.github/workflows | ||
bench | ||
src/Test/Tasty | ||
.cirrus.yml | ||
.gitignore | ||
.hlint.yaml | ||
cabal.haskell-ci | ||
changelog.md | ||
compare_benches.sh | ||
convert_readme.sh | ||
example.svg | ||
LICENSE | ||
README.md | ||
tasty-bench.cabal |
tasty-bench
![Stackage Nightly](http://stackage.org/package/tasty-bench/badge/nightly)
Featherlight benchmark framework (only one file!) for performance measurement
with API mimicking criterion
and gauge
.
A prominent feature is built-in comparison against previous runs
and between benchmarks.
- How lightweight is it?
- How is it possible?
- How to switch?
- How to write a benchmark?
- How to read results?
- Wall-clock time vs. CPU time
- Statistical model
- Memory usage
- Combining tests and benchmarks
- Troubleshooting
- Isolating interfering benchmarks
- Comparison against baseline
- Comparison between benchmarks
- Plotting results
- Build flags
- Command-line options
- Custom command-line options
How lightweight is it?
There is only one source file Test.Tasty.Bench
and no non-boot dependencies
except tasty
.
So if you already depend on tasty
for a test suite, there
is nothing else to install.
Compare this to criterion
(10+ modules, 50+ dependencies) and gauge
(40+ modules, depends on basement
and vector
). A build on a clean machine is up to 16x
faster than criterion
and up to 4x faster than gauge
. A build without dependencies
is up to 6x faster than criterion
and up to 8x faster than gauge
.
tasty-bench
is a native Haskell library and works everywhere, where GHC
does, including WASM. We support a full range of architectures (i386
, amd64
, armhf
,
arm64
, ppc64le
, s390x
) and operating systems (Linux, Windows, macOS,
FreeBSD, OpenBSD, NetBSD), plus any GHC from 7.0 to 9.8.
How is it possible?
Our benchmarks are literally regular tasty
tests, so we can leverage all existing
machinery for command-line options, resource management, structuring,
listing and filtering benchmarks, running and reporting results. It also means
that tasty-bench
can be used in conjunction with other tasty
ingredients.
Unlike criterion
and gauge
we use a very simple statistical model described below.
This is arguably a questionable choice, but it works pretty well in practice.
A rare developer is sufficiently well-versed in probability theory
to make sense and use of all numbers generated by criterion
.
How to switch?
Cabal mixins
allow to taste tasty-bench
instead of criterion
or gauge
without changing a single line of code:
cabal-version: 2.0
benchmark foo
...
build-depends:
tasty-bench
mixins:
tasty-bench (Test.Tasty.Bench as Criterion, Test.Tasty.Bench as Criterion.Main, Test.Tasty.Bench as Gauge, Test.Tasty.Bench as Gauge.Main)
This works vice versa as well: if you use tasty-bench
, but at some point
need a more comprehensive statistical analysis,
it is easy to switch temporarily back to criterion
.
How to write a benchmark?
Benchmarks are declared in a separate section of cabal
file:
cabal-version: 2.0
name: bench-fibo
version: 0.0
build-type: Simple
synopsis: Example of a benchmark
benchmark bench-fibo
main-is: BenchFibo.hs
type: exitcode-stdio-1.0
build-depends: base, tasty-bench
ghc-options: "-with-rtsopts=-A32m"
if impl(ghc >= 8.6)
ghc-options: -fproc-alignment=64
And here is BenchFibo.hs
:
import Test.Tasty.Bench
fibo :: Int -> Integer
fibo n = if n < 2 then toInteger n else fibo (n - 1) + fibo (n - 2)
main :: IO ()
main = defaultMain
[ bgroup "Fibonacci numbers"
[ bench "fifth" $ nf fibo 5
, bench "tenth" $ nf fibo 10
, bench "twentieth" $ nf fibo 20
]
]
Since tasty-bench
provides an API compatible with criterion
,
one can refer to its documentation for more examples.
How to read results?
Running the example above (cabal bench
or stack bench
)
results in the following output:
All
Fibonacci numbers
fifth: OK (2.13s)
63 ns ± 3.4 ns
tenth: OK (1.71s)
809 ns ± 73 ns
twentieth: OK (3.39s)
104 μs ± 4.9 μs
All 3 tests passed (7.25s)
The output says that, for instance, the first benchmark was repeatedly executed for 2.13 seconds (wall-clock time), its predicted mean CPU time was 63 nanoseconds and means of individual samples do not often diverge from it further than ±3.4 nanoseconds (double standard deviation). Take standard deviation numbers with a grain of salt; there are lies, damned lies, and statistics.
Wall-clock time vs. CPU time
What time are we talking about?
Both criterion
and gauge
by default report wall-clock time, which is
affected by any other application which runs concurrently.
Ideally benchmarks are executed on a dedicated server without any other load,
but — let's face the truth — most of developers run benchmarks
on a laptop with a hundred other services and a window manager, and
watch videos while waiting for benchmarks to finish. That's the cause
of a notorious "variance introduced by outliers: 88% (severely inflated)" warning.
To alleviate this issue tasty-bench
measures CPU time by getCPUTime
instead of wall-clock time by default.
It does not provide a perfect isolation from other processes (e. g.,
if CPU cache is spoiled by others, populating data back from RAM
is your burden), but is a bit more stable.
Caveat: this means that for multithreaded algorithms
tasty-bench
reports total elapsed CPU time across all cores, while
criterion
and gauge
print maximum of core's wall-clock time.
It also means that by default tasty-bench
does not measure time spent out of process,
e. g., calls to other executables. To work around this limitation
use --time-mode
command-line option or set it locally via TimeMode
option.
Statistical model
Here is a procedure used by tasty-bench
to measure execution time:
- Set
n \leftarrow 1
. - Measure execution time
t_n
ofn
iterations and execution timet_{2n}
of2n
iterations. - Find
t
which minimizes deviation of(nt,2nt)
from(t_n,t_{2n})
, namelyt \leftarrow (t_n + 2t_{2n}) / 5n
. - If deviation is small enough (see
--stdev
below) or time is running out soon (see--timeout
below), returnt
as a mean execution time. - Otherwise set
n \leftarrow 2n
and jump back to Step 2.
This is roughly similar to the linear regression approach which criterion
takes,
but we fit only two last points. This allows us to simplify away all heavy-weight
statistical analysis. More importantly, earlier measurements,
which are presumably shorter and noisier, do not affect overall result.
This is in contrast to criterion
, which fits all measurements and
is biased to use more data points corresponding to shorter runs
(it employs n \leftarrow 1.05n
progression).
Mean time and its deviation does not say much about the distribution of individual timings. E. g., imagine a computation which (according to a coarse system timer) takes either 0 ms or 1 ms with equal probability. While one would be able to establish that its mean time is 0.5 ms with a very small deviation, this does not imply that individual measurements are anywhere near 0.5 ms. Even assuming an infinite precision of a system timer, the distribution of individual times is not known to be normal.
Obligatory disclaimer: statistics is a tricky matter, there is no
one-size-fits-all approach.
In the absence of a good theory
simplistic approaches are as (un)sound as obscure ones.
Those who seek statistical soundness should rather collect raw data
and process it themselves using a proper statistical toolbox.
Data reported by tasty-bench
is only of indicative and comparative significance.
Memory usage
Configuring RTS to collect GC statistics
(e. g., via cabal bench --benchmark-options '+RTS -T'
or stack bench --ba '+RTS -T'
) enables tasty-bench
to estimate and report
memory usage:
All
Fibonacci numbers
fifth: OK (2.13s)
63 ns ± 3.4 ns, 223 B allocated, 0 B copied, 2.0 MB peak memory
tenth: OK (1.71s)
809 ns ± 73 ns, 2.3 KB allocated, 0 B copied, 4.0 MB peak memory
twentieth: OK (3.39s)
104 μs ± 4.9 μs, 277 KB allocated, 59 B copied, 5.0 MB peak memory
All 3 tests passed (7.25s)
This data is reported as per RTSStats
fields: allocated_bytes
, copied_bytes
and max_mem_in_use_bytes
.
Combining tests and benchmarks
When optimizing an existing function, it is important to check that its
observable behavior remains unchanged. One can rebuild
both tests and benchmarks after each change, but it would be more convenient
to run sanity checks within benchmark itself. Since our benchmarks
are compatible with tasty
tests, we can easily do so.
Imagine you come up with a faster function myFibo
to generate Fibonacci numbers:
import Test.Tasty.Bench
import Test.Tasty.QuickCheck -- from tasty-quickcheck package
fibo :: Int -> Integer
fibo n = if n < 2 then toInteger n else fibo (n - 1) + fibo (n - 2)
myFibo :: Int -> Integer
myFibo n = if n < 3 then toInteger n else myFibo (n - 1) + myFibo (n - 2)
main :: IO ()
main = Test.Tasty.Bench.defaultMain -- not Test.Tasty.defaultMain
[ bench "fibo 20" $ nf fibo 20
, bench "myFibo 20" $ nf myFibo 20
, testProperty "myFibo = fibo" $ \n -> fibo n === myFibo n
]
This outputs:
All
fibo 20: OK (3.02s)
104 μs ± 4.9 μs
myFibo 20: OK (1.99s)
71 μs ± 5.3 μs
myFibo = fibo: FAIL
*** Failed! Falsified (after 5 tests and 1 shrink):
2
1 /= 2
Use --quickcheck-replay=927711 to reproduce.
1 out of 3 tests failed (5.03s)
We see that myFibo
is indeed significantly faster than fibo
,
but unfortunately does not do the same thing. One should probably
look for another way to speed up generation of Fibonacci numbers.
Troubleshooting
-
If benchmarks take too long, set
--timeout
to limit execution time of individual benchmarks, andtasty-bench
will do its best to fit into a given time frame. Without--timeout
we rerun benchmarks until achieving a target precision set by--stdev
, which in a noisy environment of a modern laptop with GUI may take a lot of time.While
criterion
runs each benchmark at least for 5 seconds,tasty-bench
is happy to conclude earlier, if it does not compromise the quality of results. In our experimentstasty-bench
suites tend to finish earlier, even if some individual benchmarks take longer than withcriterion
.A common source of noisiness is garbage collection. Setting a larger allocation area (nursery) is often a good idea, either via
cabal bench --benchmark-options '+RTS -A32m'
orstack bench --ba '+RTS -A32m'
. Alternatively bake it intocabal
file asghc-options: "-with-rtsopts=-A32m"
. -
Never compile benchmarks with
-fstatic-argument-transformation
, because it breaks a trick we use to force GHC into reevaluation of the same function application over and over again. -
If benchmark results look malformed like below, make sure that you are invoking
Test.Tasty.Bench.defaultMain
and notTest.Tasty.defaultMain
(the difference isconsoleBenchReporter
vs.consoleTestReporter
):All fibo 20: OK (1.46s) Response {respEstimate = Estimate {estMean = Measurement {measTime = 87496728, measAllocs = 0, measCopied = 0}, estStdev = 694487}, respIfSlower = FailIfSlower Infinity, respIfFaster = FailIfFaster Infinity}
-
If benchmarks fail with an error message
Unhandled resource. Probably a bug in the runner you're using.
or
Unexpected state of the resource (NotCreated) in getResource. Report as a tasty bug.
this is likely caused by
env
orenvWithCleanup
affecting benchmarks structure. You can useenv
to read test data fromIO
, but not to read benchmark names or affect their hierarchy in other way. This is a fundamental restriction oftasty
to list and filter benchmarks without launching missiles. -
If benchmarks fail with
Test dependencies form a loop
orTest dependencies have cycles
, this is likely because ofbcompare
, which compares a benchmark with itself. Locating a benchmark in a global environment may be tricky, please refer totasty
documentation for details and consider usinglocateBenchmark
. -
When seeing
This benchmark takes more than 100 seconds. Consider setting --timeout, if this is unexpected (or to silence this warning).
do follow the advice: abort benchmarks and pass
-t100
or similar. Unless you are benchmarking a very computationally expensive function, a single benchmark should stabilize after a couple of seconds. This warning is a sign that your environment is too noisy, in which casetasty-bench
will continue trying with exponentially longer intervals, often unproductively. -
The following error can be thrown when benchmarks are built with
ghc-options: -threaded
:Benchmarks must not be run concurrently. Please pass -j1 and/or avoid +RTS -N.
The underlying cause is that
tasty
runs tests concurrently, which is harmful for reliable performance measurements. Make sure to usetasty-bench >= 0.3.4
and invokeTest.Tasty.Bench.defaultMain
and notTest.Tasty.defaultMain
. Note thatlocalOption (NumThreads 1)
quashes the warning, but does not eliminate the cause. -
If benchmarks using GHC 9.4.4+ segfault on Windows, check that you are not using non-moving garbage collector
--nonmoving-gc
. This is likely caused by GHC issue. Previous releases oftasty-bench
recommended enabling--nonmoving-gc
to stabilise benchmarks, but it's discouraged now. -
If you see
<stdout>: commitBuffer: invalid argument (cannot encode character '\177')
it means that your locale does not support UTF-8.
tasty-bench
makes an effort to force locale to UTF-8, but sometimes, when benchmarks are a part of a larger application, it's impossible to do so. In such case runlocale -a
to list available locales and set a UTF-8-capable one (e. g.,export LANG=C.UTF-8
) before starting benchmarks.
Isolating interfering benchmarks
One difficulty of benchmarking in Haskell is that it is
hard to isolate benchmarks so that they do not interfere.
Changing the order of benchmarks or skipping some of them
has an effect on heap's layout and thus affects garbage collection.
This issue is well attested in
both
criterion
and
gauge
.
Usually (but not always) skipping some benchmarks speeds up remaining ones. That's because once a benchmark allocated heap which for some reason was not promptly released afterwards (e. g., it forced a top-level thunk in an underlying library), all further benchmarks are slowed down by garbage collector processing this additional amount of live data over and over again.
There are several mitigation strategies. First of all, giving garbage collector
more breathing space by +RTS -A32m
(or more) is often good enough.
Further, avoid using top-level bindings to store large test data. Once such thunks
are forced, they remain allocated forever, which affects detrimentally subsequent
unrelated benchmarks. Treat them as external data, supplied via env
: instead of
largeData :: String
largeData = replicate 1000000 'a'
main :: IO ()
main = defaultMain
[ bench "large" $ nf length largeData, ... ]
use
import Control.DeepSeq (force)
import Control.Exception (evaluate)
main :: IO ()
main = defaultMain
[ env (evaluate (force (replicate 1000000 'a'))) $ \largeData ->
bench "large" $ nf length largeData, ... ]
Finally, as an ultimate measure to reduce interference between benchmarks, one can run each of them in a separate process. We do not quite recommend this approach, but if you are desperate, here is how:
cabal run -v0 all:benches -- -l | sed -e 's/[\"]/\\\\\\&/g' | while read -r name; do cabal run -v0 all:benches -- -p '$0 == "'"$name"'"'; done
This assumes that there is a single benchmark suite in the project and that benchmark names do not contain newlines.
Comparison against baseline
One can compare benchmark results against an earlier run in an automatic way.
When using this feature, it's especially important to compile benchmarks with
ghc-options:
-fproc-alignment
=64
, otherwise results could be skewed by
intermittent changes in cache-line alignment.
Firstly, run tasty-bench
with --csv FILE
key
to dump results to FILE
in CSV format
(it could be a good idea to set smaller --stdev
, if possible):
Name,Mean (ps),2*Stdev (ps)
All.Fibonacci numbers.fifth,48453,4060
All.Fibonacci numbers.tenth,637152,46744
All.Fibonacci numbers.twentieth,81369531,3342646
Now modify implementation and rerun benchmarks
with --baseline FILE
key. This produces a report as follows:
All
Fibonacci numbers
fifth: OK (0.44s)
53 ns ± 2.7 ns, 8% more than baseline
tenth: OK (0.33s)
641 ns ± 59 ns, same as baseline
twentieth: OK (0.36s)
77 μs ± 6.4 μs, 5% less than baseline
All 3 tests passed (1.50s)
You can also fail benchmarks, which deviate too far from baseline, using
--fail-if-slower
and --fail-if-faster
options. For example, setting both of them
to 6 will fail the first benchmark above (because it is more than 6% slower),
but the last one still succeeds (even while it is measurably faster than baseline,
deviation is less than 6%). Consider also using --hide-successes
to show
only problematic benchmarks, or even
tasty-rerun
package
to focus on rerunning failing items only.
If you wish to compare two CSV reports non-interactively, here is a handy awk
incantation:
awk 'BEGIN{FS=",";OFS=",";print "Name,Old,New,Ratio"}FNR==1{trueNF=NF;next}NF<trueNF{print "Benchmark names should not contain newlines";exit 1}FNR==NR{oldTime=$(NF-trueNF+2);NF-=trueNF-1;a[$0]=oldTime;next}{newTime=$(NF-trueNF+2);NF-=trueNF-1;print $0,a[$0],newTime,newTime/a[$0];gs+=log(newTime/a[$0]);gc++}END{if(gc>0)print "Geometric mean,,",exp(gs/gc)}' old.csv new.csv
A larger shell snippet to compare two git
commits can be found in compare_benches.sh
.
Note that columns in CSV report are different from what criterion
or gauge
would produce. If names do not contain commas, missing columns can be faked this way:
awk 'BEGIN{FS=",";OFS=",";print "Name,Mean,MeanLB,MeanUB,Stddev,StddevLB,StddevUB"}NR==1{trueNF=NF;next}NF<trueNF{print $0;next}{mean=$(NF-trueNF+2);stddev=$(NF-trueNF+3);NF-=trueNF-1;print $0,mean/1e12,mean/1e12,mean/1e12,stddev/2e12,stddev/2e12,stddev/2e12}'
To fake gauge
in --csvraw
mode use
awk 'BEGIN{FS=",";OFS=",";print "name,iters,time,cycles,cpuTime,utime,stime,maxrss,minflt,majflt,nvcsw,nivcsw,allocated,numGcs,bytesCopied,mutatorWallSeconds,mutatorCpuSeconds,gcWallSeconds,gcCpuSeconds"}NR==1{trueNF=NF;next}NF<trueNF{print $0;next}{mean=$(NF-trueNF+2);fourth=$(NF-trueNF+4);fifth=$(NF-trueNF+5);sixth=$(NF-trueNF+6);NF-=trueNF-1;print $0,1,mean/1e12,0,mean/1e12,mean/1e12,0,sixth+0,0,0,0,0,fourth+0,0,fifth+0,0,0,0,0}'
Comparison between benchmarks
You can also compare benchmarks to each other without any external tools, all in the comfort of your terminal.
import Test.Tasty.Bench
fibo :: Int -> Integer
fibo n = if n < 2 then toInteger n else fibo (n - 1) + fibo (n - 2)
main :: IO ()
main = defaultMain
[ bgroup "Fibonacci numbers"
[ bcompare "tenth" $ bench "fifth" $ nf fibo 5
, bench "tenth" $ nf fibo 10
, bcompare "tenth" $ bench "twentieth" $ nf fibo 20
]
]
This produces a report, comparing mean times of fifth
and twentieth
to tenth
:
All
Fibonacci numbers
fifth: OK (16.56s)
121 ns ± 2.6 ns, 0.08x
tenth: OK (6.84s)
1.6 μs ± 31 ns
twentieth: OK (6.96s)
203 μs ± 4.1 μs, 128.36x
To locate a baseline benchmark in a larger suite use locateBenchmark
.
One can leverage comparisons between benchmarks to implement portable performance
tests, expressing properties like "this algorithm must be at least twice faster
than that one" or "this operation should not be more than thrice slower than that".
This can be achieved with bcompareWithin
, which takes an acceptable interval
of performance as an argument.
Plotting results
Users can dump results into CSV with --csv FILE
and plot them using gnuplot
or other software. But for convenience
there is also a built-in quick-and-dirty SVG plotting feature,
which can be invoked by passing --svg FILE
. Here is a sample of its output:
Build flags
Build flags are a brittle subject and users do not normally need to touch them.
- If you find yourself in an environment, where
tasty
is not available and you have access to boot packages only, you can still usetasty-bench
! Just copyTest/Tasty/Bench.hs
to your project (imagine it like a header-only C library). It will provide you with functions to buildBenchmarkable
and run them manually viameasureCpuTime
. This mode of operation can be also configured by disabling Cabal flagtasty
.
Command-line options
Use --help
to list all command-line options.
-
-p
,--pattern
This is a standard
tasty
option, which allows filtering benchmarks by a pattern orawk
expression. Please refer totasty
documentation for details. -
-t
,--timeout
This is a standard
tasty
option, setting timeout for individual benchmarks in seconds. Use it when benchmarks tend to take too long:tasty-bench
will make an effort to report results (even if of subpar quality) before timeout. Setting timeout too tight (insufficient for at least three iterations) will result in a benchmark failure. One can adjust it locally for a group of benchmarks, e. g.,localOption (mkTimeout 100000000)
for 100 seconds. -
--stdev
Target relative standard deviation of measurements in percents (5% by default). Large values correspond to fast and loose benchmarks, and small ones to long and precise. It can also be adjusted locally for a group of benchmarks, e. g.,
localOption (RelStDev 0.02)
. If benchmarking takes far too long, consider setting--timeout
, which will interrupt benchmarks, potentially before reaching the target deviation. -
--csv
File to write results in CSV format.
-
--baseline
File to read baseline results in CSV format (as produced by
--csv
). -
--fail-if-slower
,--fail-if-faster
Upper bounds of acceptable slow down / speed up in percents. If a benchmark is unacceptably slower / faster than baseline (see
--baseline
), it will be reported as failed. Can be used in conjunction with a standardtasty
option--hide-successes
to show only problematic benchmarks. Both options can be adjusted locally for a group of benchmarks, e. g.,localOption (FailIfSlower 0.10)
. -
--svg
File to plot results in SVG format.
-
--time-mode
Whether to measure CPU time (
cpu
, default) or wall-clock time (wall
). -
+RTS -T
Estimate and report memory usage.
Custom command-line options
As usual with tasty
, it is easy to extend benchmarks with custom command-line options.
Here is an example:
import Data.Proxy
import Test.Tasty.Bench
import Test.Tasty.Ingredients.Basic
import Test.Tasty.Options
import Test.Tasty.Runners
newtype RandomSeed = RandomSeed Int
instance IsOption RandomSeed where
defaultValue = RandomSeed 42
parseValue = fmap RandomSeed . safeRead
optionName = pure "seed"
optionHelp = pure "Random seed used in benchmarks"
main :: IO ()
main = do
let customOpts = [Option (Proxy :: Proxy RandomSeed)]
ingredients = includingOptions customOpts : benchIngredients
opts <- parseOptions ingredients benchmarks
let RandomSeed seed = lookupOption opts
defaultMainWithIngredients ingredients benchmarks
benchmarks :: Benchmark
benchmarks = bgroup "All" []