JuliaParallel / JuliaParallel/DistributedArrays.jl

Allowing a DArray to do as standard Array does

Open
#202 4 comments 0 reactions 0 assignees View on GitHub
Dominant language
Julia
Stars
205
Forks
34
PR merge metrics
No merged PRs in 30d

Description

Dear All,

I'm considering the following MWE, which consists of creating a matrix and vector of a `struct` an doing a calculation on them. I import the relevant mathematical operators from base, and it just works. Next I `addprocs` and try it with `DArray`, and the same calculation fails. Is there a way to enable this kind of functionality? It's definitely possible that I'm barking up the wrong tree and there's a much better way of achieving this - please let me know!

```
using Distributed

import Base.+, Base.*, Base.zero

let
struct Foo{T<:Number}
x::T
end
Base.:+(a::Foo, b::Foo) = Foo(a.x + b.x)
Base.:*(a::Foo, b::Foo) = Foo(a.x * b.x)
Base.:zero(a::Foo{T}) where {T} = Foo(zero(T))
function runlocal()
A = [Foo(rand()) for i in 1:3, j in 1:3]
b = [Foo(rand()) for j in 1:3]
@show A * b
end
runlocal()
end

addprocs(2)
@everywhere using DistributedArrays
@everywhere let
struct Foo{T<:Number}
x::T
end
Base.:+(a::Foo, b::Foo) = Foo(a.x + b.x)
Base.:*(a::Foo, b::Foo) = Foo(a.x * b.x)
Base.:zero(a::Foo{T}) where {T} = Foo(zero(T))
function rundistributed()
A = @DArray [Foo(rand()) for i in 1:3, j in 1:3]
b = @DArray [Foo(rand()) for j in 1:3]
@show A * b
end
rundistributed()
end
```

Thanks,
James

Output:

```
ERROR: On worker 2:
MethodError: Cannot `convert` an object of type Int64 to an object of type Foo{Float64}
Closest candidates are:
convert(::Type{T}, ::T) where T at essentials.jl:154
Foo{Float64}(::Any) where T<:Number at REPL[6]:3 (method too new to be called from this world context.)
fill! at ./array.jl:283
#253 at /home/cookj/.julia/packages/DistributedArrays/f3HAT/src/linalg.jl:111
run_work_thunk at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/process_messages.jl:56
#remotecall_fetch#148 at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/remotecall.jl:364
remotecall_fetch at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/remotecall.jl:364
#remotecall_fetch#152 at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/remotecall.jl:406
remotecall_fetch at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/remotecall.jl:406 [inlined]
#252 at /home/cookj/.julia/packages/DistributedArrays/f3HAT/src/linalg.jl:107 [inlined]
#672 at ./asyncmap.jl:100
macro expansion at ./asyncmap.jl:235 [inlined]
#688 at ./task.jl:259
#remotecall_wait#154(::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}, ::Function, ::Function, ::Distributed.Worker, ::Module, ::Vararg{Any,N} where N) at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/remotecall.jl:421
remotecall_wait(::Function, ::Distributed.Worker, ::Module, ::Vararg{Any,N} where N) at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/remotecall.jl:412
#remotecall_wait#157(::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}, ::Function, ::Function, ::Int64, ::Module, ::Vararg{Any,N} where N) at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/remotecall.jl:433
remotecall_wait(::Function, ::Int64, ::Module, ::Vararg{Any,N} where N) at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/remotecall.jl:433
(::getfield(Distributed, Symbol("##163#165")){Module,Expr})() at ./task.jl:259

...and 2 more exception(s).

Stacktrace:
[1] sync_end(::Array{Any,1}) at ./task.jl:226
[2] macro expansion at ./task.jl:245 [inlined]
[3] remotecall_eval(::Module, ::Array{Int64,1}, ::Expr) at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/macros.jl:206
[4] top-level scope at /home/cookj/builds/julia/usr/share/julia/stdlib/v1.0/Distributed/src/macros.jl:190
```

Contributor guide

No contributing guide indexed for this repository

Assessment

This issue has not been assessed yet.

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.