Improving Random
Carter Schonwald
carter.schonwald at gmail.com
Tue Jun 2 18:32:17 UTC 2020
It’s worth also mentioning that my previous 1.2 wip stuff was using
splitmix as the suggested default Splittable too.
The proposal has a number of nice ideas. And a number of things that I’m
reflecting on how to tweak or align with my own thoughts because I think
it’s wrong but I’m not 100% on what approach is best yet. Just that the
current one proposed or that random currently has is not !
I’m taking my time with this because even under ideal circumstances rng
algorithms can have hard to see issues, and all the weirdness going on in
the world right now doesn’t lend itself to speedy clear thinking so I’m
being doubly careful to figure out how to communicate and factor this work.
On Mon, Jun 1, 2020 at 7:26 AM Markert, Leonhard <leonhard.markert at tweag.io>
wrote:
> Thank you, Simon! I am keen to see the improvements we've been working on
> released for others to use.
>
> I just wanted to mention Oleg Grenrus (@phadej) here - the proposed random
> v1.2 uses his fast, pure-Haskell SplitMix implementation
> <https://hackage.haskell.org/package/splitmix> as its default PRNG.
>
> On Mon, Jun 1, 2020 at 12:55 PM Simon Peyton Jones via Libraries <
> libraries at haskell.org> wrote:
>
>> Friends
>>
>>
>>
>> Random number generation lies far outside my expertise, but I know it to
>> be an area where it’s easy to mess up, either in performance or in
>> generating genuinely random numbers. So I’m delighted that Dominic and his
>> colleagues have been working so hard on this. We all owe them a debt of
>> thanks. Good RNGs are at the beating heart of many other algorithms, but
>> are rather un-loved as an object of study in their own right.
>>
>>
>>
>> So thank you Dominic, @curiousleo @lehins -- and indeed Guy Steele and
>> colleagues, on whose work this is based. We don’t often get perf boosts of
>> 1000x!
>>
>>
>>
>> I hope that that, after suitable scrutiny and refinement if necessary,
>> this ends up being accepted.
>>
>>
>>
>> Simon
>>
>>
>>
>> *From:* Libraries <libraries-bounces at haskell.org> *On Behalf Of *
>> dominic at steinitz.org
>> *Sent:* 26 May 2020 11:00
>> *To:* libraries <libraries at haskell.org>
>> *Cc:* Alexey Kuleshevich <alexey at kuleshevi.ch>
>> *Subject:* Improving Random
>>
>>
>>
>> Hello Libraries,
>>
>> You may recall that following the blog post
>> <https://alexey.kuleshevi.ch/blog/2019/12/21/random-benchmarks/> by
>> @lehins, a group of us (@curiousleo, @lehins and me) invited participation
>> in February
>> <https://mail.haskell.org/pipermail/libraries/2020-February/030261.html>
>> to take this work and apply it to improving the current random library.
>>
>> Our proximate goals were to fix #25
>> <https://github.com/haskell/random/issues/25> (filed in 2015) and #51
>> <https://github.com/haskell/random/issues/51> (filed in 2018). After a
>> lot of discussion and experimentation, we have a proposal that addresses
>> both these issues and also: #26
>> <https://github.com/haskell/random/issues/26>, #44
>> <https://github.com/haskell/random/issues/44>, #53
>> <https://github.com/haskell/random/issues/53>, #55
>> <https://github.com/haskell/random/issues/55>, #58
>> <https://github.com/haskell/random/issues/58> and #59
>> <https://github.com/haskell/random/issues/59>.
>>
>> For backwards compatibility, the proposal retains the old style classes
>> and enhances them. Thus in 1.1 we have
>>
>> class RandomGen g where
>>
>> next :: g -> (Int, g)
>>
>> genRange :: g -> (Int, Int)
>>
>> split :: g -> (g, g)
>>
>> {-# MINIMAL next, split #-}
>>
>> and in 1.2 we have
>>
>> class RandomGen g where
>>
>> next :: g -> (Int, g)
>>
>> genWord8 :: g -> (Word8, g)
>>
>> genWord16 :: g -> (Word16, g)
>>
>> genWord32 :: g -> (Word32, g)
>>
>> genWord64 :: g -> (Word64, g)
>>
>> genWord32R :: Word32 -> g -> (Word32, g)
>>
>> genWord64R :: Word64 -> g -> (Word64, g)
>>
>> genShortByteString :: Int
>>
>> -> g -> (Data.ByteString.Short.Internal.ShortByteString, g)
>>
>> genRange :: g -> (Int, Int)
>>
>> split :: g -> (g, g)
>>
>> {-# MINIMAL split, (genWord32 | genWord64 | next, genRange) #-}
>>
>> and next and genRange are deprecated. This interface is what allows the
>> significantly faster performance as no longer is everything forced to go
>> via Integer.
>>
>> Several new interfaces are introduced and it is recommended that new
>> applications use these and, where feasible, existing applications migrate
>> to using them.
>>
>> The major API addition in this PR is the definition of a new class
>> MonadRandom:
>>
>> -- | 'MonadRandom' is an interface to monadic pseudo-random number generators.
>>
>> class Monad m => MonadRandom g s m | g m -> s where
>>
>> {-# MINIMAL freezeGen,thawGen,(uniformWord32|uniformWord64) #-}
>>
>>
>>
>> type Frozen g = (f :: Type) | f -> g
>>
>> freezeGen :: g s -> m (Frozen g)
>>
>> thawGen :: Frozen g -> m (g s)
>>
>>
>>
>> uniformWord32 :: g s -> m Word32 -- default implementation in terms of uniformWord64
>>
>> uniformWord64 :: g s -> m Word64 -- default implementation in terms of uniformWord32
>>
>> -- plus methods for other word sizes and for byte strings
>>
>> -- all have default implementations so the MINIMAL pragma holds
>>
>> Conceptually, in MonadRandom g s m, g s is the type of the generator, s
>> is the state type, and m the underlying monad. Via the functional
>> dependency g m -> s, the state type is determined by the generator and
>> monad.
>>
>> Frozen is the type of the generator's state "at rest". It is defined as
>> an injective type family via f -> g, so there is no ambiguity as to
>> which g any Frozen g belongs to.
>>
>> This definition is generic enough to accommodate, for example, the Gen
>> type from mwc-random, which itself abstracts over the underlying
>> primitive monad and state token. This is the full instance declaration
>> (provided here as an example - this instance is not part of random as
>> random does not depend on mwc-random):
>>
>> instance (s ~ PrimState m, PrimMonad m) => MonadRandom MWC.Gen s m where
>>
>> type Frozen MWC.Gen = MWC.Seed
>>
>> freezeGen = MWC.save
>>
>> thawGen = MWC.restore
>>
>>
>>
>> uniformWord8 = MWC.uniform
>>
>> uniformWord16 = MWC.uniform
>>
>> uniformWord32 = MWC.uniform
>>
>> uniformWord64 = MWC.uniform
>>
>> uniformShortByteString n g = unsafeSTToPrim (genShortByteStringST n (MWC.uniform g))
>>
>> Pure random number generators can also be made instances of this class
>> providing a uniform interface to both pure and stateful random number
>> generators. An instance for the standard number generator StdGen is
>> provided.
>>
>> The Random typeclass has conceptually been split into Uniform and
>> UniformRange. The Random typeclass is still included for backwards
>> compatibility. Uniform is for types where it is possible to sample from
>> the type's entire domain; UniformRange is for types where one can sample
>> from a specified range:
>>
>> class Uniform a where
>>
>> uniformM :: MonadRandom g s m => g s -> m a
>>
>>
>>
>> class UniformRange a where
>>
>> uniformRM :: MonadRandom g s m => (a, a) -> g s -> m a
>>
>> The proposal is a breaking change but the changes are not very intrusive
>> and we have PRs ready for the affected downstream libraries:
>>
>> - requires base >= 4.10 (GHC-8.2)
>> - StdGen is no longer an instance of Read
>> - randomIO and randomRIO were extracted from the Random class into
>> separate functions
>>
>> In addition, there may be import clashes with new functions, e.g. uniform
>> and uniformR.
>>
>> Further explanatory details may be found here
>> <https://github.com/idontgetoutmuch/random/blob/v1.2-release-notes/RELEASE-NOTES-v1.2.md#api-changes>
>> and the PR for the proposed new version is here
>> <https://github.com/haskell/random/pull/61>.
>>
>> Here are some benchmarks run on a 3.1 GHz Intel Core i7. The full
>> benchmarks can be run using e.g. stack bench. The benchmarks are
>> measured in milliseconds per 100,000 generations. In some cases, the
>> performance is over x1000(!) times better; the minimum performance increase
>> for the types listed below is more than x35.
>>
>> | Name | Mean (1.1) | Mean (1.2) | Improvement|
>>
>> | ----------------------- | ---------- | ---------- | ---------- |
>>
>> | pure/random/Float | 30 | 0.03 | 1038|
>>
>> | pure/random/Double | 52 | 0.03 | 1672|
>>
>> | pure/random/Integer | 43 | 0.33 | 131|
>>
>> | pure/uniform/Word8 | 14 | 0.03 | 422|
>>
>> | pure/uniform/Word16 | 13 | 0.03 | 375|
>>
>> | pure/uniform/Word32 | 21 | 0.03 | 594|
>>
>> | pure/uniform/Word64 | 42 | 0.03 | 1283|
>>
>> | pure/uniform/Word | 44 | 0.03 | 1491|
>>
>> | pure/uniform/Int8 | 15 | 0.03 | 511|
>>
>> | pure/uniform/Int16 | 15 | 0.03 | 507|
>>
>> | pure/uniform/Int32 | 22 | 0.03 | 749|
>>
>> | pure/uniform/Int64 | 44 | 0.03 | 1405|
>>
>> | pure/uniform/Int | 43 | 0.03 | 1512|
>>
>> | pure/uniform/Char | 17 | 0.49 | 35|
>>
>> | pure/uniform/Bool | 18 | 0.03 | 618|
>>
>> | pure/uniform/CChar | 14 | 0.03 | 485|
>>
>> | pure/uniform/CSChar | 14 | 0.03 | 455|
>>
>> | pure/uniform/CUChar | 13 | 0.03 | 448|
>>
>> | pure/uniform/CShort | 14 | 0.03 | 473|
>>
>> | pure/uniform/CUShort | 13 | 0.03 | 457|
>>
>> | pure/uniform/CInt | 21 | 0.03 | 737|
>>
>> | pure/uniform/CUInt | 21 | 0.03 | 742|
>>
>> | pure/uniform/CLong | 43 | 0.03 | 1544|
>>
>> | pure/uniform/CULong | 42 | 0.03 | 1460|
>>
>> | pure/uniform/CPtrdiff | 43 | 0.03 | 1494|
>>
>> | pure/uniform/CSize | 43 | 0.03 | 1475|
>>
>> | pure/uniform/CWchar | 22 | 0.03 | 785|
>>
>> | pure/uniform/CSigAtomic | 21 | 0.03 | 749|
>>
>> | pure/uniform/CLLong | 43 | 0.03 | 1554|
>>
>> | pure/uniform/CULLong | 42 | 0.03 | 1505|
>>
>> | pure/uniform/CIntPtr | 43 | 0.03 | 1476|
>>
>> | pure/uniform/CUIntPtr | 42 | 0.03 | 1463|
>>
>> | pure/uniform/CIntMax | 43 | 0.03 | 1535|
>>
>> | pure/uniform/CUIntMax | 42 | 0.03 | 1493|
>>
>>
>>
>> Dominic Steinitz
>>
>> dominic at steinitz.org
>>
>> http://idontgetoutmuch.org
>>
>> Twitter: @idontgetoutmuch
>>
>>
>>
>>
>>
>>
>>
>>
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>>
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