Crates.io | mpi |
lib.rs | mpi |
version | 0.8.0 |
source | src |
created_at | 2015-09-09 19:26:30.373455 |
updated_at | 2024-05-03 03:06:09.958378 |
description | Message Passing Interface bindings for Rust |
homepage | https://github.com/rsmpi/rsmpi |
repository | https://github.com/rsmpi/rsmpi |
max_upload_size | |
id | 3013 |
size | 396,589 |
The Message Passing Interface (MPI) is a specification for a message-passing style concurrency library. Implementations of MPI are often used to structure parallel computation on High Performance Computing systems. The MPI specification describes bindings for the C programming language (and through it C++) as well as for the Fortran programming language. This library tries to bridge the gap into a more rustic world.
An implementation of the C language interface that conforms to MPI-3.1. rsmpi
is currently tested with these implementations:
Users have also had success with these MPI implementations, but they are not tested in CI:
PrgEnv-amd/8.3.3
For a reasonable chance of success with rsmpi
with any MPI implementation, you must have one of:
MPI_PKG_CONFIG
to be the name or path for pkg-config for your implementation
rsmpi
automatically uses CRAY_MPICH_DIR
on Cray environments so the above need not be setmpich
and ompi
are tried by default as a last resortpkg-config --cflags --libs mpich
mpicc
MPICC=/path/to/mpicc
to specify fullympicc
in $PATH
mpicc -show
should print the full command line that is used to invoke the wrapped C compiler in gcc-compatible syntax (e.g., -lmpi
, -I/usr/local/include
, ...)MSMPI_INC
and either MSMPI_LIB32
or MSMPI_LIB64
should be set
Since the MPI standard leaves some details of the C API unspecified (whether to implement certain constants and even functions using preprocessor macros or native C constructs, the details of most types, etc.) rsmpi
takes a two step approach to generating functional low-level bindings.
First, it uses a thin static library written in C (see rsmpi.h and rsmpi.c) that tries to capture the underspecified identifiers and re-exports them with a fixed C API. This library is built from build.rs using the gcc
crate.
Second, to generate FFI definitions tailored to each MPI implementation, rsmpi
uses rust-bindgen
which needs libclang
. See the bindgen project page for more information.
Furthermore, rsmpi
uses the libffi
crate which installs the native libffi
which depends on certain build tools. See the libffi project page for more information.
Add the mpi
crate as a dependency in your Cargo.toml
:
# "features" is optional
[dependencies]
mpi = { version = "0.8.0", features = ["user-operations", "derive"] }
Then use it in your program like this:
use mpi::request::WaitGuard;
use mpi::traits::*;
fn main() {
let universe = mpi::initialize().unwrap();
let world = universe.world();
let size = world.size();
let rank = world.rank();
let next_rank = (rank + 1) % size;
let previous_rank = (rank - 1 + size) % size;
let msg = vec![rank, 2 * rank, 4 * rank];
mpi::request::scope(|scope| {
let _sreq = WaitGuard::from(
world
.process_at_rank(next_rank)
.immediate_send(scope, &msg[..]),
);
let (msg, status) = world.any_process().receive_vec();
println!(
"Process {} got message {:?}.\nStatus is: {:?}",
rank, msg, status
);
let x = status.source_rank();
assert_eq!(x, previous_rank);
assert_eq!(vec![x, 2 * x, 4 * x], msg);
let root_rank = 0;
let root_process = world.process_at_rank(root_rank);
let mut a;
if world.rank() == root_rank {
a = vec![2, 4, 8, 16];
println!("Root broadcasting value: {:?}.", &a[..]);
} else {
a = vec![0; 4];
}
root_process.broadcast_into(&mut a[..]);
println!("Rank {} received value: {:?}.", world.rank(), &a[..]);
assert_eq!(&a[..], &[2, 4, 8, 16]);
});
}
The bindings follow the MPI 3.1 specification.
Currently supported:
Not supported (yet):
One-sided communication (RMA)
MPI parallel I/O
A million small things
These optional features can be enabled in your cargo manifest. See the Usage section above.
user-operations
enables capturing lambdas and safe creation in UserOperation
. This feature
requires the libffi
system library, which is not available on all systems out-of-the-box.
let mut h = 0;
comm.all_reduce_into(
&(rank + 1),
&mut h,
&UserOperation::commutative(|x, y| {
let x: &[Rank] = x.downcast().unwrap();
let y: &mut [Rank] = y.downcast().unwrap();
for (&x_i, y_i) in x.iter().zip(y) {
*y_i += x_i;
}
}),
);
derive
enables the Equivalence
derive macro, which makes it easy to send structs
over-the-wire without worrying about safety around padding, and allowing arbitrary datatype
matching between structs with the same field order but different layout.
#[derive(Equivalence)]
struct MyProgramOpts {
name: [u8; 100],
num_cycles: u32,
material_properties: [f64; 20],
}
Every public item of rsmpi
should at least have a short piece of documentation associated with it. Documentation can be generated via:
cargo doc
Documentation for the latest version of the crate released to crates.io is hosted on Github pages.
See files in examples/. These examples also act as integration tests.
It is possible to use rsmpi
with a communicator provided by mpi4py. An example project demonstrating this is mpi4py_with_rsmpi.
Licensed under either of
at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.