close #1073

disable print in gk.jl for benchmarking
adjust some iteration counts

examples/gk/gk.jl

@@ -8,7 +8,7 @@
 function myunifskew(n)
     A = zeros(n, n)
 
-    print("A[i,j] initialized with zeros \n");
+    #print("A[i,j] initialized with zeros \n");
 
     for i=1:n
     	for j=1:i-1
@@ -28,8 +28,8 @@ function myunifskew(n)
 
     	end
     	if rem(i,1000) == 0
-	    print(i)
-	    print("\n")
+	    #print(i)
+	    #print("\n")
     	end
     end
 
@@ -64,15 +64,15 @@ function gk(n, myeps)
 
 	csum = zeros(n)
 
-	tic()
+#	tic()
 	while(stop != 1)
      	    t=t+1
      	    iter=t
      	    #iteration number
 
      	    if rem(iter, 100) == 0
-         	print(iter)
-		print("\n")
+         	#print(iter)
+		#print("\n")
      	    end
 
 	    for i=1:n
@@ -114,7 +114,7 @@ function gk(n, myeps)
 
 	end
 
-	times[KK] = toc()
+	times[KK] = 0#toc()
 	iteration[KK] = iter
 
 	x = X/t
@@ -133,7 +133,7 @@ function gk(n, myeps)
     	end
 
 	if Axepse==n
-	    print(" \n Ax <= eps*e  \n")
+	    #print(" \n Ax <= eps*e  \n")
 	end
 
 	#if A*x <= eps*e
@@ -148,38 +148,38 @@ function gk(n, myeps)
 	end
 
         if errorlmt ==n
-    	    print("Assertion condition is satisfied i.e. AX-U<10^-8 \n")
+    	    #print("Assertion condition is satisfied i.e. AX-U<10^-8 \n")
 	else
     	    print("Error:  AX-U<10^-8 not satisfied \n")
 	end
 
 	#print("welcome")	
 
-	print("Time for \n")
-	print(eps)
-	print("\n")
-	print("is  \n")
-	print(times[KK])
-	print("\n")
-	print("Number of iteration is \n")
-	print(iteration[KK])
-	print("\n")
+	# print("Time for \n")
+	# print(eps)
+	# print("\n")
+	# print("is  \n")
+	# print(times[KK])
+	# print("\n")
+	# print("Number of iteration is \n")
+	# print(iteration[KK])
+	# print("\n")
     end
 
-    print("Epsilon vector is \n")
-    print(myeps)
-    print("\n")
-    print("time vector is \n ")
-    print(times)
-    print("\n")
-    print("Iteration Vector is \n")
-    print(iteration)
-    print("\n \n")
+    # print("Epsilon vector is \n")
+    # print(myeps)
+    # print("\n")
+    # print("time vector is \n ")
+    # print(times)
+    # print("\n")
+    # print("Iteration Vector is \n")
+    # print(iteration)
+    # print("\n \n")
 
     #out = [myeps, time, iteration]
     #print("Epsilon-Time-Iteration tradeoff \n")
     #print(out)
-    print("\n \n")
+    #print("\n \n")
 
 end
 #end # @profile begin

examples/stockcorr.jl

@@ -7,7 +7,7 @@ function stockcorr()
     CurrentPrice = [78. 102.]     # Initial Prices of the two stocks
     Corr = [1. 0.4; 0.4 1.]       # Correlation Matrix
     T = 500                       # Number of days to simulate = 2years = 500days
-    n = 100000                    # Number of simulations
+    n = 3000                      # Number of simulations
     dt = 1/250                    # Time step (1year = 250days)
     Div=[0.01 0.01]               # Dividend
     Vol=[0.2 0.3]                 # Volatility

test/perf2/perf2.jl

@@ -0,0 +1,72 @@
+macro timeit(ex,name)
+    quote
+        t = Inf
+        for i=1:5
+            t = min(t, @elapsed $ex)
+        end
+        println($name, "\t", t*1000)
+    end
+end
+
+srand(1776)  # get more consistent times
+
+require("$JULIA_HOME/../../examples/list.jl")
+
+function listn1n2(n1::Int64,n2::Int64)
+    l1 = Nil{Int64}()
+    for i=n2:-1:n1
+        l1 = Cons{Int64}(i,l1)
+    end
+    l1
+end
+
+@timeit listn1n2(1,10^6) "cons    "
+gc()
+
+
+# issue #950
+load("$JULIA_HOME/../../examples/gk/gk.jl")
+@timeit gk(350,[0.1]) "gk      "
+
+# issue #942
+require("linalg_sparse.jl")
+s = sparse(ones(280,280));
+@timeit s*s "sparsemul"
+
+# issue #939
+y = [500000:-1:1];
+@timeit sortperm(y) "sortperm"
+
+# issue #938
+x = 1:600000;
+@timeit sparse(x,x,x) "sparserang"
+
+# issue #445
+load("$JULIA_HOME/../../examples/stockcorr.jl")
+@timeit stockcorr() "stockcorr"
+
+
+function cmp_with_func(x::Vector, f::Function)
+    count::Int = 0
+    for i = 1:length(x)-1
+        if f(x[i], x[i+1])
+            count += 1
+        end
+    end
+    return count
+end
+
+x = randn(200_000)
+@timeit (for n in 1:10; count = cmp_with_func(x, isless) end) "funarg  "
+
+
+function arith_vectorized(b,c,d)
+    a = b.*c + d + 1.0
+end
+
+len = 1_000_000
+b = randn(len)
+c = randn(len)
+d = randn(len)
+
+@timeit (for n in 1:10; a = arith_vectorized(b,c,d); end) "vectoriz"