t min_mode_samples = 64; - - // Maximum permissible variability (= median absolute deviation / center). - double target_rel_mad = 0.002; - - // Abort after this many evals without reaching target_rel_mad. This - // prevents infinite loops. - size_t max_evals = 9; - - // Retry the measure loop up to this many times. - size_t max_measure_retries = 2; - - // Whether to print additional statistics to stdout. - bool verbose = true; -}; - -// Measurement result for each unique input. -struct Result { - FuncInput input; - - // Robust estimate (mode or median) of duration. - float ticks; - - // Measure of variability (median absolute deviation relative to "ticks"). - float variability; -}; - -// Ensures the thread is running on the specified cpu, and no others. -// Reduces noise due to desynchronized socket RDTSC and context switches. -// If "cpu" is negative, pin to the currently running core. -void PinThreadToCPU(const int cpu = -1); - -// Returns tick rate, useful for converting measurements to seconds. Invariant -// means the tick counter frequency is independent of CPU throttling or sleep. -// This call may be expensive, callers should cache the result. -double InvariantTicksPerSecond(); - -// Precisely measures the number of ticks elapsed when calling "func" with the -// given inputs, shuffled to ensure realistic branch prediction hit rates. -// -// "func" returns a 'proof of work' to ensure its computations are not elided. -// "arg" is passed to Func, or reserved for internal use by MeasureClosure. -// "inputs" is an array of "num_inputs" (not necessarily unique) arguments to -// "func". The values should be chosen to maximize coverage of "func". This -// represents a distribution, so a value's frequency should reflect its -// probability in the real application. Order does not matter; for example, a -// uniform distribution over [0, 4) could be represented as {3,0,2,1}. -// Returns how many Result were written to "results": one per unique input, or -// zero if the measurement failed (an error message goes to stderr). -size_t Measure(const Func func, const void* arg, const FuncInput* inputs, - const size_t num_inputs, Result* results, - const Params& p = Params()); - -// Calls operator() of the given closure (lambda function). -template <class Closure> -static FuncOutput CallClosure(const void* f, const FuncInput input) { - return (*reinterpret_cast<const Closure*>(f))(input); -} - -// Same as Measure, except "closure" is typically a lambda function of -// FuncInput -> FuncOutput with a capture list. -template <class Closure> -static inline size_t MeasureClosure(const Closure& closure, - const FuncInput* inputs, - const size_t num_inputs, Result* results, - const Params& p = Params()) { - return Measure(reinterpret_cast<Func>(&CallClosure<Closure>), - reinterpret_cast<const void*>(&closure), inputs, num_inputs, - results, p); -} - -} // namespace random_internal_nanobenchmark -ABSL_NAMESPACE_END -} // namespace absl - -#endif // ABSL_RANDOM_INTERNAL_NANOBENCHMARK_H_ |