signal_processing/parallel.back at main · MozammilQ/signal_processing · GitHub

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using Distributed

num_cores=4
server_specs=("root@192.168.1.2",num_cores)
machines=Vector{typeof(server_specs)}(undef,1)
machines[1]=server_specs
node_working_dir="/home/red/Desktop/Julia_Workspaces/sig_proc"
server_pids=addprocs(machines,max_parallel=20,dir=node_working_dir)


@fetch myid()

using SharedArrays
s_arr=SharedArray{Float32}(1,init=false,workers())


@everywhere [2] begin
    f(x)=2*x
    ff(x)=3*x
    end

@fetchfrom 2

@everywhere [3] x=5


@spawnat 2 for i in 1:10^4 end


arr=[Complex(i,j) for i=rand(100),j=rand(100)]

fft([Complex(i,j) for i=rand(100),j=rand(100)])


f(x)=2*x
x=5

put!(RemoteChannel(2),f(x))
put!(RemoteChannel(3),f(x))


for i in workers()
    print("Result from: ")
    print(i)
    print("  -->> ")
    println(remotecall_fetch(f,i,i))
end

fetch(@spawnat 2 f(x))


## Calculating factorial on all nodes

for i in workers()
    print("Result from: ")
    print(i)
    print("  -->> ")
    println(remotecall_fetch(factorial,i,i))
end


put!(RemoteChannel(2), ff(x)=3*x)