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2021-07-26 06:20:03 <Axman6> OpenMPI takes care of several things: it distributes binaries across clusters (it's almost exclusively used for HPC/scientific computing as far as I understand it), and abstracting network comminications between distinct executions - it's niche is things like large matrix computations where each node in the cluster computes a sub computation and then MPI helps to efficiently move the temporary results around and combine them into the full result
2021-07-26 06:20:43 <Axman6> Distributed computing only makes sense if there's a network, so that's why I metnion it
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2021-07-26 06:21:05 <euouae> Ok but I'm assuming they're not communicating with TCP, or are they?
2021-07-26 06:21:50 <Axman6> if you're talking about MPI, that would depend on the cluster. MPI usually knows how to use things like infiniband, which is basically a networked PCI bus with direct memory access
2021-07-26 06:22:14 <Axman6> but there's no reason not to use TCP either, it'll just be hiugher latency, which might be fine
2021-07-26 06:22:46 <euouae> I guess you're right, adding seconds to a computation is not a big deal if it takes an hour or more
2021-07-26 06:22:48 <Axman6> you did specifically ask about distributed computing, so if that's not what you axtually meant, I can give other answers :P
2021-07-26 06:23:04 <Axman6> actually*
2021-07-26 06:23:31 <euouae> I don't feel very comfortable in these topics as I've never done them before, so my apology if I'm flimsy hehe
2021-07-26 06:23:42 <euouae> I've only had experience with parallelism within a single node
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2021-07-26 06:24:19 <euouae> I think as a first introduction I might go with C++ and OpenMPI and switch to Haskell later if I can
2021-07-26 06:24:22 <Axman6> Well we have lots of tools for that, and that book is basically the bible on the topic, do get reading! it's extremely approachable if you have the basics of Haskell down
2021-07-26 06:24:34 <euouae> Oh so it does mention distributed computing as well?
2021-07-26 06:24:45 <Axman6> if you're working on a single machine, OpenMPI is unnecessary. OpenMP will give you parallelism though
2021-07-26 06:24:58 <euouae> I have access to a supercoputer
2021-07-26 06:25:01 <Axman6> you don't seem to be talking about distributed computing
2021-07-26 06:25:24 <Axman6> OpenMPI doesn't magically take a single binary and make it run across a whole cluster though
2021-07-26 06:25:36 <euouae> I've never used OpenMPI
2021-07-26 06:25:46 <euouae> It's on my todo list
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2021-07-26 07:28:22 <juri_> I haven't seen much haskell distributed computing stuff that 'just works', sadly.
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2021-07-26 07:29:01 <euouae> juri_: so it's a thing for experts?
2021-07-26 07:29:15 <euouae> I'm just getting into it myself, I'm hopeful
2021-07-26 07:29:23 <euouae> at least I'm hopeful I can get it done in C++
2021-07-26 07:29:33 <juri_> I think it's just a thing that stalls every now and then, because there's not much demand.
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2021-07-26 07:29:59 <euouae> It surprises me that scientific computing isn't bigger with Haskell
2021-07-26 07:30:05 <euouae> It is very convenient for it
2021-07-26 07:30:21 <juri_> I think one thing that has stuck in that area is accelerate.
2021-07-26 07:30:30 <juri_> or data parallel haskell..
2021-07-26 07:31:19 <juri_> accelerate is neat, because if you write code within it's constraints, you can use a GPU and CPU at the same time..
2021-07-26 07:31:44 <euouae> Right but can you use multiple nodes?
2021-07-26 07:31:52 <juri_> I'm just not much of a fan, because it requires real nvidia drivers.
2021-07-26 07:32:05 <euouae> Real drivers?
2021-07-26 07:32:26 <juri_> no, for that, you'd want cloud haskell. which seems to be stalling out.
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2021-07-26 07:33:41 <Athas> DPH is also long dead, but Accelerate is active.
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