- Haskell-Cafe - Haskell.org

Is protocol-buffers package maintainer reachable?
by Chris Kuklewicz 19 May '12

19 May '12

To those looking for me: I live! And I got reminded to get back in touch via http://www.well-typed.com/blog/66 (kudos to them!). protocol-buffers is updated, now on to regex-*

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Protocol Buffers 2.0.7
by Chris Kuklewicz 19 May '12

19 May '12

I have returned from the shadows of the intenet to maintain some packages! Version 2.0.7 of protocol-buffers (3 packages) has been uploaded to hackage. This makes it compile with ghc-7.4.1 and handle missing package names better. Thanks to everyone who sent email and patches, including Nathan Howell, Alexey Khudyakov, Howard B. Golden, Bryan O'Sullivan, Michael Stone, Daniel Rebelo de Oliveira, Paul Graphov, Tsurann, Sergei Trofimovich, Yitzchak Gale. The usual hackage links: http://hackage.haskell.org/package/hprotoc http://hackage.haskell.org/package/protocol-buffers-descriptor http://hackage.haskell.org/package/protocol-buffers And the darcs repo is at: http://code.haskell.org/protocol-buffers/ Q: What is protocol-buffers? A: It is a Haskell version of Google's protocol buffer wire protocol, see http://code.google.com/p/protobuf/ for a full description. Q: What does the hprotoc executable do? A: It convers "protocol-buffer descriptor files" into Haskell code to implement those data messages. Q: What does the protocol-buffers library do? A: It is the runtime API for using the binary protocol, serializing and deserializing the data types generated by hprotoc. Q: What is the protocol-buffers-descriptor library do? A: It is the support library for parsing "protocol-buffer descriptor files" into data structures. Most of this code is generated by hprotoc from a "protocol-buffer descriptor file" for "protocol-buffer descriptor files". Yes, it had to be bootstrapped. -- Dr. Chris Kuklewicz

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ANNOUNCE: time-lens-0.1
by Roman Cheplyaka 19 May '12

19 May '12

I'm happy to announce the first, experimental version of the time-lens library. http://hackage.haskell.org/package/time-lens https://github.com/feuerbach/time-lens Its goal is to simplify working with time and date data structures in Haskell by providing lens-based overloaded accessors for Data.Time types. E.g. to find the current hour you currently need to write something like todHour . localTimeOfDay . zonedTimeToLocalTime <$> getZonedTime With time-lens it becomes getL hours <$> getZonedTime The difference is even more impressive when you need to *update* the hour in a ZonedTime structure, but admittedly such a need is relatively rare. The library is pure Haskell 2010 code. It is also completely type-compatible with Data.Time, so it's very easy to start using it in existing projects. -- Roman I. Cheplyaka :: http://ro-che.info/

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Re: [Haskell-cafe] Can Haskell outperform C++?
by Janis Voigtländer 19 May '12

19 May '12

Am 19.05.2012 12:00, schrieb wren ng thornton: > Exactly. That's what I was trying to get at re the problems of comparing > Haskell to C++ (or indeed any pair of dissimilar languages). A > legitimate comparison will involve far more than microbenchmarks, but > then a legitimate comparison must always have a specific focus and > context in order to be able to say anything interesting. The problems I > see in language comparisons is that by and large they tend not to have > any such focus[1], and consequently they shed little light on how the > languages compare and shed a bit of darkness by serving only to confirm > initial biases. > > > [1] A nice counter-example to this trend are papers like: > > http://www.cse.unsw.edu.au/~chak/papers/modules-classes.pdf > > There was another one comparing the expressivity of Java-style > polymorphism vs Haskell-style polymorphism, based on an analysis of > in-the-wild code; but I can't seem to pull it up at the moment. Possibly "Software extension and integration with type classes" by Lämmel and Ostermann? http://doi.acm.org/10.1145/1173706.1173732 Best, Janis. -- Jun.-Prof. Dr. Janis Voigtländer http://www.iai.uni-bonn.de/~jv/

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Can Haskell outperform C++?
by Isaac Gouy 19 May '12

19 May '12

Wed May 16 16:40:26 CEST 2012, Gregg Lebovitz wrote: 2) ... I think the problem with current comparisons, is that they are designed to favor imperative languages. Please be specific: - Which current comparisons? - How do you know what they are designed to favor?

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Re: [Haskell-cafe] AI - machine learning
by C Gosch 18 May '12

18 May '12

Hi all, I have implemented max-sum/sum-product in c++ before and a while ago, did the same in Haskell. I don't think my implementation is as idiomatic Haskellish as I would like, and I have so far not published it and also not looked at it for a little while (since I have some more projects :) ). However, if you are interested, I will publish it (maybe on github?), and I think we should join forces. I am also very interested in machine learning techniques, but I can unfortunately use neither those nor Haskell at my day job at present. Let me know what you think. Best regards, Christian Message: 3 Date: Thu, 17 May 2012 15:36:08 +0400 From: Paul Graphov <graphov(a)gmail.com> Subject: Re: [Haskell-cafe] AI - machine learning To: miro <miroslav.karpis(a)gmail.com> Cc: haskell-cafe(a)haskell.org Message-ID: <CAKHAQn%2ByFGCdLPoKR0sEhvJobwPPykvqTYieqZeBbzhyVodizg(a)mail.gmail.com> Content-Type: text/plain; charset=UTF-8 Hi Miro! I have no useful information for you. Few weeks ago I also checked for any AI (machine learning first of all) related packages exist and found nothing satisfactory except for some quite small packages implementing a single algorithm (like NN-back-propagation). So there is a lot to do :) If you are going to do something in this area please let me know, I'll be glad to collaborate! p.s. Now I'm taking Machine Learning course at Coursera.org and looking forward to apply this knowledge with Haskell. On Tue, May 15, 2012 at 3:02 AM, miro <miroslav.karpis(a)gmail.com> wrote: > Hi All, recently I started to take a look at haskell, especially at AI. I > can see some email addresses of interested people there but not so much of > other activity behind. Does it exist some mailing group especially for AI? > > Basically I'm interested in trying some machine learning algorithms. Start > with reinforcement learning and value-based), and go towards AGI (Artificial > General Intelligence). Does anybody know about some already existing haskell > approaches, or is there anybody working on this? > > Cheers, > m.

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How to use Plugins package?
by Андрей Янкин 18 May '12

18 May '12

Hi, I'm newbie and I've got a problem. I'm trying to get example programs from plugins-auto [1] or hotswap [2] to work. I think question on stackoverflow [3] somewhat related to my problem. They are compiled well, but in runtime I get either segfault or Prelude.undefined or internal error: PAP object entered! I use GHC 7.4.1. x86_64 Ubuntu I've read "Plugging Haskell In" and would like to make some fun with plugins, but alas... Maybe -dynamic flag is what I seek? Or maybe I need to know something else? Maybe I needn't use Plugins package like in gitit? Please, could you explain how to compile plugins in haskell correctly? Where should I start? [1] http://hackage.haskell.org/package/plugins-auto [2] http://hackage.haskell.org/package/hotswap [3] http://stackoverflow.com/questions/5427777/help-with-haskell-dynamic-plugin…

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Parallel Haskell Digest 10
by Eric Kow 18 May '12

18 May '12

Hello Haskellers! Did you see Ambassador Peyton Jones in Scala land? Simon was recently at ScalaDays 2012 (a large gathering for professional Scala users) giving a [keynote talk on Cloud Haskell][v1] (one hour video). Cloud Haskell is a pretty exciting new development in the Haskell space, providing the beginnings of a story for distributed programming in Haskell. It's also one of the areas we're focused on over the Parallel GHC project, building a new implementation to replace the current prototype. We're looking forward to talking a bit more about Cloud Haskell in the next (and final) edition of the digest. Wait, did I say just **final**? Indeed, by the next digest, we'll be wrapping up the Parallel GHC project. In addition to a bit more Cloud Haskell material, we'll give a little recap of the things we and our partners worked on over the two years. It's been fun! Meanwhile, in this penultimate edition, we'll be taking a look at concurrent *channels* as our word of month. We also have new parallel Haskell book to look forward to, an update to Accelerate, the new `meta-par` family of packages to look at, and also a lot of recent activity on StackOverflow. (For fancy HTML version and images, see http://www.well-typed.com/blog/66 ) News ---------------------------------------------------------------------- * [GSoC: concurrent hashtables][n0] Loren Davis and 7 other students have been accepted to the Google Summer of Code project under Haskell.org. Loren will be working to [implement concurrent thread-safe mutable hash-table][n0]. Congratulations and best of luck to Loren, Aditya, David, Mark, Mikhail, Phillip, Shae, and Shayan. Hope it's a fun summer! * [Lectureship in Computer Science - Saint Andrews][n3] Kevin Hammond urges us to consider applying for this lecturship in functional programming (closing date 22 June) at the University of Saint Andrews: We seek lectureship applications from researchers who have a strong research background and excellent publication record in any area of functional programming, complementing and enhancing the existing research team, which has a strong focus on parallel programming models and implementation, resource-aware functional programming, dependent type systems, refactoring, static analysis, and performance modelling, and deep connections with the Haskell community. * [O'Reilly book on Parallel and Concurrent Haskell][n4] (17 May) Haskell is getting a third O'Reilly book! Joining the introductory [Real World Haskell][rwh], and web-oriented [Haskell and Yesod][yesod-book], will be a forthcoming book on parallelism and concurrency in Haskell (tentative completion date March 2013). Simon Marlow will building this book off his [CEFP 2012 tutorial][sm-cefp] tutorial. He's “really keen for this to be a book that will be useful to people both learning about parallelism and concurrency in Haskell, and coding stuff for real-world use.” Please let him know if you have suggestions for topics or application areas you'd like covered. ## Conferences * [Erlang Workshop (due 3 Jun, workshop 14 Sep)][n1] Haskell has been borrowing from Erlang lately (Cloud Haskell!). John Hughes suggests, “Why not adapt some cool Haskell ideas to Erlang too?” The Eleventh ACM SIGPLAN Erlang Workshop will take place this year in Copenhagen, Denmark on the tail end of the ICFP. Just two weeks to go! * [Facing the Multicore-Challenge III (19-21 Sep)][n2] And if ICFP isn't enough for you, how about this Conference for Young Scientists, just a few days after? The Hochschule für Technik, will hosting the third multicore-challenge conference in Stuttgart, Germany, from 19-21 September. It aims to combine new aspects of multi-/manycore microprocessor technologies, parallel applications, numerical simulation, software development and tools. Contributions are welcome from all participating disciplines. Particular emphasis is placed on the support and advancement of young scientists. Word of the month ---------------------------------------------------------------------- This month, we'll be taking a short breather in our exploration of the Haskell concurrency space, and fleshing out some of the uses for the tools we already have. In the past two digests, we saw how Haskell provides *locks* for low-level concurrency, and the vastly safer *transactions* for concurrency at a higher level. Both approaches give us the notion of a typed mutable variables, the idea being that an `MVar Int` would hold a locked integer, whereas a `TVar Int` would hold instead hold transactional reference to an integer. These variables can hold arbitrarily complex things of arbitrary type; you could have anything from a `TVar Char` to a `TVar Customer` (where `Customer` would be some record you've defined in your application). Now that we have mutable variables, it's worth thinking a bit harder about what we might actually put into them. Suppose you find yourself in a typical producer/consumer scenario, for example, with a web service that automatically marks student essays, and which is broken into a piece that accepts submissions (producer) and which passes them on to the core essay-marking engine (consumer). So the producer generates essays and the consumer eats them up and does some work on them; how do we get them talking to each other? It's not enough to just use a single `TVar` because we want the producer to be able to continue cranking out essays whilst the consumer is working, rather than waiting for it to finish. We assume here that essay-marking is a fairly clever and computationally expensive process, and for this reason, we would want some kind of backlog that the producer can tack things on to, and the consumer can pull things off of. As such, our word of the month is *channel*. The unbounded channel abstraction is something that you can fairly easily implement out of either the locky `MVar`'s or transactional `TVar`'s, but we'll focus on the latter as transactions are just so much more civilised (though the same concepts would mostly apply). In the STM world, channels look a little like the following: -- Control.Concurrent.STM.TChan data TChan a newTChan :: STM (TChan a) writeTChan :: TChan a -> a -> STM () readTChan :: TChan -> STM a In the same fashion as the `TVar`'s that we introduced last time, `TChan`'s are parameterised with a type variable, meaning that you could have a channel of characters with `TChan Char`, or a channel of customers with `TChan Customer`, and so forth. Creating, reading, and writing to a channel are all transactions (i.e., in the the STM monad). Revisiting our essay marking service, we can sketch out how these channels might be used: import Control.Concurrent.STM.TChan main :: IO () main = do chan <- newTChan forkIO (producer chan) forkIO (consumer chan) forever $ return () producer :: TChan Essay -> IO () producer chan = forever $ do essay <- magicalWebFrameworkStuff atomically $ writeTChan chan essay consumer :: TChan Essay -> IO () consumer chan = forever $ do essay <- atomically $ readTChan chan mark essay mark :: Essay -> IO () mark essay = putStrLn "Let me think..." -- State-of-the-art marking technology, -- just $25000 per site license randomRIO (1, 10000000) >>= threadDelay pass <- randomIO if pass then putStrLn "Pass, good job!" eles putStrLn "Fail!" And that's it! Using concurrent channels does not get more complicated or deeper than this. You may have noticed that in this particular example, we have not really gained (or for that matter lost) that much from sticking to the transactional version of channels. Using the locky `MVar` version would basically consist of dropping the `atomically`'s, importing from `Control.Concurrent.Chan`, and using `Chan` instead of `TChan`. Now that we have a bit of an idea what channels are about, it could be worthwhile to consider what it really offers over simpler alternatives. For example, in the introduction we rejected the idea of just using a single `TVar` because this would force our producer and consumers to wait on each other for each and every essay, rather than going about their asynchronously merry ways. So we know we want something *like* channels, but how exactly do we go about building them? For starters, wouldn't we get a channel structure by just wrapping `Data.Sequence.Seq` with a single `TVar`? It could be made to work as we are using STM (it simply wouldn't work if we were using `MVar`'s instead; consider the empty channel), but it would leave us with the unfortunately inability to simultaneously read from and write to the channel. These operations would have to grab a hold of the whole queue, leaving the other to retry until later. It would a little sad not to enable this bit of concurrency, considering that that reading and writing take place at opposite ends of the queue, the reader walking along trying to keep up with the writer. Instead of naively wrapping a queue, the current implementation uses a sort of linked list with `TVar`'ed cons cells and `TVar`'s pointing to both the beginning (the read end) and the end of the list (the write end). Here are the data structures that make up a channel: type TVarList a = TVar (TList a) data TList a = TNil | TCons a (TVarList a) data TChan a = TChan (TVar (TVarList a)) -- read end (TVar (TVarList a)) -- write end It can be a little bit tricky to think about because we've got `TVar`'s wrapping around things that eventually wrap around `TVar`'s themselves. It's a whole chain of `TVar`'s, and if you can have a `TVar a`, there's no reason not to have a `TVar (TVar a)`. If that feels a bit shaky, try implementing channels yourself as a quick little exercise. We'll speed things along with a handful of pictures to illustrate how it might work. First, our visual language for talking about `TVar`'ed cons cells: ![TChan legend](channel-legend.png) A new channel has three `TVar`'s, one for the linked list (it points to `TNil`), and a pair of read/write ones pointing to this pointer: ![new TChan](channel-new.png) Writing the channel involves adding to the list and moving the write pointer to the new tail of the list: ![write TChan](channel-write.png) And finally reading those items off the channel involves moving the read pointer forward: ![read TChan](channel-read.png) The implementation should be fairly straightforward from the pictures, although one place you might get stuck when trying to read from an empty channel. After all, how do you return a value from a channel that doesn't have any, especially since you're expected to return plain old `a` instead of `Maybe a`? Well, sometimes you just gotta wait. We briefly glossed over this in our taste of STM in the [last word of the month][ph-digest-9], but STM offers a `retry` function simply causes a transaction to be aborted and tried again. Using this notion of blocking, you should be able to get a `readTChan` that waits until there is something to be read. Hopefully, the exercise of implementing channels will be a useful reminder to think of the concurrency abstractions that Haskell provides (threads, transactional mutable variables) as primitives on top of which you can build more interesting and useful abstractions. For a little more fun, head over to Simon Marlow's [tutorial on parallelism and concurrency][tutorial-sm]. In this tutorial, Simon illustrates the building channels over `MVar`'s (also worth doing) and mentions an easy generalisation to *multicast* channels (one write end, two read ends!) and also a small extension to “unread” a value (pushing it back on to the read end). Both extensions are easy on the surface, but hard to nail down to the exact desired semantics (there's no known correct implementation of the unread extension), at least when you're dealing with locks and `MVar`'s. But if you stick to transactions and `TVar`'s, both wind up being straightforward. Check out his tutorial! Videos ---------------------------------------------------------------------- * [Towards Haskell in the Cloud][v1] (17 Apr, 1 hour) Simon Peyton Jones gave one of the keynote lectures at the recent ScalaDays 2012 in London. Simon sets the stage with some of the recent thinking about how functional programming and parallel programming fit together: that functional is the way forward, but no one single approach is going to cover all scenarios; that cost models are important to keep in mind; and that being able to explore all these different approaches within a single language is a great thing. From here, Simon launches into the heart of his presentation, Cloud Haskell (Scala hackers, think Akka). Cloud Haskell was developed with distributed programming in mind, in other words, large scale, multiple machines, no shared memory. Simon's talk covers quite a bit of ground: the Erlang-style actor model as an explicit embrace of distributed memory; the Haskell typed channels twist; programmer-controlled serialisation with type classes; and finally the longtime big stumper, how we go about serialising functions. It's interesting stuff. And as a sort of side bonus, even if don't walk away with a better idea what Cloud Haskell is all about, you should at least get a concrete sense for how type classes work. Blogs and packages ---------------------------------------------------------------------- * [hpuns: parallel jeux de mots (plays on words)][b2] HPuns is a valuable tool for making your future (French speaking) children's lives miserable. It generates awful puns from names, and in parallel, no less! Paul Brauner was just looking for some parallel “speedups out of the box.“ Where he was previously was able to get only a mediocre speedup with Strategies, with the monad-par package he was able to knock out a quick 1.3x speedup (-N3) over a lunchbreak. HPuns may just be a toy (one file!) but it could be what you're looking for if monad-par usage examples is what you're after. * [Accelerate version 0.12: GPU computing with Haskell][b5] (14 May) Manuel Chakravarty the recent 0.12 release of Accelerate, with full sharing recovery in scalar expressions and array computations, some more examples, and bug fixes. Accelerate should still be considered a beta release, but the folks at UNSW are hungry for early adopters. So do give it a try! * [How to write hybrid CPU/GPU programs with Haskell][b3] (4 May) If you like your monad-par and your Accelerate working together, consider this proposition from Ryan Newton: “What’s better than programming a GPU with a high-level, Haskell-embedded DSL (domain-specific-language)? Well, perhaps writing portable CPU/GPU programs that utilize both pieces of silicon…” Ryan walks us through installing the recently released meta-par packages and writing some simple hybrid code. The general idea seems to be to define CPU and GPU implementations of a task and to allow the generalised work-stealing scheduler to choose between them; the promise being that if a program performs much better on one device (say the GPU), that device will wind up doing most of the work. More generally, the meta-par family of packages is aimed at heterogeneous programming (it provides a mechanism for building parallel schedulers out of "mix-in" components). Ryan's post focuses on the CPU/GPU scenario, but there are also future packages coming our way for distributed programming too. If you are interested in learning more, have a look at the [meta-par GitHub][meta-par] page and the the draft paper [A Meta-Scheduler for the Par-Monad][meta-par-paper]. Mailing lists ---------------------------------------------------------------------- * [Is protocol-buffers package maintainer reachable?][m1] (23 Apr) Paul Graphov finds the protocol-buffers and hprotoc packages failing to build with the latest GHC. Unfortunately, he seems to be having trouble getting his patches to maintainer Chris Kuklewicz. The mailing list thread came up with suggestions for places we might get in touch with Chris, and also touched on a sort of recurring dilemma in the Haskell community: what do we do when package maintainers disappear? The general feeling seems to be that provided we can find a new maintainer, we should discuss it on the mailing list, then go ahead and take over. * [Threads and hGetLine][m5] (28 Apr) H.M. has a simplified scenario he's having trouble with: suppose you have thread waiting on input with `hGetLine`, and you have a supervisor thread to close the handle and/or kill the first thread. How do you make it work? It seems that `hClose` and `killThread` do not work for H. because the first thread is blocking for input. Alvaro Gutierrez suggests perhaps using a different approach which doesn't involve killing threads, perhaps non-blocking IO and a synchronised condition variable. Perhaps H.M. is on Windows? Joey Adams points out that “GHC currently doesn't have proper IO manager support for Windows. On Windows, IO is performed through FFI calls. An FFI call masks asynchronous exceptions… If another thread tries to `killThread` the thread waiting for input, the exception will not be received until the FFI call completes. This means both threads will hang.” * [using ResourceT with MVars][m2] (2 May) Warren Harris would like to use LevelDB (an open source on-disk key-value store inspired by BigTable). Unfortunately for Warren, the 0.0.3 version of leveldb-haskell switches from `get`/`put` in the `IO` monad to `ResourceT`. This makes it tricky for him to write code like withMVar state $ \db -> do maybeValue <- get db rdOpts key put db wrOpts key $ maybe init incr maybeValue In effect, the question is “how do I run MVar operations in ResourceT?” Michael Snoyman suggests the [lifted-based][lifted-base] package for exactly this. Lifted-base exports IO operations from the base library lifted to any instance of `MonadBase` or `MonadBaseControl`. Warren can use any of the `Control.Concurrent.MVar.Lifted` functions since `ResourceT` is an instance of `MonadBaseControl` * [meaning of `__PARALLEL_HASKELL__` and -parallel][m3] (13 Apr) Facundo Domínguez was wondering what the `__PARALLEL_HASKELL__` CPP macro, and the `-parallel` flags stand for. Jost Berthold explains that they both relate to parallel versions of GHC on distributed memory platforms. * [Can Haskell outperform C++?][m4] (6 May) Janek S. has seen claims floating around the internet that Haskell programs can have comparable performance to C and C++ versions. He's also seen claims about the promise of functional programming for automatically parallelising the software. Is there any evidence for these claims? This is a tricky question to pin down, and one that is vulnerable to apple/orange comparisons (some suggestions in the thread, [1][donscore], [2][bfusion], [3][shootout]) or debates about what makes a programming language desirable. Janek's question sparked a fairly epic thread, maybe worth digging through if you're struggled with Haskell performance before; or are member of the shadowy Haskell propaganda committee. For parallel Haskellers, I'll pick out a handful of sub-topics that came up. Ertugrul Söylemez makes a general comment to look at the bigger picture. While (currently) seldomly beats C/C++ for number crunching algorithms, “where [it] really gets beyond C and C++ is in concurrency. Multithreaded network servers written in Haskell are not only a lot easier to write, but they also perform better than well written server programs in C/C++. This is because Haskell's concurrency goes well with its parallel execution model, where in machine code you don't really have a notion of procedures. You have thunks and they can not only be executed in parallel, but they can also be moved between threads freely.” As for automatic parallelisation, Simon Marlow points out that there isn't yet any fully implicit parallelism in Haskell. What Haskell does provide, on the other hand, is a “a guarantee that you can safely call any function in parallel… as long as the function does not have an IO type”. So while fully automatic parallelism isn't here (and may not ever be), you can at least take an arbitrary piece of Haskell code and use it with something like `parMap`, or call it from mulitple threads, and expect some sort of speedup from it; and safely, with a fully deterministic result and no nasty concurrency bugs to worry about. Finally, showing how it can be tricky to performance can be quite tricky, Ryan Newton had an example in his monad-par repo of a (rather C-ish) [aggressively optimised Haskell program][mandel] that was 6⨉ slower than its counterpart and worse 9⨉ with the new LLVM backend (said backend has been helpful in other cases, though, eg. for Manuel Chakravarty). There's a happy ending behind this. After some digging, Ryan uncovered a clever math trick used in the OCaml standard library. Porting it to Haskell makes his program not only faster than OCaml and Scheme but 48% faster than C++ too! Looks like we'll be getting a library patch from Ryan soon. “The moral,” Ryan comments, “is that community members could do a great deal to help "Haskell" performance by simply microbenchmarking and optimizing library routines in base!” StackOverflow and Reddit ---------------------------------------------------------------------- This month saw quite a lot of activity on StackOverflow, largely from [user Clinton][so-clinton] trying to puzzle through STM and other concurrency issues. The STM and `atomicModifyIORef` series of questions could be interesting, at the very least, to see what sorts of things people wonder about when they first run into Haskell concurrency. ## General questions * [Identifying the current HEC for a function in Haskell][s1] * [Haskell parallel computation using an STArray][s2] * [Slowdown when using parallel strategies in Haskell][s3] * [Haskell parallel performance][s4] * [“Monad-friendly” event-based IO][s5] * [Haskell concurrency - is forkIO really nondeterministic?][s6] * [TimeoutManager uses tryPutMVar to put nothing][s8] * [Software transactional memory with a big, shared piece of data][s9] ## STM * [How does TVar work?][sc11] * [Container for Haskell TVars][s7] * [Updating two or more TVars atomically. Possible?][sc10] * [TVar: Preventing starvation][sc9] * [TVar: orElse][sc8] * [Concurrent generic data structure without deadlocks or resource starvation][sc7] * [Concurrent data structure guidelines][sc2] * [“Wait-free” data in Haskell][sc1] ## atomicModifyIORef * [How does 'atomicModifyIORef' work?][sc6] * [Concurrency using simple IORef?][sc5] * [Atomic IO wrapper/laziness?][sc4] * [Attempt at parallel `atomicModifyIORef` implementation][sc3] * [Concurrent data structure guidelines][sc2] ## Reddit * [SPJ talk: Towards Haskell in the Cloud : haskell][r1] * [Revamped Haskell concurrency and parallelism libraries page: from parallel arrays to Cloud Haskell : haskell][r2] Help and Feedback ---------------------------------------------------------------------- If you'd like to make an announcement in the next Haskell Parallel Digest, then get in touch with me, Eric Kow, at <parallel(a)well-typed.com>. Please feel free to leave any comments and feedback! [lifted-base]: http://hackage.haskell.org/package/lifted-base [tutorial-sm]: http://community.haskell.org/~simonmar/par-tutorial.pdf [ph-digest-6]: http://www.well-typed.com/blog/60 [ph-digest-9]: http://www.well-typed.com/blog/65 [so-clinton]: http://stackoverflow.com/users/525980/clinton [meta-par]: https://github.com/simonmar/monad-par/ [meta-par-paper]: http://www.cs.indiana.edu/~rrnewton/papers/meta-par_submission.pdf [donscore]: http://donsbot.wordpress.com/2007/11/29/use-those-extra-cores-and-beat-c-to… [bfusion]: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.90.3166 [mandel]: https://github.com/simonmar/monad-par/blob/662fa05b2839c8a0a6473dc490ead8dd… [shootout]: http://shootout.alioth.debian.org/ [rwh]: http://book.realworldhaskell.org/ [yesodbook]: http://www.yesodweb.com/book [sm-cefp]: http://community.haskell.org/~simonmar/papers/par-tutorial-cefp-2012.pdf [yesod-book]: http://www.yesodweb.com/book [n0]: http://www.google-melange.com/gsoc/project/google/gsoc2012/lorehead/36001 [n1]: http://www.haskell.org/pipermail/haskell/2012-April/023275.html [n2]: http://www.multicore-challenge.org/ [n3]: https://www.vacancies.st-andrews.ac.uk//ViewVacancy.aspx?enc=mEgrBL4XQK0+ld… [n4]: http://www.haskell.org/pipermail/haskell/2012-May/023328.html [b1]: http://www.haskell.org/haskellwiki/Applications_and_libraries/Concurrency_a… [b2]: http://code.google.com/p/hpuns/source/browse/Main.hs [b3]: http://parfunk.blogspot.co.uk/2012/05/how-to-write-hybrid-cpugpu-programs.h… [b4]: http://www.haskell.org/pipermail/haskell-cafe/2012-May/101113.html [b5]: http://justtesting.org/gpu-accelerated-array-computations-in-haskell [v1]: http://skillsmatter.com/podcast/home/haskell-cloud/js-4179 [m1]: http://www.haskell.org/pipermail/haskell-cafe/2012-April/100867.html [m2]: http://www.haskell.org/pipermail/haskell-cafe/2012-May/101027.html [m3]: https://groups.google.com/d/msg/parallel-haskell/kU0Ndl-IH3Y/GoQog9psZJIJ [m4]: http://www.haskell.org/pipermail/haskell-cafe/2012-May/101123.html [m5]: http://www.haskell.org/pipermail/haskell-cafe/2012-April/100988.html [s1]: http://stackoverflow.com/questions/10105127/identifying-the-current-hec-for… [s2]: http://stackoverflow.com/questions/10079710/haskell-parallel-computation-us… [s3]: http://stackoverflow.com/questions/10009361/slowdown-when-using-parallel-st… [s4]: http://stackoverflow.com/questions/9578416/haskell-parallel-performance [s5]: http://stackoverflow.com/questions/10364549/monad-friendly-event-based-io [s6]: http://stackoverflow.com/questions/10247555/haskell-concurrency-is-forkio-r… [s7]: http://stackoverflow.com/questions/10098506/container-for-haskell-tvars [s8]: http://stackoverflow.com/questions/9869763/timeoutmanager-uses-tryputmvar-t… [s9]: http://stackoverflow.com/questions/9547325/software-transactional-memory-wi… [r1]: http://www.reddit.com/r/haskell/comments/t0qg0/spj_talk_towards_haskell_in_… [r2]: http://www.reddit.com/r/haskell/comments/stn2b/revamped_haskell_concurrency… [sc1]: http://stackoverflow.com/questions/10239239/wait-free-data-in-haskell [sc2]: http://stackoverflow.com/questions/10220629/haskell-concurrent-data-structu… [sc3]: http://stackoverflow.com/questions/10203446/haskell-attempt-at-parallel-ato… [sc4]: http://stackoverflow.com/questions/10169434/haskell-atomic-io-wrapper-lazin… [sc5]: http://stackoverflow.com/questions/10115756/haskell-concurrency-using-simpl… [sc6]: http://stackoverflow.com/questions/10102881/haskell-how-does-atomicmodifyio… [sc7]: http://stackoverflow.com/questions/10101861/haskell-concurrent-generic-data… [sc8]: http://stackoverflow.com/questions/10101044/haskell-tvar-orelse [sc9]: http://stackoverflow.com/questions/10099990/haskell-tvar-preventing-starvat… [sc10]: http://stackoverflow.com/questions/10099815/haskell-updating-two-or-more-tv… [sc11]: http://stackoverflow.com/questions/10092655/haskell-how-does-tvar-work -- Eric Kow <http://erickow.com>

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Data Kinds and superfluous (in my opinion) constraints contexts
by Serguey Zefirov 17 May '12

17 May '12

I decided to take a look at DataKinds extension, which became available in GHC 7.4. My main concerns is that I cannot close type classes for promoted data types. Even if I fix type class argument to a promoted type, the use of encoding function still requires specification of context. I consider this an omission of potentially very useful feature. Example is below. ----------------------------------------------------------------------------------------- {-# LANGUAGE TypeOperators, DataKinds, TemplateHaskell, TypeFamilies, UndecidableInstances #-} {-# LANGUAGE GADTs #-} -- a binary numbers. infixl 5 :* data D = D0 | D1 | D :* D deriving Show -- encoding for them. data EncD :: D -> * where EncD0 :: EncD D0 EncD1 :: EncD D1 EncDStar :: EncD (a :: D) -> EncD (b :: D) -> EncD (a :* b) -- decode of values. fromD :: D -> Int fromD D0 = 0 fromD D1 = 1 fromD (d :* d0) = fromD d * 2 + fromD d0 -- decode of encoded values. fromEncD :: EncD d -> Int fromEncD EncD0 = 0 fromEncD EncD1 = 1 fromEncD (EncDStar a b) = fromEncD a * 2 + fromEncD b -- constructing encoded values from type. -- I've closed possible kinds for class parameter (and GHC successfully compiles it). -- I fully expect an error if I will try to apply mkD to some type that is not D. -- (and, actually, GHC goes great lengths to prevent me from doing that) -- By extension of argument I expect GHC to stop requiring context with MkD a where -- I use mkD "constant function" and it is proven that a :: D. class MkD (a :: D) where mkD :: EncD a instance MkD D0 where mkD = EncD0 instance MkD D1 where mkD = EncD1 -- But I cannot omit context here... instance (MkD a, MkD b) => MkD (a :* b) where mkD = EncDStar mkD mkD data BV (size :: D) where BV :: EncD size -> Integer -> BV size bvSize :: BV (size :: D) -> Int bvSize (BV size _) = fromEncD size -- ...and here. -- This is bad, because this context will arise in other places, some of which -- are autogenerated and context for them is incomprehensible to human -- reader. -- (they are autogenerated precisely because of that - it is tedious and error prone -- to satisfy type checker.) fromIntgr :: Integer -> BV (size :: D) -- doesn't work, but desired. -- fromIntgr :: MkD size => Integer -> BV (size :: D) -- does work, but is not that useful. fromIntgr int = BV mkD int -----------------------------------------------------------------------------------------

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Fwd: Can Haskell outperform C++?
by Colin Adams 17 May '12

17 May '12

Oops. Forget to reply to all. ---------- Forwarded message ---------- From: Colin Adams <colinpauladams(a)gmail.com> Date: 17 May 2012 08:43 Subject: Re: [Haskell-cafe] Can Haskell outperform C++? To: Roman Werpachowski <roman.werpachowski(a)gmail.com> On 17 May 2012 07:12, Roman Werpachowski <roman.werpachowski(a)gmail.com>wrote: > > It depends on what you use the code for. If I run an overnight report > for the trading book of my bank in 16 hours, it is > not acceptable and is a disaster. If I run it in 8h, it's OK-ish. In > business settings, you often have strict deadlines and > optimizing the code to be 2x faster can make a huge difference, as you > change from missing the deadline to > meeting a deadline. > > Seconded. I remember once being asked to examine a certain batch program for performance improvements. I spotted an obvious inefficiency, and made a recommendation, which was implemented. It saved something like 10 - 30 minutes on the overnight run (which took hours), so I was disappointed with the result. But the client was delighted, as the run now fitted into the batch window.

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