AsynchronousIterativeAlgorithms.jl

Installation

julia> ] add AsynchronousIterativeAlgorithms

Quick start

# Launch multiple processes (or remote machines)using Distributed;addprocs(5)# Instantiate and precompile environment in all processes@everywhere (using Pkg; Pkg.activate(@__DIR__); Pkg.instantiate(); Pkg.precompile())# You can now use AsynchronousIterativeAlgorithms@everywhere (using AsynchronousIterativeAlgorithms;const AIA= AsynchronousIterativeAlgorithms)

# define on all processes@everywherebegin# algorithmmutable struct SGD<:AbstractAlgorithm{Vector{Float64},Vector{Float64}}        stepsize::Float64        previous_q::Vector{Float64}# previous querySGD(stepsize::Float64)=new(stepsize, Float64[])end# initialisation stepfunction (sgd::SGD)(problem::Any)        sgd.previous_q=rand(problem.n)end# worker stepfunction (sgd::SGD)(q::Vector{Float64}, problem::Any)         sgd.stepsize* problem.∇f(q,rand(1:problem.m))end# asynchronous central stepfunction (sgd::SGD)(a::Vector{Float64}, worker::Int64, problem::Any)         sgd.previous_q-= aendend

@everywherebeginstruct LRMSE        A::Union{Matrix{Float64}, Nothing}        b::Union{Vector{Float64}, Nothing}        n::Int64        m::Int64        L::Float64# Lipschitz constant of f        ∇f::FunctionendfunctionLRMSE(A::Matrix{Float64}, b::Vector{Float64})        m, n=size(A)        L=maximum(A'*A)∇f(x)= A'* (A* x- b)/ n∇f(x,i)= A[i,:]* (A[i,:]'* x- b[i])LRMSE(A, b, n, m, L, ∇f)endend

# Provide the stopping criteriastopat= (iteration=1000, time=42.)# Instanciate your algorithmsgd=SGD(0.01)# Create a function that returns an instance of your problem for a given pidproblem_constructor= (pid)->LRMSE(rand(42,10),rand(42))# And you can start!history=start(sgd, problem_constructor, stopat);