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Spelling benchmark (#42457)

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* spelling: approximate

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* spelling: available

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* spelling: benchmarks

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* spelling: between

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* spelling: calculation

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* spelling: characterization

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* spelling: coefficient

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* spelling: computation

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* spelling: deterministic

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* spelling: divisor

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* spelling: encounter

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* spelling: expected

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* spelling: fibonacci

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* spelling: fulfill

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* spelling: implements

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* spelling: into

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* spelling: intrinsic

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* spelling: markdown

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* spelling: measure

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* spelling: occurrences

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* spelling: omitted

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* spelling: partition

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* spelling: performance

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* spelling: practice

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* spelling: preemptive

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* spelling: repeated

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* spelling: requirements

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* spelling: requires

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* spelling: response

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* spelling: supports

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* spelling: unknown

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* spelling: utilities

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* spelling: verbose

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Co-authored-by: Josh Soref <jsoref@users.noreply.github.com>
This commit is contained in:
Josh Soref
2022-04-25 12:02:06 -04:00
committed by GitHub
parent e8b5204bd0
commit fa3ff899a9
15 changed files with 35 additions and 35 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
benchmark/CMakeLists.txt
View File

@@ -241,7 +241,7 @@ set(SWIFT_BENCHMARK_EXTRA_FLAGS "" CACHE STRING
"Extra options to pass to swiftc when building the benchmarks")
set(SWIFT_BENCHMARK_UNOPTIMIZED_DRIVER NO CACHE BOOL
"Build the benchmark driver utilites without optimization (default: no)")
"Build the benchmark driver utilities without optimization (default: no)")
if (SWIFT_BENCHMARK_BUILT_STANDALONE)
# This option's value must match the value of the same option used when

6
benchmark/scripts/Benchmark_Driver
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@@ -20,7 +20,7 @@ Example:
Use `Benchmark_Driver -h` for help on available commands and options.
class `BenchmarkDriver` runs performance tests and impements the `run` COMMAND.
class `BenchmarkDriver` runs performance tests and implements the `run` COMMAND.
class `BenchmarkDoctor` analyzes performance tests, implements `check` COMMAND.
"""
@@ -544,7 +544,7 @@ class BenchmarkDoctor(object):
caveat = "" if setup == 0 else " (excluding the setup overhead)"
log("'%s' execution took at least %d μs%s.", name, runtime, caveat)
def factor(base): # suitable divisior that's integer power of base
def factor(base): # suitable divisor that's integer power of base
return int(
pow(base, math.ceil(math.log(runtime / float(threshold), base)))
)
@@ -718,7 +718,7 @@ class BenchmarkDoctor(object):
return measurements
def analyze(self, benchmark_measurements):
"""Analyze whether benchmark fullfills all requirtements."""
"""Analyze whether benchmark fulfills all requirements."""
self.log.debug("Analyzing %s", benchmark_measurements["name"])
for rule in self.requirements:
rule(benchmark_measurements)

16
benchmark/scripts/compare_perf_tests.py
View File

@@ -22,7 +22,7 @@ class `PerformanceTestSamples` is collection of `Sample`s and their statistics.
class `PerformanceTestResult` is a summary of performance test execution.
class `LogParser` converts log files into `PerformanceTestResult`s.
class `ResultComparison` compares new and old `PerformanceTestResult`s.
class `TestComparator` analyzes changes betweeen the old and new test results.
class `TestComparator` analyzes changes between the old and new test results.
class `ReportFormatter` creates the test comparison report in specified format.
"""
@@ -111,7 +111,7 @@ class PerformanceTestSamples(object):
Experimentally, this rule seems to perform well-enough on the
benchmark runtimes in the microbenchmark range to filter out
the environment noise caused by preemtive multitasking.
the environment noise caused by preemptive multitasking.
"""
lo = (
0
@@ -205,7 +205,7 @@ class PerformanceTestSamples(object):
@property
def cv(self):
"""Coeficient of Variation (%)."""
"""Coefficient of Variation (%)."""
return (self.sd / self.mean) if self.mean else 0
@property
@@ -225,7 +225,7 @@ class PerformanceTestResult(object):
Reported by the test driver (Benchmark_O, Benchmark_Onone, Benchmark_Osize
or Benchmark_Driver).
It suppors 2 log formats emitted by the test driver. Legacy format with
It supports 2 log formats emitted by the test driver. Legacy format with
statistics for normal distribution (MEAN, SD):
#,TEST,SAMPLES,MIN(μs),MAX(μs),MEAN(μs),SD(μs),MEDIAN(μs),MAX_RSS(B)
And new quantiles format with variable number of columns:
@@ -311,7 +311,7 @@ class PerformanceTestResult(object):
"""Merge two results.
Recomputes min, max and mean statistics. If all `samples` are
avaliable, it recomputes all the statistics.
available, it recomputes all the statistics.
The use case here is comparing test results parsed from concatenated
log files from multiple runs of benchmark driver.
"""
@@ -514,12 +514,12 @@ class LogParser(object):
class TestComparator(object):
"""Analyzes changes betweeen the old and new test results.
"""Analyzes changes between the old and new test results.
It determines which tests were `added`, `removed` and which can be
compared. It then splits the `ResultComparison`s into 3 groups according to
the `delta_threshold` by the change in performance: `increased`,
`descreased` and `unchanged`. Whole computaion is performed during
`descreased` and `unchanged`. Whole computation is performed during
initialization and results are provided as properties on this object.
The lists of `added`, `removed` and `unchanged` tests are sorted
@@ -576,7 +576,7 @@ class TestComparator(object):
class ReportFormatter(object):
"""Creates the report from perfromance test comparison in specified format.
"""Creates the report from performance test comparison in specified format.
`ReportFormatter` formats the `PerformanceTestResult`s and
`ResultComparison`s provided by `TestComparator` into report table.

4
benchmark/scripts/run_smoke_bench
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@@ -15,7 +15,7 @@
#
# Performs a very fast check which benchmarks regressed and improved.
#
# Initially runs the benchmars with a low sample count and just re-runs those
# Initially runs the benchmarks with a low sample count and just re-runs those
# benchmarks which differ.
# Also reports code size differences.
#
@@ -224,7 +224,7 @@ def measure(driver, tests, i):
def merge(results, other_results):
""""Merge the other PreformanceTestResults into the first dictionary."""
""""Merge the other PerformanceTestResults into the first dictionary."""
for test, result in other_results.items():
results[test].merge(result)
return results

10
benchmark/scripts/test_Benchmark_Driver.py
View File

@@ -135,12 +135,12 @@ class Test_parse_args(unittest.TestCase):
self.assertIsNone(parse_args(["run"]).output_dir)
self.assertEqual(parse_args(["run", "--output-dir", "/log"]).output_dir, "/log")
def test_check_supports_vebose_output(self):
def test_check_supports_verbose_output(self):
self.assertFalse(parse_args(["check"]).verbose)
self.assertTrue(parse_args(["check", "-v"]).verbose)
self.assertTrue(parse_args(["check", "--verbose"]).verbose)
def test_check_supports_mardown_output(self):
def test_check_supports_markdown_output(self):
self.assertFalse(parse_args(["check"]).markdown)
self.assertTrue(parse_args(["check", "-md"]).markdown)
self.assertTrue(parse_args(["check", "--markdown"]).markdown)
@@ -486,7 +486,7 @@ class TestBenchmarkDriverRunningTests(unittest.TestCase):
shutil.rmtree(temp_dir)
def test_deterministing_hashing(self):
def test_deterministic_hashing(self):
cmd = ["printenv", "SWIFT_DETERMINISTIC_HASHING"]
driver = BenchmarkDriver(["no args"], tests=["ignored"])
self.assertEqual(driver._invoke(cmd).strip(), "1")
@@ -839,7 +839,7 @@ class TestBenchmarkDoctor(unittest.TestCase):
quantum used by macos scheduler. Linux scheduler's quantum is 6ms.
Driver yielding the process before the 10ms quantum elapses helped
a lot, but benchmarks with runtimes under 1ms usually exhibit a strong
mode which is best for accurate performance charaterization.
mode which is best for accurate performance characterization.
To minimize the number of involuntary context switches that corrupt our
measurements, we should strive to stay in the microbenchmark range.
@@ -999,7 +999,7 @@ class TestBenchmarkDoctor(unittest.TestCase):
doctor.analyze(
{
# The threshold of 15 pages was estimated from previous
# measurements. The normal range should be probably aproximated
# measurements. The normal range should be probably approximate
# by a function instead of a simple constant.
# TODO: re-evaluate normal range from whole SBS
"name": "ConstantMemory",

6
benchmark/scripts/test_compare_perf_tests.py
View File

@@ -247,7 +247,7 @@ class TestPerformanceTestResult(unittest.TestCase):
def test_init_delta_quantiles(self):
# #,TEST,SAMPLES,MIN(μs),𝚫MEDIAN,𝚫MAX
# 2-quantile from 2 samples in repeated min, when delta encoded,
# the difference is 0, which is ommited -- only separator remains
# the difference is 0, which is omitted -- only separator remains
log = "202,DropWhileArray,2,265,,22"
r = PerformanceTestResult(log.split(","), quantiles=True, delta=True)
self.assertEqual((r.num_samples, r.min, r.median, r.max), (2, 265, 265, 287))
@@ -257,7 +257,7 @@ class TestPerformanceTestResult(unittest.TestCase):
def test_init_oversampled_quantiles(self):
"""When num_samples is < quantile + 1, some of the measurements are
repeated in the report summary. Samples should contain only true
values, discarding the repetated artifacts from quantile estimation.
values, discarding the repeated artifacts from quantile estimation.
The test string is slightly massaged output of the following R script:
subsample <- function(x, q) {
@@ -517,7 +517,7 @@ class OldAndNewLog(unittest.TestCase):
class TestLogParser(unittest.TestCase):
def test_parse_results_csv(self):
"""Ignores uknown lines, extracts data from supported formats."""
"""Ignores unknown lines, extracts data from supported formats."""
log = """#,TEST,SAMPLES,MIN(us),MAX(us),MEAN(us),SD(us),MEDIAN(us)
7,Array.append.Array.Int?,20,10,10,10,0,10
21,Bridging.NSArray.as!.Array.NSString,20,11,11,11,0,11

4
benchmark/scripts/test_utils.py
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@@ -69,7 +69,7 @@ class Mock(object):
def expect(self, call_args, response):
"""Expect invocation of tested method with given arguments.
Stores the canned reponse in the `respond` dictionary.
Stores the canned response in the `respond` dictionary.
"""
call_args = tuple(call_args)
self.expected.append(call_args)
@@ -83,7 +83,7 @@ class Mock(object):
)
def assert_called_all_expected(self):
"""Verify that all expeced invocations of tested method were called."""
"""Verify that all expected invocations of tested method were called."""
assert self.calls == self.expected, "\nExpected: {0}, \n Called: {1}".format(
self.expected, self.calls
)

2
benchmark/single-source/Breadcrumbs.swift
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@@ -323,7 +323,7 @@ class UTF16ToIdxRange: BenchmarkBase {
}
/// Split a string into `count` random slices and convert their index ranges
/// into into UTF-16 offset pairs.
/// into UTF-16 offset pairs.
class IdxToUTF16Range: BenchmarkBase {
let count: Int
var inputIndices: [Range<String.Index>] = []

2
benchmark/single-source/LuhnAlgoEager.swift
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@@ -72,7 +72,7 @@ extension MapSomeSequenceView: Sequence {
}
// now extend a lazy collection to return that view
// from a call to mapSome. In pracice, when doing this,
// from a call to mapSome. In practice, when doing this,
// you should do it for all the lazy wrappers
// (i.e. random-access, forward and sequence)
extension LazyCollectionProtocol {

4
benchmark/single-source/LuhnAlgoLazy.swift
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@@ -72,7 +72,7 @@ extension MapSomeSequenceView: Sequence {
}
// now extend a lazy collection to return that view
// from a call to mapSome. In pracice, when doing this,
// from a call to mapSome. In practice, when doing this,
// you should do it for all the lazy wrappers
// (i.e. random-access, forward and sequence)
extension LazyCollectionProtocol {
@@ -219,7 +219,7 @@ let combineDoubleDigits = {
(10...18).contains($0) ? $0-9 : $0
}
// first, the lazy version of checksum calcuation
// first, the lazy version of checksum calculation
let lazychecksum = { (ccnum: String) -> Bool in
ccnum.lazy
|> reverse

2
benchmark/single-source/SIMDReduceInteger.swift
View File

@@ -120,7 +120,7 @@ public func run_SIMDReduceInt32x4_init(_ n: Int) {
@inline(never)
public func run_SIMDReduceInt32x4_cast(_ n: Int) {
// Morally it seems like we "should" be able to use withMemoryRebound
// to SIMD4<Int32>, but that function requries that the sizes match in
// to SIMD4<Int32>, but that function requires that the sizes match in
// debug builds, so this is pretty ugly. The following "works" for now,
// but is probably in violation of the formal model (the exact rules
// for "assumingMemoryBound" are not clearly documented). We need a

2
benchmark/single-source/SortArrayInClass.swift
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@@ -8,7 +8,7 @@
// See https://swift.org/LICENSE.txt for license information
// See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors
//
// This benchmark is derived from user code that encoutered a major
// This benchmark is derived from user code that encountered a major
// performance problem in normal usage. Contributed by Saleem
// Abdulrasool (compnerd).
//

4
benchmark/single-source/SortIntPyramids.swift
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@@ -1,8 +1,8 @@
import TestsUtils
// This benchmark aims to measuare heapSort path of stdlib sorting function.
// This benchmark aims to measure heapSort path of stdlib sorting function.
// Datasets in this benchmark are influenced by stdlib partition function,
// therefore if stdlib partion implementation changes we should correct these
// therefore if stdlib partition implementation changes we should correct these
// datasets or disable/skip this benchmark
public let benchmarks = [
BenchmarkInfo(

2
benchmark/single-source/WordCount.swift
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@@ -245,7 +245,7 @@ public func run_WordCountUniqueUTF16(_ n: Int) {
}
/// Returns an array of all words in the supplied string, along with their
/// number of occurances. The array is sorted by decreasing frequency.
/// number of occurrences. The array is sorted by decreasing frequency.
/// (Words are case-sensitive and only support a limited subset of Unicode.)
@inline(never)
func histogram<S: Sequence>(for words: S) -> [(String, Int)]

4
benchmark/utils/TestsUtils.swift
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@@ -31,7 +31,7 @@ public enum BenchmarkCategory : String {
case exclusivity, differentiation
// Algorithms are "micro" that test some well-known algorithm in isolation:
// sorting, searching, hashing, fibonaci, crypto, etc.
// sorting, searching, hashing, fibonacci, crypto, etc.
case algorithm
// Miniapplications are contrived to mimic some subset of application behavior
@@ -55,7 +55,7 @@ public enum BenchmarkCategory : String {
// counterproductive.
case unstable
// CPU benchmarks represent instrinsic Swift performance. They are useful for
// CPU benchmarks represent intrinsic Swift performance. They are useful for
// measuring a fully baked Swift implementation across different platforms and
// hardware. The benchmark should also be reasonably applicable to real Swift
// code--it should exercise a known performance critical area. Typically these