diff --git a/.editorconfig b/.editorconfig
index 2f69c3f4bb7674ad95bd758cf2665572aab64280..81951082f05d398c94390564d10854fc6b9029c8 100644
--- a/.editorconfig
+++ b/.editorconfig
@@ -12,3 +12,7 @@ max_line_length = 100
[*.F08]
indent_style = space
indent_size = 3
+
+[*.jl]
+indent_style = space
+indent_size = 4
diff --git a/src/benchmarks/rodinia-srad/julia/README b/src/benchmarks/rodinia-srad/julia/README
new file mode 100644
index 0000000000000000000000000000000000000000..d7f99e7b8a9c51579cd393e4d118a3cddc07a66d
--- /dev/null
+++ b/src/benchmarks/rodinia-srad/julia/README
@@ -0,0 +1,12 @@
+Usage:
+srad 128 128 0 31 0 31 0.5 2
+
+128 //number of rows in the domain
+128 //number of cols in the domain
+0 //y1 position of the speckle
+31 //y2 position of the speckle
+0 //x1 position of the speckle
+31 //x2 position of the speckle
+0.5 //Lambda value
+2 //number of iterations
+
diff --git a/src/benchmarks/rodinia-srad/julia/srad.jl b/src/benchmarks/rodinia-srad/julia/srad.jl
new file mode 100755
index 0000000000000000000000000000000000000000..3f97a0d9903ab1d272ad40820c1ccbe45fbdcc76
--- /dev/null
+++ b/src/benchmarks/rodinia-srad/julia/srad.jl
@@ -0,0 +1,148 @@
+#!/usr/bin/env julia
+
+const OUTPUT = haskey(ENV, "OUTPUT")
+
+function usage()
+ prog = basename(Base.source_path())
+# println(STDERR,"Usage ",prog," <rows> <cols> <y1> <y2> <x1> <x2> <no. of threads><lamda> <no. of iter>")
+ println(STDERR,"Usage ",prog," <rows> <cols> <y1> <y2> <x1> <x2> <lamda> <no. of iter>")
+ println(STDERR,"\t<rows> - number of rows")
+ println(STDERR, "\t<cols> - number of cols\n")
+ println(STDERR, "\t<y1> - y1 value of the speckle\n")
+ println(STDERR, "\t<y2> - y2 value of the speckle\n")
+ println(STDERR, "\t<x1> - x1 value of the speckle\n")
+ println(STDERR, "\t<x2> - x2 value of the speckle\n")
+# println(STDERR, "\t<no. of threads> - no. of threads\n")
+ println(STDERR, "\t<lamda> - lambda (0,1)\n")
+ println(STDERR, "\t<no. of iter> - number of iterations\n")
+ exit(1)
+end
+
+
+function main(args)
+ if length(args) != 8
+ usage()
+ end
+ rows = parse(Int64,args[1])
+ cols = parse(Int64,args[2])
+ if ((rows % 16) != 0) | ((cols % 16) != 0)
+ println(STDERR,"rows and cols must be mutiples of 16")
+ exit(1)
+ end
+ r1 = parse(Int32,args[3]) + 1
+ r2 = parse(Int32,args[4]) + 1
+ c1 = parse(Int32,args[5]) + 1
+ c2 = parse(Int32,args[6]) + 1
+ lambda = parse(Float32,args[7])
+ niter = parse(Int32,args[8])
+
+ size_R = (r2 - r1 + 1) * (c2 - c1 + 1);
+
+ iN::Array{Int32,1} = [i-1 for i in 1:rows]
+ iS::Array{Int32,1} = [i+1 for i in 1:rows]
+ jW::Array{Int32,1} = [j-1 for j in 1:cols]
+ jE::Array{Int32,1} = [j+1 for j in 1:cols]
+ iN[1] = 1
+ iS[rows] = rows
+ jW[1] = 1
+ jE[cols] = cols
+
+ dN::SharedArray{Float32,2} = SharedArray(Float32,(rows,cols))
+ dS::SharedArray{Float32,2} = SharedArray(Float32,(rows,cols))
+ dW::SharedArray{Float32,2} = SharedArray(Float32,(rows,cols))
+ dE::SharedArray{Float32,2} = SharedArray(Float32,(rows,cols))
+
+ println("Randomizing the input matrix")
+
+ srand(7)
+ I = rand(Float32,rows,cols)
+ J::SharedArray{Float32,2} = SharedArray(Float32,(rows,cols),init = J -> J[Base.localindexes(J)] = exp.(I[Base.localindexes(J)]))
+ c::SharedArray{Float32,2} = SharedArray(Float32,(rows,cols))
+
+ println("Start the SRAD main loop")
+
+ tic()
+
+ sum::Float32 = 0
+ sum2::Float32 = 0
+ for iter in 1:niter
+ sum = 0
+ sum2 = 0
+ for i in r1:r2
+ for j in c1:c2
+ tmp = J[i,j]
+ sum += tmp
+ sum2 += tmp * tmp
+ end
+ end
+ end
+
+ meanROI::Float32 = sum / size_R
+ varROI::Float32 = (sum / size_R) - meanROI * meanROI
+ q0sqr::Float32 = varROI / (meanROI * meanROI)
+
+ @sync @parallel for i in 1:size(J,1)
+ for j in size(J,2)
+ Jc = J[i,j]
+
+ # directional derivates
+ dN[i,j] = J[iN[i],j] - Jc
+ dS[i,j] = J[iS[i],j] - Jc
+ dW[i,j] = J[i,jW[j]] - Jc
+ dE[i,j] = J[i,jE[j]] - Jc
+
+ G2 = (dN[i,j] * dN[i,j] + dS[i,j] * dS[i,j] + dW[i,j] * dW[i,j] +
+ dE[i,j] * dE[i,j]) /
+ (Jc * Jc)
+
+ L = (dN[i,j] + dS[i,j] + dW[i,j] + dE[i,j]) / Jc
+
+ num = (0.5 * G2) - ((1.0 / 16.0) * (L * L))
+ den = 1 + (0.25 * L)
+ qsqr = num / (den * den)
+
+ # diffusion coefficent (equ 33)
+ den = (qsqr - q0sqr) / (q0sqr * (1 + q0sqr))
+ c[i,j] = 1.0 / (1.0 + den)
+
+ # saturate diffusion coefficent
+ if (c[i,j] < 0)
+ c[i,j] = 0
+ elseif (c[i,j] > 1)
+ c[i,j] = 1
+ end
+ end
+ end
+
+ @sync @parallel for i in 1:size(J,1)
+ for j in 1:size(J,2)
+ # diffusion coefficient
+ cN = c[i,j]
+ cS = c[iS[i],j]
+ cW = c[i,j]
+ cE = c[i,jE[j]]
+
+ # divergence (equ 58)
+ D = cN * dN[i,j] + cS * dS[i,j] + cW * dW[i,j] + cE * dE[i,j]
+
+ # image update (equ 61)
+ J[i,j] += 0.25 * lambda * D
+ end
+ end
+
+ toc()
+
+ println("Computation done")
+
+ if OUTPUT
+ f = open("output.txt","w")
+ for i in 1:size(J,1)
+ for j in 1:size(J,2)
+ print(f,@sprintf("%.5f ",J[i,j]))
+ end
+ println(f)
+ end
+ close(f)
+ end
+end
+