ompi VS libevent

The commercial Linux world (see https://github.com/open-mpi/ompi/issues/4349) and other open source OSes (eg FreeBSD) seem to have lined up behind little-endian PowerPC. IBM still has a big-endian problem with AIX, IBM i, and Linux on Z.

Roughly, the sets of computational problems that people used (use?) MPI for. Things like numerical solvers for sparse matrices that are so big that you need to split them across your entire cluster. These still require a lot of node-to-node communication, and on top of it, the pattern is dependent on each problem (so easy solutions like map-reduce are effectively out). See eg https://www.open-mpi.org/, and https://courses.csail.mit.edu/18.337/2005/book/Lecture_08-Do... for the prototypical use case.

One of the guys at the local LUG is one of the lead maintainers of Open MPI. He told us about a comment that ran into the hundreds of lines, all for a one-line change in the code.

But it would be very inconvenient to have to keep crediting everyone who's ever worked on it. If you look at old projects, their licenses can have like 10-20 of those lines (here's one I was recently looking into).

I have a bit of experience programming for a highly-parallel supercomputer, specifically in my case an IBM BlueGene/Q. In that case, the answer is a lot of message passing (we used Open MPI [0]). Since the nodes are discrete and don't have any shared memory, you end up with something kinda reminiscent of the actor model as popularized by Erlang and co -- but in C for number-crunching performance.

That said, each of the nodes is itself composed of multiple cores with shared memory. So in cases where you really want to grind out performance, you actually end up using message passing to divvy up chunks of work, and then use classic pthreads to parallelize things further, with lower latency.

Debugging is a bit of a nightmare, though, since some bugs inevitably only come up once you have a large number of nodes running the algorithm in parallel. But you'll probably be in a mainframe-style time-sharing setup, so you may have to wait hours or more to rerun things.

This applies less to some of the newer supercomputers, which are more or less clusters of GPUs instead of clusters of CPUs. I imagine there's some commonality, but I haven't worked with any of them so I can't really say.

[0] https://www.open-mpi.org/

I would suggest using OpenMPI because it's pretty easy to get started with. You can build OpenMPI with CUDA support, then you can pass device pointers directly to MPI_Send and MPI_Recv. Then you don't have to deal with transfers and synchronization issues.

backends from native torch distributed configuration: nccl, gloo, mpi.

I use a linux ubuntu machine with MPI (https://www.open-mpi.org/). I had a question on making my computer simulations faster. Would be better to get an older AMD 9590 machine clocked at 4.7 ghz or continue using my Ryzen 7 1700 machine clocked at something like 3.5ghz?

OpenMPI - Message passing interface implementation. BSD-3-Clause

However, you should be able to use a different version of the library that is compatible with your system. Maybe you can install the development package for `libevent` via the system package manager? That should assure a working state. Otherwise you should be able to download a compatible version from https://libevent.org/ (either binary or source and build it yourself).

They're different. Node uses libuv while chromium uses libevent. You're also seeing different APIs for working with the event loop like nextTick() in Node that doesn't exist in browsers.

Unknown OS, continue trying to install? Menu? Develope this area! Querying Versions on https://libevent.org... Please be patient.

app-id: dev.geopjr.Hashbrown runtime: org.gnome.Platform runtime-version: "3.38" sdk: org.gnome.Sdk command: hashbrown finish-args: - --socket=wayland - --socket=fallback-x11 - --share=ipc cleanup: - /include - /lib/pkgconfig - /share/doc - /share/man - "*.a" - "*.la" modules: - name: libevent sources: - type: git url: https://github.com/libevent/libevent.git tag: release-2.1.12-stable - name: hashbrown buildsystem: simple build-commands: - $(pwd)/crystal/bin/crystal build ./src/hashbrown.cr --no-debug --release - install -D -m 0755 hashbrown /app/bin/hashbrown - install -D -m 0644 extra/Hashbrown.desktop /app/share/applications/dev.geopjr.Hashbrown.desktop - install -D -m 0644 extra/icons/logo.svg /app/share/icons/hicolor/scalable/apps/dev.geopjr.Hashbrown.svg - install -D -m 0644 extra/icons/symbolic.svg /app/share/icons/hicolor/symbolic/apps/dev.geopjr.Hashbrown-symbolic.svg post-install: - install -D -m 0644 extra/dev.geopjr.Hashbrown.metainfo.xml /app/share/metainfo/dev.geopjr.Hashbrown.metainfo.xml sources: - type: git url: https://github.com/GeopJr/Hashbrown.git tag: v1.2.0 commit: 02ecf5cc5aacc32fc484fd9e348d2b1220168295 - type: archive dest: crystal/ url: https://github.com/crystal-lang/crystal/releases/download/1.0.0/crystal-1.0.0-1-linux-x86_64.tar.gz sha256: 00211ca77758e99210ec40b8c5517b086d2ff9909e089400f6d847a95e5689a4 - type: git url: https://github.com/jhass/crystal-gobject.git commit: 6468c57f8aa54b71c766d27b1e59e87a09ee8552 dest: lib/gobject - type: git url: https://github.com/elorest/compiled_license.git tag: v0.1.3 commit: f287c2c8c95579688fa5620df954d8cc1272cbbf dest: lib/compiled_license