Search code in Julia

[Julieta Martinez]

Without multithreading and due to JuliaLang/julia#939, implementing the lookup-table-based search of MCQ in Julia is simply not competitive. We should revisit this once Julia gets decent multithreading and faster partial sort.

[Julieta Martinez]

This would also remove the C++ code that we have and, save the CUDA code, make the project fully-Julian.

[Julieta Martinez]

I have written a Julia version here

Rayuela.jl/src/Linscan.jl

Lines 40 to 90 in 40555c0

 function linscan_pq_julia( 
   B::Matrix{Int16},          # m-by-n. The database, encoded 
   X::Matrix{Cfloat},         # d-by-nq. The queries. 
   C::Vector{Matrix{Cfloat}}, # The cluster centers 
   knn:: Int = 10000)           # Number of knn results to return 
  
   m, n  = size( B ) 
   d, nq = size( X ) 
   subdims = splitarray( 1:d, m ) 
  
   @show knn, nq 
   dists = zeros( Cfloat, knn, nq ) 
   idx   = zeros(  Cuint, knn, nq ) 
   Bt = B' 
  
   # Compute distance tables between queries and codebooks 
   tables = Vector{Matrix{Cfloat}}(m) 
   for i = 1:m 
     # tables[i] = Distances.pairwise(Distances.SqEuclidean(), X[subdims[i],:], C[i]) 
     tables[i] = Distances.pairwise(Distances.SqEuclidean(), C[i], X[subdims[i],:]) 
   end 
  
   # Compute approximate distances and sort 
   @inbounds for i = 1:nq # Loop over each query 
  
     # println(i) 
     xq_dists  = zeros(Cfloat, n) 
     p         = zeros(Cuint, n) 
  
      for j = 1:m # Loop over each codebook 
       t = tables[j][:,i] 
  
       for k = 1:n # Loop over each code 
         xq_dists[k] += t[ Bt[k,j] ] 
       end 
     end 
  
     # p = sortperm(xq_dists; alg=PartialQuickSort(knn)) 
     sortperm!(p, xq_dists; alg=PartialQuickSort(knn)) 
     # @simd for j=1:n; p[j]=j; end 
     # sortperm!(p, xq_dists; alg=PartialQuickSort(knn), initialized=true) 
     # sort(xq_dists; alg=PartialQuickSort(knn)) 
  
     dists[:,i] = xq_dists[ p[1:knn] ] 
     idx[:,i]   = p[1:knn] 
  
   end # @inbounds 
  
   return dists, idx 
  
 end 

Too slow in the meantime.