# Rewriting function on CPU for execution on GPU
**URL:** https://discourse.julialang.org/t/rewriting-function-on-cpu-for-execution-on-gpu/31608
**Category:** GPU
**Created:** [November 28, 2019, 6:06am UTC](https://discourse.julialang.org/t/rewriting-function-on-cpu-for-execution-on-gpu/31608 "2019-11-28T06:06:33Z")
**Posts on this page:** 5
**Page:** 1
### Author:  [@ennvvy](https://discourse.julialang.org/u/ennvvy)
#### Post date: [November 28, 2019, 6:06am UTC](https://discourse.julialang.org/t/rewriting-function-on-cpu-for-execution-on-gpu/31608/1 "2019-11-28T06:06:33Z")
I am trying to execute a function that I am currently running on a CPU on the GPU. There are a few bottlenecks, like accessing elements of an array `scalar getindex is disallowed`
The code is below:
```julia
using CUDAdrv,CUDAnative,CuArrays
CuArrays.allowscalar(false)
upagents=[10,20,30,35,25,15,12,11,9]
cn=fill(0.0,40,1)
cedg=fill(0.0,40)
s=fill(0.0,40)
c=fill(0.0,40)
thet=rand(40)
the=fill(0.0,40)
C=rand(40)
A=zeros(Int,40)
A[10:20].=1
cupagents=cu(upagents)
ccn=cu(cn)
ccedg=cu(cedg)
cs=cu(s)
cc=cu(c)
cthet=cu(thet)
cthe=cu(the)
cC=cu(C)
cA=cu(A)
function update!(upagents,cn,s,c,cedg,C,thet,the,A)
for h in upagents
cn.=0.0
s.=0.0
c.=0.0
cedg.=0.0
cn[findall(x->x==1||x!=1&&rand()<0.5,A)].=1.0
cedg=exp.(-abs.(thet[h].-thet)/(1.0-C[h])).*cn #--> thet[h],C[h] doesn't work
cedg./=sum(cedg)
s=cedg.*sin.(thet)
c=cedg.*cos.(thet)
the[h]=atan(sum(s),sum(c)) #-->the[h] doesn't work
end
end
```
It would be helpful to hear comments and suggestions to implement it better.
---
### Author:  [@baggepinnen](https://discourse.julialang.org/u/baggepinnen)
#### Post date: [November 28, 2019, 6:34am UTC](https://discourse.julialang.org/t/rewriting-function-on-cpu-for-execution-on-gpu/31608/2 "2019-11-28T06:34:30Z")
> [@ennvvy](#):
>
> s=fill(0.0,40) c=fill(0.0,40) thet=rand(40) the=fill(0.0,40) C=rand(40) A=zeros(Int,40)
If these sizes are representative of the real problem, I don’t think the GPU will speed things up. GPU is useful for much larger arrays, think images.
---
### Author:  [@ennvvy](https://discourse.julialang.org/u/ennvvy)
#### Post date: [November 28, 2019, 6:39am UTC](https://discourse.julialang.org/t/rewriting-function-on-cpu-for-execution-on-gpu/31608/3 "2019-11-28T06:39:01Z")
No, they are not. This is just a representative example. It will be of the order of \>10,000
---
### Author:  [@baggepinnen](https://discourse.julialang.org/u/baggepinnen)
#### Post date: [November 29, 2019, 5:45am UTC](https://discourse.julialang.org/t/rewriting-function-on-cpu-for-execution-on-gpu/31608/4 "2019-11-29T05:45:41Z")
> [@ennvvy](#):
>
> cn[findall(x-\>x==1||x!=1&&rand()\<0.5,A)].=1.0
Instead of `findall`, try logical indexing
```julia
cn[A .== 1 .| A .!= 1 .& rand.() .< 0.5] .= 1.0
```
or something like that
---
### Author:  [@ennvvy](https://discourse.julialang.org/u/ennvvy)
#### Post date: [November 29, 2019, 5:48am UTC](https://discourse.julialang.org/t/rewriting-function-on-cpu-for-execution-on-gpu/31608/5 "2019-11-29T05:48:00Z")
I tried this [Writing simple kernel functions (EM algorithm) - #7 by ennvvy](https://discourse.julialang.org/t/writing-simple-kernel-functions-em-algorithm/24787/7). Also, the scalar indexing that I have highlighted, dont work! I get the following error:
```julia
scalar getindex is disallowed
Stacktrace:
[1] error(::String) at ./error.jl:33
[2] assertscalar(::String) at /root/.julia/packages/GPUArrays/0lvhc/src/indexing.jl:14
[3] getindex at /root/.julia/packages/GPUArrays/0lvhc/src/indexing.jl:54 [inlined]
[4] iterate at ./abstractarray.jl:914 [inlined]
[5] iterate at ./abstractarray.jl:912 [inlined]
[6] update!(::CuArray{Float32,1,Nothing}, ::CuArray{Float32,2,Nothing}, ::CuArray{Float32,1,Nothing}, ::CuArray{Float32,1,Nothing}, ::CuArray{Float32,1,Nothing}, ::CuArray{Float32,1,Nothing}, ::CuArray{Float32,1,Nothing}, ::CuArray{Float32,1,Nothing}, ::CuArray{Float32,1,Nothing}) at ./In[7]:25
[7] ##core#472() at /root/.julia/packages/BenchmarkTools/7aqwe/src/execution.jl:297
[8] ##sample#473(::BenchmarkTools.Parameters) at /root/.julia/packages/BenchmarkTools/7aqwe/src/execution.jl:303
[9] #_run#8(::Bool, ::String, ::Base.Iterators.Pairs{Symbol,Integer,NTuple{4,Symbol},NamedTuple{(:samples, :evals, :gctrial, :gcsample),Tuple{Int64,Int64,Bool,Bool}}}, ::typeof(BenchmarkTools._run), ::BenchmarkTools.Benchmark{Symbol("##benchmark#471")}, ::BenchmarkTools.Parameters) at /root/.julia/packages/BenchmarkTools/7aqwe/src/execution.jl:331
[10] (::Base.var"#inner#2"{Base.Iterators.Pairs{Symbol,Integer,NTuple{5,Symbol},NamedTuple{(:verbose, :samples, :evals, :gctrial, :gcsample),Tuple{Bool,Int64,Int64,Bool,Bool}}},typeof(BenchmarkTools._run),Tuple{BenchmarkTools.Benchmark{Symbol("##benchmark#471")},BenchmarkTools.Parameters}})() at ./none:0
[11] #invokelatest#1 at ./essentials.jl:713 [inlined]
[12] #invokelatest at ./none:0 [inlined]
[13] #run_result#37 at /root/.julia/packages/BenchmarkTools/7aqwe/src/execution.jl:32 [inlined]
[14] #run_result at ./none:0 [inlined]
[15] #run#39(::Base.Iterators.Pairs{Symbol,Integer,NTuple{5,Symbol},NamedTuple{(:verbose, :samples, :evals, :gctrial, :gcsample),Tuple{Bool,Int64,Int64,Bool,Bool}}}, ::typeof(run), ::BenchmarkTools.Benchmark{Symbol("##benchmark#471")}, ::BenchmarkTools.Parameters) at /root/.julia/packages/BenchmarkTools/7aqwe/src/execution.jl:46
[16] #run at ./none:0 [inlined] (repeats 2 times)
[17] #warmup#42 at /root/.julia/packages/BenchmarkTools/7aqwe/src/execution.jl:79 [inlined]
[18] warmup(::BenchmarkTools.Benchmark{Symbol("##benchmark#471")}) at /root/.julia/packages/BenchmarkTools/7aqwe/src/execution.jl:79
[19] top-level scope at /root/.julia/packages/BenchmarkTools/7aqwe/src/execution.jl:390
[20] top-level scope at In[9]:100:
```