Grok 10.0.5
nanobenchmark.h
Go to the documentation of this file.
1// Copyright 2019 Google LLC
2// SPDX-License-Identifier: Apache-2.0
3//
4// Licensed under the Apache License, Version 2.0 (the "License");
5// you may not use this file except in compliance with the License.
6// You may obtain a copy of the License at
7//
8// http://www.apache.org/licenses/LICENSE-2.0
9//
10// Unless required by applicable law or agreed to in writing, software
11// distributed under the License is distributed on an "AS IS" BASIS,
12// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13// See the License for the specific language governing permissions and
14// limitations under the License.
15
16#ifndef HIGHWAY_HWY_NANOBENCHMARK_H_
17#define HIGHWAY_HWY_NANOBENCHMARK_H_
18
19// Benchmarks functions of a single integer argument with realistic branch
20// prediction hit rates. Uses a robust estimator to summarize the measurements.
21// The precision is about 0.2%.
22//
23// Examples: see nanobenchmark_test.cc.
24//
25// Background: Microbenchmarks such as http://github.com/google/benchmark
26// can measure elapsed times on the order of a microsecond. Shorter functions
27// are typically measured by repeating them thousands of times and dividing
28// the total elapsed time by this count. Unfortunately, repetition (especially
29// with the same input parameter!) influences the runtime. In time-critical
30// code, it is reasonable to expect warm instruction/data caches and TLBs,
31// but a perfect record of which branches will be taken is unrealistic.
32// Unless the application also repeatedly invokes the measured function with
33// the same parameter, the benchmark is measuring something very different -
34// a best-case result, almost as if the parameter were made a compile-time
35// constant. This may lead to erroneous conclusions about branch-heavy
36// algorithms outperforming branch-free alternatives.
37//
38// Our approach differs in three ways. Adding fences to the timer functions
39// reduces variability due to instruction reordering, improving the timer
40// resolution to about 40 CPU cycles. However, shorter functions must still
41// be invoked repeatedly. For more realistic branch prediction performance,
42// we vary the input parameter according to a user-specified distribution.
43// Thus, instead of VaryInputs(Measure(Repeat(func))), we change the
44// loop nesting to Measure(Repeat(VaryInputs(func))). We also estimate the
45// central tendency of the measurement samples with the "half sample mode",
46// which is more robust to outliers and skewed data than the mean or median.
47
48#include <stddef.h>
49#include <stdint.h>
50
51#include "hwy/highway_export.h"
52
53// Enables sanity checks that verify correct operation at the cost of
54// longer benchmark runs.
55#ifndef NANOBENCHMARK_ENABLE_CHECKS
56#define NANOBENCHMARK_ENABLE_CHECKS 0
57#endif
58
59#define NANOBENCHMARK_CHECK_ALWAYS(condition) \
60 while (!(condition)) { \
61 fprintf(stderr, "Nanobenchmark check failed at line %d\n", __LINE__); \
62 abort(); \
63 }
64
65#if NANOBENCHMARK_ENABLE_CHECKS
66#define NANOBENCHMARK_CHECK(condition) NANOBENCHMARK_CHECK_ALWAYS(condition)
67#else
68#define NANOBENCHMARK_CHECK(condition)
69#endif
70
71namespace hwy {
72
73namespace platform {
74
75// Returns tick rate, useful for converting measurements to seconds. Invariant
76// means the tick counter frequency is independent of CPU throttling or sleep.
77// This call may be expensive, callers should cache the result.
79
80// Returns current timestamp [in seconds] relative to an unspecified origin.
81// Features: monotonic (no negative elapsed time), steady (unaffected by system
82// time changes), high-resolution (on the order of microseconds).
84
85// Returns ticks elapsed in back to back timer calls, i.e. a function of the
86// timer resolution (minimum measurable difference) and overhead.
87// This call is expensive, callers should cache the result.
89
90} // namespace platform
91
92// Returns 1, but without the compiler knowing what the value is. This prevents
93// optimizing out code.
95
96// Input influencing the function being measured (e.g. number of bytes to copy).
97using FuncInput = size_t;
98
99// "Proof of work" returned by Func to ensure the compiler does not elide it.
100using FuncOutput = uint64_t;
101
102// Function to measure: either 1) a captureless lambda or function with two
103// arguments or 2) a lambda with capture, in which case the first argument
104// is reserved for use by MeasureClosure.
105using Func = FuncOutput (*)(const void*, FuncInput);
106
107// Internal parameters that determine precision/resolution/measuring time.
108struct Params {
109 // For measuring timer overhead/resolution. Used in a nested loop =>
110 // quadratic time, acceptable because we know timer overhead is "low".
111 // constexpr because this is used to define array bounds.
112 static constexpr size_t kTimerSamples = 256;
113
114 // Best-case precision, expressed as a divisor of the timer resolution.
115 // Larger => more calls to Func and higher precision.
116 size_t precision_divisor = 1024;
117
118 // Ratio between full and subset input distribution sizes. Cannot be less
119 // than 2; larger values increase measurement time but more faithfully
120 // model the given input distribution.
121 size_t subset_ratio = 2;
122
123 // Together with the estimated Func duration, determines how many times to
124 // call Func before checking the sample variability. Larger values increase
125 // measurement time, memory/cache use and precision.
126 double seconds_per_eval = 4E-3;
127
128 // The minimum number of samples before estimating the central tendency.
130
131 // The mode is better than median for estimating the central tendency of
132 // skewed/fat-tailed distributions, but it requires sufficient samples
133 // relative to the width of half-ranges.
134 size_t min_mode_samples = 64;
135
136 // Maximum permissible variability (= median absolute deviation / center).
137 double target_rel_mad = 0.002;
138
139 // Abort after this many evals without reaching target_rel_mad. This
140 // prevents infinite loops.
141 size_t max_evals = 9;
142
143 // Whether to print additional statistics to stdout.
144 bool verbose = true;
145};
146
147// Measurement result for each unique input.
148struct Result {
150
151 // Robust estimate (mode or median) of duration.
152 float ticks;
153
154 // Measure of variability (median absolute deviation relative to "ticks").
156};
157
158// Precisely measures the number of ticks elapsed when calling "func" with the
159// given inputs, shuffled to ensure realistic branch prediction hit rates.
160//
161// "func" returns a 'proof of work' to ensure its computations are not elided.
162// "arg" is passed to Func, or reserved for internal use by MeasureClosure.
163// "inputs" is an array of "num_inputs" (not necessarily unique) arguments to
164// "func". The values should be chosen to maximize coverage of "func". This
165// represents a distribution, so a value's frequency should reflect its
166// probability in the real application. Order does not matter; for example, a
167// uniform distribution over [0, 4) could be represented as {3,0,2,1}.
168// Returns how many Result were written to "results": one per unique input, or
169// zero if the measurement failed (an error message goes to stderr).
170HWY_DLLEXPORT size_t Measure(const Func func, const uint8_t* arg,
171 const FuncInput* inputs, const size_t num_inputs,
172 Result* results, const Params& p = Params());
173
174// Calls operator() of the given closure (lambda function).
175template <class Closure>
176static FuncOutput CallClosure(const Closure* f, const FuncInput input) {
177 return (*f)(input);
178}
179
180// Same as Measure, except "closure" is typically a lambda function of
181// FuncInput -> FuncOutput with a capture list.
182template <class Closure>
183static inline size_t MeasureClosure(const Closure& closure,
184 const FuncInput* inputs,
185 const size_t num_inputs, Result* results,
186 const Params& p = Params()) {
187 return Measure(reinterpret_cast<Func>(&CallClosure<Closure>),
188 reinterpret_cast<const uint8_t*>(&closure), inputs, num_inputs,
189 results, p);
190}
191
192} // namespace hwy
193
194#endif // HIGHWAY_HWY_NANOBENCHMARK_H_
#define HWY_DLLEXPORT
Definition highway_export.h:13
HWY_DLLEXPORT uint64_t TimerResolution()
HWY_DLLEXPORT double Now()
HWY_DLLEXPORT double InvariantTicksPerSecond()
Definition aligned_allocator.h:27
static FuncOutput CallClosure(const Closure *f, const FuncInput input)
Definition nanobenchmark.h:176
FuncOutput(*)(const void *, FuncInput) Func
Definition nanobenchmark.h:105
size_t FuncInput
Definition nanobenchmark.h:97
uint64_t FuncOutput
Definition nanobenchmark.h:100
HWY_DLLEXPORT size_t Measure(const Func func, const uint8_t *arg, const FuncInput *inputs, const size_t num_inputs, Result *results, const Params &p=Params())
static size_t MeasureClosure(const Closure &closure, const FuncInput *inputs, const size_t num_inputs, Result *results, const Params &p=Params())
Definition nanobenchmark.h:183
HWY_DLLEXPORT int Unpredictable1()
Definition nanobenchmark.h:108
size_t subset_ratio
Definition nanobenchmark.h:121
size_t precision_divisor
Definition nanobenchmark.h:116
bool verbose
Definition nanobenchmark.h:144
size_t min_mode_samples
Definition nanobenchmark.h:134
static constexpr size_t kTimerSamples
Definition nanobenchmark.h:112
size_t max_evals
Definition nanobenchmark.h:141
double target_rel_mad
Definition nanobenchmark.h:137
size_t min_samples_per_eval
Definition nanobenchmark.h:129
double seconds_per_eval
Definition nanobenchmark.h:126
Definition nanobenchmark.h:148
float ticks
Definition nanobenchmark.h:152
float variability
Definition nanobenchmark.h:155
FuncInput input
Definition nanobenchmark.h:149