<div dir="ltr">Simon, I certainly want to help get to the bottom of the performance issue at hand :D. Sorry if my reply was misleading. The constant factor overhead of pushing `TVar`s into the internal structure may be pressuring unacceptable GC behavior to happen sooner. My impression was that given the same size problem performance loss shifted from synchronization to GC.<div><br></div><div>Compl, I'm not aware of mutable heap objects being problematic in particular for GHC's GC. There are lots of special cases to handle them of course. I have successfully written Haskell programs that get good performance from the GC with the dominant fraction of heap objects being mutable. I looked a little more at `TSkipList` and one tricky aspect of an STM based skip list is how to manage randomness. In `TSkipList`'s code there is the following comment:</div><div><div><br></div></div><div><pre style="color:rgb(0,0,0)"><span class="gmail-hs-comment" style="color:rgb(138,138,138)">-- | Returns a randomly chosen level. Used for inserting new elements. /O(1)./</span>
<a name="line-98"></a><span class="gmail-hs-comment" style="color:rgb(138,138,138)">-- For performance reasons, this function uses 'unsafePerformIO' to access the</span>
<a name="line-99"></a><span class="gmail-hs-comment" style="color:rgb(138,138,138)">-- random number generator. (It would be possible to store the random number</span>
<a name="line-100"></a><span class="gmail-hs-comment" style="color:rgb(138,138,138)">-- generator in a 'TVar' and thus be able to access it safely from within the</span>
<a name="line-101"></a><span class="gmail-hs-comment" style="color:rgb(138,138,138)">-- STM monad. This, however, might cause high contention among threads.)</span></pre><pre style="color:rgb(0,0,0)"><span class="gmail-hs-comment" style="color:rgb(138,138,138)"><pre style="color:rgb(0,0,0)"><span class="gmail-hs-identifier" style="color:rgb(7,54,66)">chooseLevel</span> <span class="gmail-hs-glyph" style="color:rgb(220,50,47)">::</span> <a href="http://hackage.haskell.org/package/tskiplist-1.0.1/docs/src/Control.Concurrent.STM.TSkipList.Internal.html#TSkipList" class="gmail-" style="text-decoration-line:none;border-bottom:1px solid rgb(238,232,213)"><span class="gmail-hs-identifier gmail-hs-type" style="color:rgb(95,95,175)">TSkipList</span></a> <a href="http://hackage.haskell.org/package/tskiplist-1.0.1/docs/src/Control.Concurrent.STM.TSkipList.Internal.html#local-6989586621679028835" class="gmail-" style="text-decoration-line:none;border-bottom:1px solid rgb(238,232,213)"><span class="gmail-hs-identifier gmail-hs-type" style="color:rgb(95,95,175)">k</span></a> <a href="http://hackage.haskell.org/package/tskiplist-1.0.1/docs/src/Control.Concurrent.STM.TSkipList.Internal.html#local-6989586621679028836" style="text-decoration-line:none;border-bottom:1px solid rgb(238,232,213)"><span class="gmail-hs-identifier gmail-hs-type" style="color:rgb(95,95,175)">a</span></a> <span class="gmail-hs-glyph" style="color:rgb(220,50,47)">-></span> <span class="gmail-hs-identifier gmail-hs-type" style="color:rgb(95,95,175)">Int</span></pre></span></pre></div><div><br></div><div>This level is chosen on insertion to determine the height of the node. When writing my own STM skiplist I found that the details in unsafely accessing randomness had a significant impact on performance. We went with an unboxed array of PCG states that had an entry for each capability giving constant memory overhead in the number of capabilities. `TSkipList` uses `newStdGen` which involves allocation and synchronization.</div><div><br></div><div>Again, I'm not pointing this out to say that this is the entirety of the issue you are encountering, rather, I do think the `TSkipList` library could be improved to allocate much less. Others can speak to how to tell where the time is going in GC (my knowledge of this is likely out of date).</div><div><br></div><div>Ryan</div><div><br></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, Jul 29, 2020 at 4:57 PM Simon Peyton Jones <<a href="mailto:simonpj@microsoft.com">simonpj@microsoft.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
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<p class="MsoNormal"><span>Compl’s problem is (apparently) that execution becomes dominated by GC. That doesn’t sound like a constant-factor overhead from TVars, no matter how efficient (or otherwise) they are. It sounds
more like a space leak to me; perhaps you need some strict evaluation or something.<u></u><u></u></span></p>
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<p class="MsoNormal"><span>My point is only: before re-engineering STM it would make sense to get a much more detailed insight into what is actually happening, and where the space and time is going. We have tools to do this
(heap profiling, Threadscope, …) but I know they need some skill and insight to use well. But we don’t have nearly enough insight to draw meaningful conclusions yet.<u></u><u></u></span></p>
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<p class="MsoNormal"><span>Maybe someone with experience of performance debugging might feel able to help Compl?<u></u><u></u></span></p>
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<p class="MsoNormal"><span>Simon<u></u><u></u></span></p>
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<p class="MsoNormal"><b><span lang="EN-US">From:</span></b><span lang="EN-US"> Haskell-Cafe <<a href="mailto:haskell-cafe-bounces@haskell.org" target="_blank">haskell-cafe-bounces@haskell.org</a>>
<b>On Behalf Of </b>Ryan Yates<br>
<b>Sent:</b> 29 July 2020 20:41<br>
<b>To:</b> YueCompl <<a href="mailto:compl.yue@icloud.com" target="_blank">compl.yue@icloud.com</a>><br>
<b>Cc:</b> Haskell Cafe <<a href="mailto:haskell-cafe@haskell.org" target="_blank">haskell-cafe@haskell.org</a>><br>
<b>Subject:</b> Re: [Haskell-cafe] STM friendly TreeMap (or similar with range scan api) ? WAS: Best ways to achieve throughput, for large M:N ratio of STM threads, with hot TVar updates?<u></u><u></u></span></p>
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Hi Compl,<u></u><u></u></p>
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There is a lot of overhead with TVars. My thesis work addresses this by incorporating mutable constructor fields with STM. I would like to get all that into GHC as soon as I can :D. I haven't looked closely at the `tskiplist` package, I'll take a look and
see if I see any potential issues. There was some recent work on concurrent B-tree that may be interesting to try.<u></u><u></u></p>
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Ryan<u></u><u></u></p>
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<u></u> <u></u></p>
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On Wed, Jul 29, 2020 at 10:24 AM YueCompl <<a href="mailto:compl.yue@icloud.com" target="_blank">compl.yue@icloud.com</a>> wrote:<u></u><u></u></p>
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Hi Cafe and Ryan,<u></u><u></u></p>
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<u></u> <u></u></p>
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I tried Map/Set from stm-containers and TSkipList (added range scan api against its internal data structure) from <a href="https://nam06.safelinks.protection.outlook.com/?url=http%3A%2F%2Fhackage.haskell.org%2Fpackage%2Ftskiplist&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838761589&sdata=ZOvJVBqJgdGqx2k%2F49fhZeTYkWAd4GRY%2B8ZxH7cyEkI%3D&reserved=0" target="_blank">http://hackage.haskell.org/package/tskiplist</a> ,
with them I've got quite improved at scalability on concurrency. <u></u><u></u></p>
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But unfortunately then I hit another wall at single thread scalability over working memory size, I suspect it's because massively more TVars (those being pointers per se) are introduced by those "contention-free" data structures, they need to mutate separate
pointers concurrently in avoiding contentions anyway, but such pointer-intensive heap seems imposing extraordinary pressure to GHC's garbage collector, that GC will dominate CPU utilization with poor business progress. <u></u><u></u></p>
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For example in my test, I use `+RTS -H2g` for the Haskell server process, so GC is not triggered until after a while, then spin off 3 Python client to insert new records concurrently, in the first stage each Python process happily taking ~90% CPU filling (through
local mmap) the arrays allocated from the server and logs of success scroll quickly, while the server process utilizes only 30~40% CPU to serve those 3 clients (insert meta data records into unique indices merely); then the client processes' CPU utilization
drop drastically once Haskell server process' private memory reached around 2gb, i.e. GC started engaging, the server process's CPU utilization quickly approaches ~300%, while all client processes' drop to 0% for most of the time, and occasionally burst a
tiny while with some log output showing progress. And I disable parallel GC lately, enabling parallel GC only makes it worse.<u></u><u></u></p>
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If I comment out the code updating the indices (those creating many TVars), the overall throughput only drop slowly as more data are inserted, the parallelism feels steady even after the server process' private memory takes several GBs.<u></u><u></u></p>
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I didn't expect this, but appears to me that GC of GHC is really not good at handling massive number of pointers in the heap, while those pointers are essential to reduce contention (and maybe expensive data copying too) at heavy parallelism/concurrency.<u></u><u></u></p>
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Btw I tried `+RTS -xn` with GHC 8.10.1 too, no obvious different behavior compared to 8.8.3; and also tried tweaking GC related RTS options a bit, including increasing -G up to 10, no much difference too.<u></u><u></u></p>
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I feel hopeless at the moment, wondering if I'll have to rewrite this in-memory db in Go/Rust or some other runtime ...<u></u><u></u></p>
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Btw I read <a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftech.channable.com%2Fposts%2F2020-04-07-lessons-in-managing-haskell-memory.html&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838761589&sdata=gqSH82%2FOYRaW4fzBDl%2BLDjhbRA%2BDRE6jaj4k1UI2gFE%3D&reserved=0" target="_blank">https://tech.channable.com/posts/2020-04-07-lessons-in-managing-haskell-memory.html</a> in
searching about the symptoms, and don't feel likely to convert my DB managed data into immutable types thus to fit into Compact Regions, not quite likely a live in-mem database instance can do.<u></u><u></u></p>
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So seems there are good reasons no successful DBMS, at least in-memory ones have been written in Haskell.<u></u><u></u></p>
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Best regards,<u></u><u></u></p>
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Compl<u></u><u></u></p>
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On 2020-07-25, at 22:07, Ryan Yates <<a href="mailto:fryguybob@gmail.com" target="_blank">fryguybob@gmail.com</a>> wrote:<u></u><u></u></p>
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Unfortunately my STM benchmarks are rather disorganized. The most relevant paper using them is:<u></u><u></u></p>
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Leveraging hardware TM in Haskell (PPoPP '19)<u></u><u></u></p>
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<a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdl.acm.org%2Fdoi%2F10.1145%2F3293883.3295711&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838771582&sdata=h3po1gPutR%2BsiCST1N0RNkM6irnVL0%2BVbYl3Vs8F8Oc%3D&reserved=0" target="_blank">https://dl.acm.org/doi/10.1145/3293883.3295711</a><u></u><u></u></p>
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Or my thesis:<u></u><u></u></p>
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<a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Furresearch.rochester.edu%2FinstitutionalPublicationPublicView.action%3FinstitutionalItemId%3D34931&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838771582&sdata=jBQMX5RRajIj0KbLWQCMt%2BMyMJIEmTpSuEHBWpq5Isg%3D&reserved=0" target="_blank">https://urresearch.rochester.edu/institutionalPublicationPublicView.action?institutionalItemId=34931</a> <u></u><u></u></p>
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The PPoPP benchmarks are on a branch (or the releases tab on github):<u></u><u></u></p>
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<a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Ffryguybob%2Fghc-stm-benchmarks%2Ftree%2Fwip%2Fmutable-fields%2Fbenchmarks%2FPPoPP2019%2Fsrc&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838771582&sdata=PinsrrGPgAB9TgxH61xngSItw1DcIRf1Niq39b%2BOe0s%3D&reserved=0" target="_blank">https://github.com/fryguybob/ghc-stm-benchmarks/tree/wip/mutable-fields/benchmarks/PPoPP2019/src</a> <u></u><u></u></p>
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All that to say, without an implementation of mutable constructor fields (which I'm working on getting into GHC) the scaling is limited.<u></u><u></u></p>
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<u></u> <u></u></p>
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Ryan<u></u><u></u></p>
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On Sat, Jul 25, 2020 at 3:45 AM Compl Yue via Haskell-Cafe <<a href="mailto:haskell-cafe@haskell.org" target="_blank">haskell-cafe@haskell.org</a>> wrote:<u></u><u></u></p>
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<p>Dear Cafe,<u></u><u></u></p>
<p>As Chris Allen has suggested, I learned that <a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fhackage.haskell.org%2Fpackage%2Fstm-containers&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838781576&sdata=ZwtAltlFRkny5q7M%2B7Pople6c4WA%2Bs8vZhwewUge7eg%3D&reserved=0" target="_blank">
https://hackage.haskell.org/package/stm-containers</a> and <a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fhackage.haskell.org%2Fpackage%2Fttrie&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838781576&sdata=zMcZy%2BEzqklkQGjKglCgwg5ZoWyWZIyeRNaCcqtnECs%3D&reserved=0" target="_blank">
https://hackage.haskell.org/package/ttrie</a> can help a lot when used in place of traditional HashMap for stm tx processing, under heavy concurrency, yet still with automatic parallelism as GHC implemented them. Then I realized that in addition to hash map
(used to implement dicts and scopes), I also need to find a TreeMap replacement data structure to implement the db index. I've been focusing on the uniqueness constraint aspect, but it's still an index, needs to provide range scan api for db clients, so hash
map is not sufficient for the index.<u></u><u></u></p>
<p>I see Ryan shared the code benchmarking RBTree with stm in mind:<u></u><u></u></p>
<p><a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Ffryguybob%2Fghc-stm-benchmarks%2Ftree%2Fmaster%2Fbenchmarks%2FRBTree-Throughput&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838791571&sdata=Nl2eN81Kjaf5qyNKEaxxc0ioMw6w4QoX4b5vAE5RaF8%3D&reserved=0" target="_blank">https://github.com/fryguybob/ghc-stm-benchmarks/tree/master/benchmarks/RBTree-Throughput</a>
<u></u><u></u></p>
<p><a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Ffryguybob%2Fghc-stm-benchmarks%2Ftree%2Fmaster%2Fbenchmarks%2FRBTree&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838791571&sdata=%2BLp6HQCyROOlpA2pr8BR8DPls68oY5Y77GKgqbSKmno%3D&reserved=0" target="_blank">https://github.com/fryguybob/ghc-stm-benchmarks/tree/master/benchmarks/RBTree</a><u></u><u></u></p>
<p>But can't find conclusion or interpretation of that benchmark suite. And here's a followup question:<u></u><u></u></p>
<p><u></u> <u></u></p>
<p>Where are some STM contention optimized data structures, that having keys ordered, with sub-range traversing api ?
<u></u><u></u></p>
<p>(of course production ready libraries most desirable)<u></u><u></u></p>
<p><u></u> <u></u></p>
<p>Thanks with regards,<u></u><u></u></p>
<p>Compl<u></u><u></u></p>
<p><u></u> <u></u></p>
<div>
<p class="MsoNormal">On 2020/7/25 <span style="font-family:"MS Gothic"">下午</span>2:04, Compl Yue via Haskell-Cafe wrote:<u></u><u></u></p>
</div>
<blockquote style="margin-top:5pt;margin-bottom:5pt">
<p>Shame on me for I have neither experienced with `perf`, I'd learn these essential tools soon to put them into good use.<u></u><u></u></p>
<p>It's great to learn about how `orElse` actually works, I did get confused why there are so little retries captured, and now I know. So that little trick should definitely be removed before going production, as it does no much useful things at excessive cost.
I put it there to help me understand internal working of stm, now I get even better knowledge ;-)<u></u><u></u></p>
<p>I think a debugger will trap every single abort, isn't it annoying when many aborts would occur? If I'd like to count the number of aborts, ideally accounted per service endpoints, time periods, source modules etc. there some tricks for that?<u></u><u></u></p>
<p>Thanks with best regards,<u></u><u></u></p>
<p>Compl<u></u><u></u></p>
<p><u></u> <u></u></p>
<div>
<p class="MsoNormal">On 2020/7/25 <span style="font-family:"MS Gothic"">上午</span>2:02, Ryan Yates wrote:<u></u><u></u></p>
</div>
<blockquote style="margin-top:5pt;margin-bottom:5pt">
<div>
<p class="MsoNormal">To be clear, I was trying to refer to Linux `perf` [^1]. Sampling based profiling can do a good job with concurrent and parallel programs where other methods are problematic. For instance,
<u></u><u></u></p>
<div>
<p class="MsoNormal"> changing the size of heap objects can drastically change cache performance and completely different behavior can show up.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">[^1]: <a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fen.wikipedia.org%2Fwiki%2FPerf_(Linux)&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838801566&sdata=v%2Bv2aVaBITriAM26CqN%2Bp35yshLl%2BbY4BWVEIOSlStA%3D&reserved=0" target="_blank">https://en.wikipedia.org/wiki/Perf_(Linux)</a><u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">The spinning in `readTVar` should always be very short and it typically shows up as intensive CPU use, though it may not be high energy use with `pause` in the loop on x86 (looks like we don't have it [^2], I thought we did, but maybe that
was only in some of my code... )<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">[^2]: <a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fghc%2Fghc%2Fblob%2Fmaster%2Frts%2FSTM.c%23L1275&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838801566&sdata=YBLmeg4Xxby%2BJJmO8B5etdA6tDpBYOry7jdjEoRFd%2Fk%3D&reserved=0" target="_blank">https://github.com/ghc/ghc/blob/master/rts/STM.c#L1275</a> <u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">All that to say, I doubt that you are spending much time spinning (but it would certainly be interesting to know if you are! You would see `perf` attribute a large amount of time to `read_current_value`). The amount of code to execute
for commit (the time when locks are held) is always much shorter than it takes to execute the transaction body. As you add more conflicting threads this gets worse of course as commits sequence.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">The code you have will count commits of executions of `retry`. Note that `retry` is a user level idea, that is, you are counting user level *explicit* retries. This is different from a transaction failing to commit and starting again.
These are invisible to the user. Also using your trace will convert `retry` from the efficient wake on write implementation, to an active retry that will always attempt again. We don't have cheap logging of transaction aborts in GHC, but I have built such
logging in my work. You can observe these aborts with a debugger by looking for execution of this line:<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal"><a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fghc%2Fghc%2Fblob%2Fmaster%2Frts%2FSTM.c%23L1123&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838811560&sdata=jAEm1CpEYQx6ORikerxVHOSlaOmrTzB3m9EVmOwo%2B8w%3D&reserved=0" target="_blank">https://github.com/ghc/ghc/blob/master/rts/STM.c#L1123</a><u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Ryan <u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
</div>
<p class="MsoNormal"><u></u> <u></u></p>
<div>
<div>
<p class="MsoNormal">On Fri, Jul 24, 2020 at 12:35 PM Compl Yue <<a href="mailto:compl.yue@icloud.com" target="_blank">compl.yue@icloud.com</a>> wrote:<u></u><u></u></p>
</div>
<blockquote style="border-top:none;border-right:none;border-bottom:none;border-left:1pt solid rgb(204,204,204);padding:0cm 0cm 0cm 6pt;margin-left:4.8pt;margin-right:0cm">
<div>
<p>I'm not familiar with profiling GHC yet, may need more time to get myself proficient with it.<u></u><u></u></p>
<p>And a bit more details of my test workload for diagnostic: the db clients are Python processes from a cluster of worker nodes, consulting the db server to register some path for data files, under a data dir within a shared filesystem, then mmap those data
files and fill in actual array data. So the db server don't have much computation to perform, but puts the data file path into a global index, which at the same validates its uniqueness. As there are many client processes trying to insert one meta data record
concurrently, with my naive implementation, the global index's TVar will almost always in locked state by one client after another, from a queue never fall empty.<u></u><u></u></p>
<p>So if `readTVar` should spinning waiting, I doubt the threads should actually make high CPU utilization, because at any instant of time, all threads except the committing one will be doing that one thing.<u></u><u></u></p>
<p>And I have something in my code to track STM retry like this:<u></u><u></u></p>
<p>```<u></u><u></u></p>
<div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(106,153,85)">-- blocking wait not expected, track stm retries explicitly</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(220,220,170)">trackSTM</span><span style="font-size:13pt;color:rgb(212,212,212)"> ::
</span><span style="font-size:13pt;color:rgb(86,156,214)">Int</span><span style="font-size:13pt;color:rgb(212,212,212)"> ->
</span><span style="font-size:13pt;color:rgb(86,156,214)">IO</span><span style="font-size:13pt;color:rgb(212,212,212)"> (</span><span style="font-size:13pt;color:rgb(86,156,214)">Either</span><span style="font-size:13pt;color:rgb(212,212,212)"> ()
</span><span style="font-size:13pt;color:rgb(156,220,254)">a</span><span style="font-size:13pt;color:rgb(212,212,212)">)<u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">trackSTM !rtc =
</span><span style="font-size:13pt;color:rgb(197,134,192)">do</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">when
</span><span style="font-size:13pt;color:rgb(106,153,85)">-- todo increase the threshold of reporting?</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">(rtc >
</span><span style="font-size:13pt;color:rgb(181,206,168)">0</span><span style="font-size:13pt;color:rgb(212,212,212)">) $
</span><span style="font-size:13pt;color:rgb(197,134,192)">do</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(106,153,85)">-- trace out the retries so the end users can be aware of them</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">tid <- myThreadId<u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">trace<u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">(
</span><span style="font-size:13pt;color:rgb(206,145,120)">"</span><span style="font-size:13pt;font-family:"Segoe UI Emoji",sans-serif;color:rgb(206,145,120)">🔙</span><span style="font-size:13pt;color:rgb(215,186,125)">\n</span><span style="font-size:13pt;color:rgb(206,145,120)">"</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)"><> show callCtx<u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)"><>
</span><span style="font-size:13pt;color:rgb(206,145,120)">"</span><span style="font-size:13pt;font-family:"Segoe UI Emoji",sans-serif;color:rgb(206,145,120)">🌀</span><span style="font-size:13pt;color:rgb(206,145,120)"> "</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)"><> show tid<u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)"><>
</span><span style="font-size:13pt;color:rgb(206,145,120)">" stm retry #"</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)"><> show rtc<u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">)<u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">$ return
</span><span style="font-size:13pt;color:rgb(86,156,214)">()</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">atomically ((Just <$> stmJob) `orElse` return Nothing) >>= \</span><span style="font-size:13pt;color:rgb(197,134,192)">case</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">Nothing ->
</span><span style="font-size:13pt;color:rgb(106,153,85)">-- stm failed, do a tracked retry</span><span style="font-size:13pt;color:rgb(212,212,212)"><u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">trackSTM (rtc +
</span><span style="font-size:13pt;color:rgb(181,206,168)">1</span><span style="font-size:13pt;color:rgb(212,212,212)">)<u></u><u></u></span></p>
</div>
<div>
<p class="MsoNormal" style="line-height:17.25pt;background:rgb(30,30,30)"><span style="font-size:13pt;color:rgb(212,212,212)">Just ... -> ...<u></u><u></u></span></p>
</div>
</div>
<p>```<u></u><u></u></p>
<p>No such trace msg fires during my test, neither in single thread run, nor in runs with pressure. I'm sure this tracing mechanism works, as I can see such traces fire, in case e.g. posting a TMVar to a TQueue for some other thread to fill it, then read the
result out, if these 2 ops are composed into a single tx, then of course it's infinite retry loop, and a sequence of such msgs are logged with ever increasing rtc #.<u></u><u></u></p>
<p>So I believe no retry has ever been triggered.<u></u><u></u></p>
<p>What can going on there?<u></u><u></u></p>
<p><u></u> <u></u></p>
<div>
<p class="MsoNormal">On 2020/7/24 <span style="font-family:"MS Gothic"">下午</span>11:46, Ryan Yates wrote:<u></u><u></u></p>
</div>
<blockquote style="margin-top:5pt;margin-bottom:5pt">
<div>
<div>
<div>
<p class="MsoNormal">> Then to explain the low CPU utilization (~10%), am I right to understand it as that upon reading a TVar locked by another committing tx, a lightweight thread will put itself into `waiting STM` and descheduled state, so the CPUs can only
stay idle as not so many threads are willing to proceed?<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Since the commit happens in finite steps, the expectation is that the lock will be released very soon. Given this when the body of a transaction executes `readTVar` it spins (active CPU!) until the `TVar` is observed unlocked. If a lock
is observed while commiting, it immediately starts the transaction again from the beginning. To get the behavior of suspending a transaction you have to successfully commit a transaction that executed `retry`. Then the transaction is put on the wakeup lists
of its read set and subsequent commits will wake it up if its write set overlaps.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">I don't think any of these things would explain low CPU utilization. You could try running with `perf` and see if lots of time is spent in some recognizable part of the RTS.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Ryan<u></u><u></u></p>
</div>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<p class="MsoNormal"><u></u> <u></u></p>
<div>
<div>
<p class="MsoNormal">On Fri, Jul 24, 2020 at 11:22 AM Compl Yue <<a href="mailto:compl.yue@icloud.com" target="_blank">compl.yue@icloud.com</a>> wrote:<u></u><u></u></p>
</div>
<blockquote style="border-top:none;border-right:none;border-bottom:none;border-left:1pt solid rgb(204,204,204);padding:0cm 0cm 0cm 6pt;margin-left:4.8pt;margin-right:0cm">
<div>
<p>Thanks very much for the insightful information Ryan! I'm glad my suspect was wrong about the Haskell scheduler:<u></u><u></u></p>
<p>> The Haskell capability that is committing a transaction will not yield to another Haskell thread while it is doing the commit. The OS thread may be preempted, but once commit starts the haskell scheduler is not invoked until after locks are released.<u></u><u></u></p>
<div>
<p class="MsoNormal">So best effort had already been made in GHC and I just need to cooperate better with its design. Then to explain the low CPU utilization (~10%), am I right to understand it as that upon reading a TVar locked by another committing tx, a
lightweight thread will put itself into `waiting STM` and descheduled state, so the CPUs can only stay idle as not so many threads are willing to proceed?<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Anyway, I see light with better data structures to improve my situation, let me try them and report back. Actually I later changed `TVar (HaskMap k v)` to be `TVar (HashMap k Int)` where the `Int` being array index into `TVar (Vector (TVar
(Maybe v)))`, in pursuing insertion order preservation semantic of dict entries (like that in Python 3.7+), then it's very hopeful to incorporate stm-containers' Map or ttrie to approach free of contention.<u></u><u></u></p>
</div>
<p>Thanks with regards,<u></u><u></u></p>
<p>Compl<u></u><u></u></p>
<p><u></u> <u></u></p>
<div>
<p class="MsoNormal">On 2020/7/24 <span style="font-family:"MS Gothic"">下午</span>10:03, Ryan Yates wrote:<u></u><u></u></p>
</div>
<blockquote style="margin-top:5pt;margin-bottom:5pt">
<div>
<div>
<p class="MsoNormal">Hi Compl,<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Having a pool of transaction processing threads can be helpful in a certain way. If the body of the transaction takes more time to execute then the Haskell thread is allowed and it yields, the suspended thread won't get in the way of other
thread, but when it is rescheduled, will have a low probability of success. Even worse, it will probably not discover that it is doomed to failure until commit time. If transactions are more likely to reach commit without yielding, they are more likely to
succeed. If the transactions are not conflicting, it doesn't make much difference other than cache churn.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">The Haskell capability that is committing a transaction will not yield to another Haskell thread while it is doing the commit. The OS thread may be preempted, but once commit starts the haskell scheduler is not invoked until after locks
are released.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">To get good performance from STM you must pay attention to what TVars are involved in a commit. All STM systems are working under the assumption of low contention, so you want to minimize "false" conflicts (conflicts that are not essential
to the computation). Something like `TVar (HashMap k v)` will work pretty well for a low thread count, but every transaction that writes to that structure will be in conflict with every other transaction that accesses it. Pushing the `TVar` into the nodes
of the structure reduces the possibilities for conflict, while increasing the amount of bookkeeping STM has to do. I would like to reduce the cost of that bookkeeping using better structures, but we need to do so without harming performance in the low TVar
count case. Right now it is optimized for good cache performance with a handful of TVars.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">There is another way to play with performance by moving work into and out of the transaction body. A transaction body that executes quickly will reach commit faster. But it may be delaying work that moves into another transaction. Forcing
values at the right time can make a big difference.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Ryan<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">On Fri, Jul 24, 2020 at 2:14 AM Compl Yue via Haskell-Cafe <<a href="mailto:haskell-cafe@haskell.org" target="_blank">haskell-cafe@haskell.org</a>> wrote:<u></u><u></u></p>
</div>
<div>
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<p>Thanks Chris, I confess I didn't pay enough attention to STM specialized container libraries by far, I skimmed through the description of stm-containers and ttrie, and feel they would definitely improve my code's performance in case I limit the server's
parallelism within hardware capabilities. That may because I'm still prototyping the api and infrastructure for correctness, so even `TVar (HashMap k v)` performs okay for me at the moment, only if at low contention (surely there're plenty of CPU cycles to
be optimized out in next steps). I model my data after graph model, so most data, even most indices are localized to nodes and edges, those can be manipulated without conflict, that's why I assumed I have a low contention use case since the very beginning
- until I found there are still (though minor) needs for global indices to guarantee global uniqueness, I feel faithful with stm-containers/ttrie to implement a more scalable global index data structure, thanks for hinting me.<u></u><u></u></p>
<p>So an evident solution comes into my mind now, is to run the server with a pool of tx processing threads, matching number of CPU cores, client RPC requests then get queued to be executed in some thread from the pool. But I'm really fond of the mechanism
of M:N scheduler which solves massive/dynamic concurrency so elegantly. I had some good result with Go in this regard, and see GHC at par in doing this, I don't want to give up this enjoyable machinery.<u></u><u></u></p>
<p>But looked at the stm implementation in GHC, it seems written TVars are exclusively locked during commit of a tx, I suspect this is the culprit when there're large M lightweight threads scheduled upon a small N hardware capabilities, that is when a lightweight
thread yield control during an stm transaction commit, the TVars it locked will stay so until it's scheduled again (and again) till it can finish the commit. This way, descheduled threads could hold live threads from progressing. I haven't gone into more details
there, but wonder if there can be some improvement for GHC RTS to keep an stm committing thread from descheduled, but seemingly that may impose more starvation potential; or stm can be improved to have its TVar locks preemptable when the owner trec/thread
is in descheduled state? Neither should be easy but I'd really love massive lightweight threads doing STM practically well.<u></u><u></u></p>
<p>Best regards,<u></u><u></u></p>
<p>Compl<u></u><u></u></p>
<p><u></u> <u></u></p>
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<p class="MsoNormal">On 2020/7/24 <span style="font-family:"MS Gothic"">上午</span>12:57, Christopher Allen wrote:<u></u><u></u></p>
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<p class="MsoNormal">It seems like you know how to run practical tests for tuning thread count and contention for throughput. Part of the reason you haven't gotten a super clear answer is "it depends." You give up fairness when you use STM instead of MVars
or equivalent structures. That means a long running transaction might get stampeded by many small ones invalidating it over and over. The long-running transaction might never clear if the small transactions keep moving the cheese. I mention this because transaction
runtime and size and count all affect throughput and latency. What might be ideal for one pattern of work might not be ideal for another. Optimizing for overall throughput might make the contention and fairness problems worse too. I've done practical tests
to optimize this in the past, both for STM in Haskell and for RDBMS workloads. <u></u>
<u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
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<p class="MsoNormal">The next step is sometimes figuring out whether you really need a data structure within a single STM container or if perhaps you can break up your STM container boundaries into zones or regions that roughly map onto update boundaries. That
should make the transactions churn less. On the outside chance you do need to touch more than one container in a transaction, well, they compose.
<u></u><u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
</div>
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<p class="MsoNormal">e.g. <a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fhackage.haskell.org%2Fpackage%2Fstm-containers&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838811560&sdata=Lq1%2BGj0Z6%2BBGMRAZrSzcTAlYgj0B0A67RaQcyyCcXbk%3D&reserved=0" target="_blank">https://hackage.haskell.org/package/stm-containers</a><u></u><u></u></p>
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<p class="MsoNormal"><a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fhackage.haskell.org%2Fpackage%2Fttrie&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838821555&sdata=PpaiVM2NrPM2HzK0bh%2BMR8YF90yHlxKnN9gwZVQHqR0%3D&reserved=0" target="_blank">https://hackage.haskell.org/package/ttrie</a><u></u><u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">It also sounds a bit like your question bumps into Amdahl's Law a bit.<u></u><u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
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<p class="MsoNormal">All else fails, stop using STM and find something more tuned to your problem space.<u></u><u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
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<p class="MsoNormal">Hope this helps,<u></u><u></u></p>
</div>
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<p class="MsoNormal">Chris Allen<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
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<p class="MsoNormal"><u></u> <u></u></p>
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<div>
<p class="MsoNormal">On Thu, Jul 23, 2020 at 9:53 AM YueCompl via Haskell-Cafe <<a href="mailto:haskell-cafe@haskell.org" target="_blank">haskell-cafe@haskell.org</a>> wrote:<u></u><u></u></p>
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<p class="MsoNormal">Hello Cafe, <u></u><u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
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<div>
<p class="MsoNormal">I'm working on an in-memory database, in Client/Server mode I just let each connected client submit remote procedure call running in its dedicated lightweight thread, modifying TVars in RAM per its business needs, then in case many clients
connected concurrently and trying to insert new data, if they are triggering global index (some TVar) update, the throughput would drop drastically. I reduced the shared state to a simple int counter by TVar, got same symptom. While the parallelism feels okay
when there's no hot TVar conflicting, or M is not much greater than N.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">As an empirical test workload, I have a `+RTS -N10` server process, it handles 10 concurrent clients okay, got ~5x of single thread throughput; but in handling 20 concurrent clients, each of the 10 CPUs can only be driven to ~10% utilization,
the throughput seems even worse than single thread. More clients can even drive it thrashing without much progressing.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal"> I can understand that pure STM doesn't scale well after reading [1], and I see it suggested [7] attractive and planned future work toward that direction.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
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<div>
<p class="MsoNormal">But I can't find certain libraries or frameworks addressing large M over small N scenarios, [1] experimented with designated N parallelism, and [7] is rather theoretical to my empirical needs.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Can you direct me to some available library implementing the methodology proposed in [7] or other ways tackling this problem?<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">I think the most difficult one is that a transaction should commit with global indices (with possibly unique constraints) atomically updated, and rollback with any violation of constraints, i.e. transactions have to cover global states
like indices. Other problems seem more trivial than this.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Specifically, [7] states:<u></u><u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">> It must be emphasized that all of the mechanisms we deploy originate, in one form or another, in the database literature from the 70s and 80s. Our contribution is to adapt these techniques to software transactional memory, providing more
effective solutions to important STM problems than prior proposals.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">I wonder any STM based library has simplified those techniques to be composed right away? I don't really want to implement those mechanisms by myself, rebuilding many wheels from scratch.<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">Best regards,<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal">Compl<u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
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<p class="MsoNormal"><u></u> <u></u></p>
</div>
<div>
<p class="MsoNormal">[1] Comparing the performance of concurrent linked-list implementations in Haskell <u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><a href="https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsimonmar.github.io%2Fbib%2Fpapers%2Fconcurrent-data.pdf&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838821555&sdata=41Jaz8ZRmRfBHyGKxfhJlm4xR7q0pOtJShtO0jTlOwQ%3D&reserved=0" target="_blank">https://simonmar.github.io/bib/papers/concurrent-data.pdf</a><u></u><u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
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<p class="MsoNormal">[7] M. Herlihy and E. Koskinen. Transactional boosting: a methodology for highly-concurrent transactional objects. In Proc. of PPoPP ’08, pages 207–216. ACM Press, 2008.<u></u><u></u></p>
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<div>
<p class="MsoNormal"><a href="https://nam06.safelinks.protection.outlook.com/?url=https:%2F%2Fwww.cs.stevens.edu%2F~ejk%2Fpapers%2Fboosting-ppopp08.pdf&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838831548&sdata=ya8Az1oC6f2xoMb90S9HCH57UTQ0nV9sg6SW%2B5JCPC4%3D&reserved=0" target="_blank">https://www.cs.stevens.edu/~ejk/papers/boosting-ppopp08.pdf</a><u></u><u></u></p>
</div>
<div>
<p class="MsoNormal"><u></u> <u></u></p>
</div>
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<p class="MsoNormal"><br clear="all">
<u></u><u></u></p>
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<p class="MsoNormal"><u></u> <u></u></p>
</div>
<p class="MsoNormal">-- <u></u><u></u></p>
<div>
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<p class="MsoNormal">Chris Allen<u></u><u></u></p>
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<p class="MsoNormal"><span style="font-size:9.5pt">Currently working on </span><a href="https://nam06.safelinks.protection.outlook.com/?url=http%3A%2F%2Fhaskellbook.com%2F&data=02%7C01%7Csimonpj%40microsoft.com%7C8ebd68bca55140cebaae08d833f888f2%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637316489838831548&sdata=tIHFQFZPIQgRp8oqGRvyebm1YQdCvGD0VoMcflzJwKc%3D&reserved=0" target="_blank">http://haskellbook.com</a><u></u><u></u></p>
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