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DVR-jl
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Removed testing files in favor of examples

This commit is contained in:
ysyapa 2023-03-19 14:59:37 -04:00
parent 1e2bad2cd9
commit 84c41e0646
3 changed files with 47 additions and 113 deletions
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47
example.ipynb Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# prerequisites: KrylovKit, TensorOperations, LinearAlgebra, CUDA#tb/cutensor (for GPU mode)\n",
"\n",
"include(\"CPU.jl\") # using CPU mode\n",
"T = Float32\n",
"\n",
"V_test(r2::T)::T =\n",
" -4 * exp(-r2 / 4)\n",
"\n",
"d = 3\n",
"n = 3\n",
"N = 6\n",
"L::T = 12.0\n",
"mu::T = 0.5\n",
"n_imag = 1\n",
"\n",
"H = HOperator{T}(V_test, 3, 3, N, L, 0.5f0, 1)\n",
"@time evals, evecs, info = eig(H, 5)\n",
"print(info.numops, \" operations : \")\n",
"println(evals)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 1.8.5",
"language": "julia",
"name": "julia-1.8"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.8.5"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}

70
tester.ipynb
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@ -1,70 +0,0 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# ./En.run -d 3 -n 3 -e 5 -c eps=0 -c pot=v_gauss,v0=-4,r=2 -N 6 -L 5:14 -c n_imag=1\n",
"\n",
"include(\"CPU.jl\")\n",
"\n",
"T=Float32\n",
"\n",
"function V_test(r2::T)::T\n",
" return -4*exp(-r2/4)\n",
"end\n",
"\n",
"N=6\n",
"for L::T in 5.0:14.0\n",
" H=HOperator{T}(V_test,3,3,N,L,0.5f0,1)\n",
" @time evals,evecs,info=eig(H,5)\n",
" print(info.numops,\" operations : \")\n",
" println(evals)\n",
"end"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# ./En.run -d 3 -n 2 -e 5 -c eps=0 -c pot=v_gauss,v0=-4,r=2 -N 32 -L 5:14 -c n_imag=0\n",
"\n",
"include(\"CPU.jl\")\n",
"\n",
"T=Float64\n",
"\n",
"function V_test(r2::T)::T\n",
" return -4*exp(-r2/4)\n",
"end\n",
"\n",
"N=32\n",
"for L::T in 5.0:14.0\n",
" H=HOperator{T}(V_test,3,2,N,L)\n",
" @time evals,evecs,info=eig(H,5)\n",
" print(info.numops,\" operations : \")\n",
" println(evals)\n",
"end"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 1.8.5",
"language": "julia",
"name": "julia-1.8"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.8.5"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}

43
tester.jl
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@ -1,43 +0,0 @@
# ./En.run -d 3 -n 3 -e 5 -c eps=0 -c pot=v_gauss,v0=-4,r=2 -N 6 -L 5:14 -c n_imag=1
using CUDA
GPU_mode = !("CPU" in ARGS) && CUDA.functional() && CUDA.has_cuda() && CUDA.has_cuda_gpu()
println("Running with ",Threads.nthreads()," thread(s)")
if GPU_mode
include("GPU.jl")
println("Available GPUs:")
print(" ")
println.(name.(devices()))
else
include("CPU.jl")
end
T=Float32
function V_zero(r2::T)::T
return 0.0
end
function V_test(r2::T)::T
return -4*exp(-r2/4)
end
N=6
n_image=1
μ=0.5
levels=5
for L::T in 5.0:14.0
H=HOperator{T}(V_test,3,3,N,L,convert(T,μ),n_image)
if GPU_mode
CUDA.@time evals,evecs,info=eig(H,levels)
else
@time evals,evecs,info=eig(H,levels)
end
print(info.numops," operations : ")
println(evals)
end