diff --git a/test/perf/arrayalloc/Makefile b/test/perf/arrayalloc/Makefile
deleted file mode 100644
index a514914fe19eb..0000000000000
--- a/test/perf/arrayalloc/Makefile
+++ /dev/null
@@ -1,14 +0,0 @@
-JULIAHOME := $(abspath ../../..)
-include $(JULIAHOME)/Make.inc
-
-ifndef PYTHONBIN
-	PYTHONBIN = python
-endif
-
-all: python julia
-
-python:
-	$(PYTHONBIN) lucompletepiv.py
-
-julia:
-	@$(call spawn,$(JULIA_EXECUTABLE)) lucompletepiv.jl
diff --git a/test/perf/arrayalloc/lucompletepiv.jl b/test/perf/arrayalloc/lucompletepiv.jl
deleted file mode 100644
index 7ce7dc5eb6f8d..0000000000000
--- a/test/perf/arrayalloc/lucompletepiv.jl
+++ /dev/null
@@ -1,55 +0,0 @@
-# This file is a part of Julia. License is MIT: http://julialang.org/license
-
-function lucompletepivCopy!(A)
-    n = size(A, 1)
-    rowpiv=zeros(Int, n-1)
-    colpiv=zeros(Int, n-1)
-    for k = 1:n-1
-        As = abs(A[k:n, k:n])
-        μ, λ = ind2sub(size(As), indmax(As))
-        μ += k-1; λ += k-1
-        rowpiv[k] = μ
-        A[[k,μ], 1:n] = A[[μ,k], 1:n]
-        colpiv[k] = λ
-        A[1:n, [k,λ]] = A[1:n, [λ,k]]
-        if A[k,k] ≠ 0
-            ρ = k+1:n
-            A[ρ, k] = A[ρ, k]/A[k, k]
-            A[ρ, ρ] = A[ρ, ρ] - A[ρ, k:k] * A[k:k, ρ]
-        end
-    end
-    return (A, rowpiv, colpiv)
-end
-
-function lucompletepivSub!(A)
-    n = size(A, 1)
-    rowpiv=zeros(Int, n-1)
-    colpiv=zeros(Int, n-1)
-    for k = 1:n-1
-        As = abs(sub(A, k:n, k:n))
-        μ, λ = ind2sub(size(As), indmax(As))
-        μ += k-1; λ += k-1
-        rowpiv[k] = μ
-        A[[k,μ], 1:n] = sub(A, [μ,k], 1:n)
-        colpiv[k] = λ
-        A[1:n, [k,λ]] = sub(A, 1:n, [λ,k])
-        if A[k,k] ≠ 0
-            ρ = k+1:n
-            A[ρ, k] = sub(A, ρ, k)/A[k, k]
-            A[ρ, ρ] = sub(A, ρ, ρ) - sub(A, ρ, k) * sub(A, k, ρ)
-        end
-    end
-    return (A, rowpiv, colpiv)
-end
-
-println("Julia version with copy slices")
-for n = [100, 250, 500, 1000]
-    A = randn(n,n)
-    @printf("size %4d matrix factorized in %6.3f seconds\n", n, mean([@elapsed lucompletepivCopy!(copy(A)) for i = 1:3]))
-end
-
-println("\nJulia version with view slices")
-for n = [100, 250, 500, 1000]
-    A = randn(n,n)
-    @printf("size %4d matrix factorized in %6.3f seconds\n", n, mean([@elapsed lucompletepivSub!(copy(A)) for i = 1:3]))
-end
diff --git a/test/perf/arrayalloc/lucompletepiv.py b/test/perf/arrayalloc/lucompletepiv.py
deleted file mode 100644
index 81785ab307976..0000000000000
--- a/test/perf/arrayalloc/lucompletepiv.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import numpy as np
-import time
-
-def lucompletepiv(A):
-    assert np.size(A, 0) == np.size(A, 1)
-    n = np.size(A, 1)
-    rowpiv = np.zeros(n-1, dtype=int)
-    colpiv = np.zeros(n-1, dtype=int)
-    for k in range(n-1):
-        Asub = abs(A[k:n, k:n])
-        mu, lam = np.unravel_index(np.argmax(Asub), np.shape(Asub))
-        mu, lam = mu + k, lam + k
-        rowpiv[k] = mu
-        A[[k, mu], :n] = A[[mu, k], :n]
-        colpiv[k] = lam
-        A[:n, [k, lam]] = A[:n, [lam, k]]
-        if A[k, k] != 0:
-            rho = slice(k+1, n)
-            A[rho, k] = A[rho, k]/A[k, k]
-            A[rho, rho] -= np.dot(np.reshape(A[rho, k], (n - (k + 1), 1)),
-                                  np.reshape(A[k, rho], (1, n - (k + 1))))
-    return (A, rowpiv, colpiv)
-
-
-for n in [100, 250, 500, 1000]:
-    tt = []
-    for rep in range(3):
-        A = np.random.randn(n, n)
-        t0 = time.time()
-        lucompletepiv(A.copy())
-        tt.append(time.time() - t0)
-
-    print("size %4d matrix factorized in %6.3f seconds" % (n, sum(tt)/3))
-
-print("")