Update performance tests

test/perf/indvec.jl

@@ -14,9 +14,8 @@ function bench_add(n)
 end
 
 bench_add(10)
-gc_disable()
+gc_enable(false)
 @time bench_add(1000000)
 @time bench_add(1000000)
 @time bench_add(1000000)
-gc_enable()
-
+gc_enable(true)

test/perf/macro.jl

@@ -4,8 +4,8 @@ using JuMP
 
 function test_linear(N)
     m = Model()
-    @defVar(m, x[1:10N,1:5N])
-    @defVar(m, y[1:N,1:N,1:N])
+    @variable(m, x[1:10N,1:5N])
+    @variable(m, y[1:N,1:N,1:N])
 
     for z in 1:10
         @constraint(m,
@@ -24,8 +24,8 @@ end
 
 function test_quad(N)
     m = Model()
-    @defVar(m, x[1:10N,1:5N])
-    @defVar(m, y[1:N,1:N,1:N])
+    @variable(m, x[1:10N,1:5N])
+    @variable(m, y[1:N,1:N,1:N])
 
     for z in 1:10
         @constraint(m,
@@ -49,8 +49,8 @@ test_linear(1)
 test_quad(1)
 for N in [20,50,100]
     println("  Running N=$(N)...")
-    N1_times = {}
-    N2_times = {}
+    N1_times = Any[]
+    N2_times = Any[]
     for iter in 1:10
         tic()
         test_linear(N)

test/perf/norms.jl

@@ -2,7 +2,7 @@ using JuMP
 
 function norm_stress1(N)
     m = Model()
-    @defVar(m, x[1:N])
+    @variable(m, x[1:N])
     for i in 1:N
         @constraint(m, norm2{x[j],j=1:i} <= i)
     end

test/perf/speed.jl

@@ -58,13 +58,13 @@ function pMedian(numFacility::Int,numCustomer::Int,numLocation::Int,useMPS)
     m = Model()
 
     # Facility locations
-    @defVar(m, 0 <= s[1:numLocation] <= 1)
+    @variable(m, 0 <= s[1:numLocation] <= 1)
 
     # Aux. variable: x_a,i = 1 iff the closest facility to a is at i
-    @defVar(m, 0 <= x[1:numLocation,1:numCustomer] <= 1)
+    @variable(m, 0 <= x[1:numLocation,1:numCustomer] <= 1)
 
     # Objective: min distance
-    @setObjective(m, Max, sum{abs(customerLocations[a]-i)*x[i,a], a = 1:numCustomer, i = 1:numLocation} )
+    @objective(m, Max, sum{abs(customerLocations[a]-i)*x[i,a], a = 1:numCustomer, i = 1:numLocation} )
 
     # Constraints
     for a in 1:numCustomer
@@ -104,9 +104,9 @@ function cont5(n,useMPS)
 
     tic()
     mod = Model()
-    @defVar(mod,  0 <= y[0:m,0:n] <= 1)
-    @defVar(mod, -1 <= u[1:m] <= 1)
-    @setObjective(mod, Min, y[0,0])
+    @variable(mod,  0 <= y[0:m,0:n] <= 1)
+    @variable(mod, -1 <= u[1:m] <= 1)
+    @objective(mod, Min, y[0,0])
 
     # PDE
     for i = 0:m1
@@ -169,4 +169,3 @@ function RunTests()
 end
 
 RunTests()
-

test/perf/speed2.jl

@@ -19,13 +19,13 @@ function pMedian(numFacility::Int,numCustomer::Int,numLocation::Int)
     m = Model()
 
     # Facility locations
-    @defVar(m, 0 <= s[1:numLocation] <= 1)
+    @variable(m, 0 <= s[1:numLocation] <= 1)
 
     # Aux. variable: x_a,i = 1 iff the closest facility to a is at i
-    @defVar(m, 0 <= x[1:numLocation,1:numCustomer] <= 1)
+    @variable(m, 0 <= x[1:numLocation,1:numCustomer] <= 1)
 
     # Objective: min distance
-    @setObjective(m, Max, sum{abs(customerLocations[a]-i)*x[i,a], a = 1:numCustomer, i = 1:numLocation} )
+    @objective(m, Max, sum{abs(customerLocations[a]-i)*x[i,a], a = 1:numCustomer, i = 1:numLocation} )
 
     # Constraints
     for a in 1:numCustomer
@@ -61,9 +61,9 @@ function cont5(n)
 
     tic()
     mod = Model()
-    @defVar(mod,  0 <= y[0:m,0:n] <= 1)
-    @defVar(mod, -1 <= u[1:m] <= 1)
-    @setObjective(mod, Min, 0.25*dx*( (y[m,0] - yt[1])^2 +
+    @variable(mod,  0 <= y[0:m,0:n] <= 1)
+    @variable(mod, -1 <= u[1:m] <= 1)
+    @objective(mod, Min, 0.25*dx*( (y[m,0] - yt[1])^2 +
        2*sum{ (y[m,j]-yt[j+1])^2, j=1:n1} + (y[m,n]-yt[n+1])^2) +
        0.25*a*dt*(2*sum{u[i]^2,i=1:m1} + u[m]^2))
 

test/perf/timetoprint.jl

@@ -9,7 +9,7 @@ run(`$(ENV["_"]) -e """
 using JuMP
 m = Model()
 N = 100
-@defVar(m, x[1:N])
+@variable(m, x[1:N])
 @constraint(m, sum{i*x[i],i=1:N} >= N)
 @time JuMP.aff_str(JuMP.REPLMode, m.linconstr[end].terms)
 @time JuMP.model_str(JuMP.REPLMode, m)"""
@@ -23,7 +23,7 @@ run(`$(ENV["_"]) -e """
 using JuMP
 m = Model()
 N = 100
-@defVar(m, x[1:N])
+@variable(m, x[1:N])
 @constraint(m, sum{i*x[i],i=1:N} >= N)
 @time JuMP.model_str(JuMP.REPLMode, m)"""
 `)
@@ -36,7 +36,7 @@ run(`$(ENV["_"]) -e """
 using JuMP
 m = Model()
 N = 10000
-@defVar(m, x[1:N])
+@variable(m, x[1:N])
 @constraint(m, sum{i*x[i],i=1:N} >= N)
 @time sprint(print, m)"""
 `)
@@ -49,11 +49,11 @@ run(`$(ENV["_"]) -e """
 using JuMP
 m = Model()
 N = 10
-@defVar(m, x1[1:N])
-@defVar(m, x2[1:N,f=1:N])
-@defVar(m, x3[1:N,f=1:2:N])
-@defVar(m, x4[[:a,:b,:c]])
-@defVar(m, x5[[:a,:b,:c],[:d,"e",4]])
+@variable(m, x1[1:N])
+@variable(m, x2[1:N,f=1:N])
+@variable(m, x3[1:N,f=1:2:N])
+@variable(m, x4[[:a,:b,:c]])
+@variable(m, x5[[:a,:b,:c],[:d,"e",4]])
 @constraint(m,
     sum{i*x1[i],i=1:N} +
     sum{i*f*x2[i,f],i=1:N,f=1:N} + 

test/perf/vector_speedtest.jl

@@ -3,11 +3,11 @@ using JuMP
 function test(n::Int)
     m = Model()
     a = rand(n,n)
-    @defVar(m,x[1:n,1:n])
+    @variable(m,x[1:n,1:n])
     b = rand(n,n,n)
-    @defVar(m,y[1:n,1:n,1:n])
+    @variable(m,y[1:n,1:n,1:n])
     c = rand(n)
-    @defVar(m,z[1:n])
+    @variable(m,z[1:n])
 
     #initialize
     @constraint(m,sum{c[i]*z[i],i=1:n}<=0)
@@ -17,24 +17,24 @@ function test(n::Int)
     @constraint(m,sum{c[i]*z[i],i=1:n}<=1)
     println("Vector with sum{}: $(toq())")
     tic()
-    @constraint(m,dot(c,z) <= 1)
-    println("Vector with dot() : $(toq())")
+    @constraint(m,vecdot(c,z) <= 1)
+    println("Vector with vecdot() : $(toq())")
 
     #2D Matrix
     tic()
     @constraint(m,sum{a[i,j]*x[i,j],i=1:n,j=1:n}<=1)
     println("2D Matrix with sum{}: $(toq())")
     tic()
-    @constraint(m,dot(a,x)<=1)
-    println("2D Matrix with bigdot(): $(toq())")
+    @constraint(m,vecdot(a,x)<=1)
+    println("2D Matrix with bigvecdot(): $(toq())")
 
     #3D Matrix
     tic()
     @constraint(m,sum{b[i,j,k]*y[i,j,k],i=1:n,j=1:n,k=1:n}<=1)
     println("3D Matrix with sum{}: $(toq())")
     tic()
-    @constraint(m,dot(b,y)<=1)
-    println("3D Matrix with dot(): $(toq())")
+    @constraint(m,vecdot(b,y)<=1)
+    println("3D Matrix with vecdot(): $(toq())")
     return 0
 end