Safe Haskell | None |
---|---|
Language | Haskell2010 |
Introduction
perf
provides high-resolution measurements of the runtime of Haskell functions. It does so by reading the RDTSC register (TSC stands for "time stamp counter"), which is present on all x86 CPUs since the Pentium architecture.
With perf
the user may measure both pure and effectful functions, as shown in the Example below. Every piece of code the user may want to profile is passed as an argument to the perf
function, along with a text label (that will be displayed in the final summary) and the measurement function (e.g. cycles
, cputime
or realtime
).
PerfT
is a monad transformer designed to collect performance information.
The transformer can be used to add performance measurent to existing code using Measure
s.
Example :
Code block to be profiled :
result <- do txt <- readFile "examples/examples.hs" let n = Text.length txt let x = foldl' (+) 0 [1..n] putStrLn $ "sum of one to number of characters is: " <> (show x :: Text) pure (n, x)
The same code, instrumented with perf
:
(result', ms) <- runPerfT $ do txt <- perf "file read" cycles $ readFile "examples/examples.hs" n <- perf "length" cycles $ pure (Text.length txt) x <- perf "sum" cycles $ pure (foldl' (+) 0 [1..n]) perf "print to screen" cycles $ putStrLn $ "sum of one to number of characters is: " <> (show x :: Text) pure (n, x)
Running the code produces a tuple of the original computation results, and a Map of performance measurements that were specified. Indicative results:
file read 4.92e5 cycles length 1.60e6 cycles print to screen 1.06e5 cycles sum 8.12e3 cycles
Note on RDTSC
Measuring program runtime with RDTSC comes with a set of caveats, such as portability issues, internal timer consistency in the case of multiprocessor architectures, and flucturations due to power throttling. For more details, see : https://en.wikipedia.org/wiki/Time_Stamp_Counter
Synopsis
- data PerfT m b a
- type Perf b a = PerfT Identity b a
- perf :: (MonadIO m, Num b) => Text -> Measure m b -> m a -> PerfT m b a
- perfN :: (MonadIO m, Monoid b) => Int -> Text -> Measure m b -> m a -> PerfT m b a
- runPerfT :: PerfT m b a -> m (a, Map Text b)
- evalPerfT :: Monad m => PerfT m b a -> m a
- execPerfT :: Monad m => PerfT m b a -> m (Map Text b)
- module Perf.Cycle
- module Perf.Measure
Documentation
PerfT is polymorphic in the type of measurement being performed. The monad stores and produces a Map of labelled measurement values
perf :: (MonadIO m, Num b) => Text -> Measure m b -> m a -> PerfT m b a Source #
Lift a monadic computation to a PerfT m, providing a label and a Measure
.
perfN :: (MonadIO m, Monoid b) => Int -> Text -> Measure m b -> m a -> PerfT m b a Source #
Lift a monadic computation to a PerfT m, and carry out the computation multiple times.
runPerfT :: PerfT m b a -> m (a, Map Text b) Source #
Consume the PerfT layer and return a (result, measurement).
>>>
:set -XOverloadedStrings
>>>
(cs, result) <- runPerfT $ perf "sum" cycles (pure $ foldl' (+) 0 [0..10000])
(50005000,fromList [("sum",562028)])
evalPerfT :: Monad m => PerfT m b a -> m a Source #
Consume the PerfT layer and return the original monadic result. Fingers crossed, PerfT structure should be completely compiled away.
>>>
result <- evalPerfT $ perf "sum" cycles (pure $ foldl' (+) 0 [0..10000])
50005000
execPerfT :: Monad m => PerfT m b a -> m (Map Text b) Source #
Consume a PerfT layer and return the measurement.
>>>
cs <- execPerfT $ perf "sum" cycles (pure $ foldl' (+) 0 [0..10000])
fromList [("sum",562028)]
module Perf.Cycle
module Perf.Measure