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Author: Dvegrod

Diff for: docs/src/examples/memcopyCellArray3D.MD

@@ -1 +1,29 @@
 
+
+# Basic example: time regression
+
+Given a very simple function, which can be replaced by any other the user might want, we will build a time regression performance test suite.
+
+```julia
+function testfun(a :: Int)
+    c = 1
+
+    for i in 1:a
+        c = c + (i ^ 2) / c
+    end
+
+    return c
+end
+```
+
+The source file for the test suite would then be:
+
+```julia
+using PerfTest
+
+@testset "Test unit" for i in [10000000,20000000,30000000]
+    x = @perftest testfun(10)
+end
+```
+
+This source specifies that the function shall be tested for the 3 different values on the test loop. The methodology used is time regression, this methodology will compare the median time attained with an historical reference and fail if outside the default tolerance interval.

Diff for: docs/src/examples/memcopyCellArray3D_ParallelStencil.MD

@@ -1 +1,131 @@
+# Roofline example: option pricing
 
+In this example we setup a roofline model methodology to test the resolution of a binomial tree using a slow implementation.
+
+```julia
+rfd_rt(r,t_per_p) = rfd(t) = exp(-r * t * t_per_p)
+up_st(sigma, t_per_p) = exp(sigma * sqrt(t_per_p))
+
+struct _Parameters
+    sigma   :: Float64
+    periods :: Int
+    t_per_p :: Float64
+    rfd     :: Function
+    up      :: Float64
+    K       :: Float64
+    S0      :: Float64
+    p       :: Float64
+end
+
+function setupProblem(sigma, t, periods_per_t, risk_free_rate, strike, price, p) :: _Parameters
+    return _Parameters(
+        sigma,
+        t * periods_per_t,
+        1 / periods_per_t,
+        rfd_rt(risk_free_rate, 1 / periods_per_t),
+        up_st(sigma, 1 / periods_per_t),
+        strike,
+        price,
+        p
+    )
+end
+
+function createBinomialTree(p :: _Parameters)::Tuple{Matrix,Array}
+
+    nodes = (p.periods + 1) * p.periods ÷ 2
+    # A and b
+    Tree = zeros(Float64, nodes, nodes)
+    B = zeros(Float64, nodes)
+
+    # Fill the body of the tree with the discounted expectations
+    for period in 1:(p.periods-1)
+        _nodes = ((period-1)*period÷2+1):((period+1)*(period+0)÷2)
+        for node in _nodes
+            Tree[node, node] = -1
+            Tree[node, node+period] = p.p * p.rfd(p.periods - period)
+            Tree[node, node+period+1] = 1 - p.p * p.rfd(p.periods - period)
+        end
+    end
+
+    # Fill the last level of the tree with the prices at maturity
+    xa = ((p.periods - 1) * p.periods ÷ 2 + 1)
+    xb = ((p.periods + 1) * (p.periods + 0) ÷ 2)
+    down = 1 / p.up
+
+    for node in xa:xb
+        Tree[node, node] = 1
+        B[node] = max((p.S0 * p.up^(xb - node) * down^(node - xa)) - p.K, 0.0)
+    end
+    return Tree, B
+end
+
+
+function solveTree(A::Matrix, b::Array, periods::Int)::Array
+
+    nodes = (periods + 1) * periods ÷ 2
+    X = zeros(Float64, nodes)
+    # Last level nodes from a to b
+    xa = ((periods - 1) * periods ÷ 2 + 1)
+    xb = ((periods + 1) * (periods + 0) ÷ 2)
+    for node in xa:xb
+        X[node] = b[node]
+    end
+    # Tree core nodes
+    for period in (periods-1):-1:1
+        _nodes = ((period-1)*period÷2+1):((period+1)*(period+0)÷2)
+        for node in _nodes
+            X[node] = A[node, node+period] * b[node+period] + A[node, node+period+1] * b[node+period+1]
+            b[node] = X[node]
+        end
+    end
+
+    return X
+end
+
+option_price(solution :: Array) = solution[1]
+
+```
+
+The following is the recipe file that sets up the performance test suite:
+
+```julia
+using Test
+using PerfTest
+
+include("main3.jl")
+
+# CONFIG
+@perftest_config begin
+    regression.enabled = false
+    roofline.autoflops = true
+    roofline.tolerance.min_percentage = 1.0
+end
+
+
+@testset "Performance Tests" begin
+
+    @testset "Tree construction" begin
+
+        @testset "Periods" for n_periods in [16, 64, 128]
+
+            param = setupProblem(0.04, 1, n_periods, 0.04, 100, 100, 0.5)
+
+            @roofline actual_flops=:autoflop target_ratio=0.05 begin
+                mem = ((:iterator + 1) * :iterator)
+                :autoflop / mem
+            end
+            A, b = createBinomialTree(param)
+
+
+            @perftest solveTree(A, b, param.periods)
+        end
+    end
+end
+```
+
+The recipe file specifies the following:
+ - The target will be evaluated using a roofline model
+ - The basic regression methodology is disabled
+ - The tolerance below the threshold will be zero
+ - The autoflops feature is enabled
+ - The roofline macro additionally receives how to calculate the flop count (actual_lops=:autoflop) and the threshold of the actual performance vs model performance is 5%