diff --git a/scripts/run_experiments.jl b/scripts/run_experiments.jl
index 148cf5549408a901b9b0abb24f7b0c626451d9fe..1c4fb44563630b2ae9e46e3bea0f29ccbae7b811 100644
--- a/scripts/run_experiments.jl
+++ b/scripts/run_experiments.jl
@@ -1,13 +1,10 @@
 # experiments
 
+using Distributed
 using Random: MersenneTwister
 using LinearAlgebra: Diagonal, I, dot, norm, mul!, diagm
 using Statistics: median
 
-using CSV
-using Colors: HSV
-using DataFrames
-using Distributed
 @everywhere using DualTVDD
 @everywhere using DualTVDD:
     DualTVL1ROFOpProblem,
@@ -15,6 +12,10 @@ using Distributed
     SurrogateAlgorithm,
     DualTVDDSurrogateAlgorithm,
     init, step!, fetch, fetch_u, gradient, divergence, normB, energy, residual
+
+using CSV
+using Colors: HSV
+using DataFrames
 using DualTVDD: fetch_u
 using FFTW
 using FileIO
@@ -270,10 +271,11 @@ function experiment_scaling_opticalflow(ctx)
     λ = 0.01
     β = 0.001
 
-    ninner = 300
-    Mdir = 2 * floor(Int, sqrt(nworkers())) # to have enough workers available
-    M = (Mdir, Mdir)
-    overlap = (5, 5)
+    ninner = 500
+    #Mdir = 2 * floor(Int, sqrt(nworkers())) # to have enough workers available
+    Mdir = nworkers()
+    M = (4, Mdir)
+    overlap = (10, 10)
 
     stopenergy = 130.
     ntimings = 3
@@ -298,6 +300,7 @@ function experiment_scaling_opticalflow(ctx)
 
     tg = timeit(galg)
 
+    # divide by 2^2 due to coloring
     nparallel = prod(M) ÷ 2^2
     ws = workers()
     @assert nparallel <= length(ws)
@@ -315,7 +318,7 @@ function experiment_scaling_opticalflow(ctx)
 
     CSV.write(joinpath(ctx.outdir, "timings.csv"), df)
     savedata(joinpath(ctx.outdir, "data.tex");
-        lambda=λ, beta=β, Mdir, M=prod(M),
+        lambda=λ, beta=β, M1=M[1], M2=M[2], M=prod(M),
         ntimings, stopenergy, ninner,
         width=size(fo, 2), height=size(fo, 1))
 end
diff --git a/scripts/run_parallel_scaling.jl b/scripts/run_parallel_scaling.jl
new file mode 100644
index 0000000000000000000000000000000000000000..626617977a0ff188de831d5ec798c1dcb6fb20f3
--- /dev/null
+++ b/scripts/run_parallel_scaling.jl
@@ -0,0 +1,20 @@
+# do not use a startup file: `julia --startup-file=no`
+# otherwise precompilation will be done over and over again
+
+using Pkg
+Pkg.activate(@__DIR__)
+Pkg.instantiate()
+
+using Distributed
+addprocs(8)
+
+@everywhere using Pkg
+@everywhere Pkg.activate(@__DIR__)
+@everywhere Pkg.instantiate()
+
+@everywhere using Revise
+includet(joinpath(@__DIR__, "run_experiments.jl"))
+
+const datapath = joinpath(@__DIR__, "..", "..", "data")
+ctx = Util.Context(datapath)
+ctx(experiment_scaling_opticalflow, "fd/scaling/opticalflow")