update in BBBB for sparse B

examples/solve_sdpa.jl

@@ -34,8 +34,8 @@ model=read_sdpa("examples/data/theta1.dat-s")
 # model=read_from_file("examples/data/theta1.dat-s")
 # model=read_from_file("examples/data/maxG11.dat-s") #use with "datarank = -1"
 
-# set_optimizer(model, Loraine.Optimizer{Float64})
-set_optimizer(model, Loraine.Optimizer{Float64x2})
+set_optimizer(model, Loraine.Optimizer{Float64})
+# set_optimizer(model, Loraine.Optimizer{Float64x2})
 
 # Loraine options
 

src/Solvers.jl

@@ -235,7 +235,7 @@ function load(model, options::Dict; T = Float64)
 
     if verb > 0
         t1 = time()
-        @printf("\n *** Loraine.jl v0.2.3 ***\n")
+        @printf("\n *** Loraine.jl v0.2.4 ***\n")
         @printf(" *** Initialisation STARTS\n")
     end
 

src/makeBBBB.jl

@@ -50,9 +50,9 @@ function makeBBBBsi(ilmi,Ailmi,AAilmi,myA,Wilmi::Matrix{T},n,to,qA,sigmaA) where
         # tmp1 = zeros(Float64,size(Wilmi, 2), size(Ailmi[1], 1))
         tmp  = zeros(T,size(Wilmi, 2), size(Ailmi[1], 1))
         i = sigmaA[ii,ilmi]
-        # if ii <= qA[1]
-        if 1==1
-             # @show "one"
+        if ii <= qA[1]
+        # if 1==0
+            # @show "one"
             # @show ii
             @timeit to "BBBBone" begin
                 @timeit to "BBBBone1" begin
@@ -98,6 +98,7 @@ function makeBBBBsi(ilmi,Ailmi,AAilmi,myA,Wilmi::Matrix{T},n,to,qA,sigmaA) where
             end
         # elseif ii <= qA[2]
          elseif 1==0
+        # @show "two"
             @timeit to "BBBBtwo" begin
             mul!(tmp1,Ailmi[i+1],Wilmi)
             @inbounds for jj = ii:n
@@ -162,12 +163,14 @@ function makeBBBBsi(ilmi,Ailmi,AAilmi,myA,Wilmi::Matrix{T},n,to,qA,sigmaA) where
             @timeit to "BBBBthree" begin
             # @show "three"
             # @show ii
+
             if ~isempty(myA[ilmi1+i].iind)
                 myAiii = myA[ilmi1+i]
                 iii_i = myAiii.iind
                 jjj_i = myAiii.jind
                 vvv_i = myAiii.nzval
-                @inbounds for jj = ii:n
+                # @inbounds for jj = ii:n
+                @inbounds for jj = 1:n
                     j = sigmaA[jj,ilmi]
                     if ~isempty(myA[ilmi1+j].iind)
                         myAjjj = myA[ilmi1+j]

src/model.jl

@@ -144,7 +144,7 @@ function prep_sparse!(A,n,i,nzA,sigmaA,qA)
     d2 = zeros(Float64,n)
     d3 = zeros(Float64,n)
 
-    kappa = 900.
+    kappa = 100.
     for j = 1:n
         nzA[j,i] = nnz(A[i,j+1])
     end