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Use Adapt and remove custom KAArray type
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@michel2323
michel2323 committed Jul 10, 2023
1 parent 3cf8956 commit 840c834
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Showing 7 changed files with 56 additions and 75 deletions.
2 changes: 1 addition & 1 deletion Project.toml
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@@ -1,7 +1,7 @@
name = "ExaAdmm"
uuid = "4d6a948c-1075-4240-a564-361a5d4e22a2"
authors = ["Youngdae Kim <[email protected]>", "Kibaek Kim <[email protected]>", "Weiqi Zhang <[email protected]>", "Bowen Li <[email protected]>", "François Pacaud <[email protected]>", "Michel Schanen <[email protected]>"]
version = "0.5.1"
version = "0.6.0"

[deps]
Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
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2 changes: 0 additions & 2 deletions README.md
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Expand Up @@ -38,8 +38,6 @@ and the same example on an AMD GPU:
using ExaAdmm
using AMDGPU

ExaAdmm.KAArray{T}(n::Int, ::ROCBackend) where {T} = ROCArray{T}(undef, n)

env, mod = solve_acopf(
"case1354pegase.m";
rho_pq=1e1,
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2 changes: 0 additions & 2 deletions src/ExaAdmm.jl
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Expand Up @@ -16,8 +16,6 @@ const KA = KernelAbstractions

export solve_acopf

struct KAArray{T} end

include("utils/parse_matpower.jl")
include("utils/opfdata.jl")
include("utils/environment.jl")
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95 changes: 48 additions & 47 deletions src/utils/opfdata.jl
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Expand Up @@ -581,13 +581,13 @@ end
function get_generator_data(data::OPFData, device; use_gpu=false)
ngen = length(data.generators)

pgmin = KAArray{Float64}(ngen, device)
pgmax = KAArray{Float64}(ngen, device)
qgmin = KAArray{Float64}(ngen, device)
qgmax = KAArray{Float64}(ngen, device)
c2 = KAArray{Float64}(ngen, device)
c1 = KAArray{Float64}(ngen, device)
c0 = KAArray{Float64}(ngen, device)
pgmin = adapt(device, zeros(Float64, ngen))
pgmax = adapt(device, zeros(Float64, ngen))
qgmin = adapt(device, zeros(Float64, ngen))
qgmax = adapt(device, zeros(Float64, ngen))
c2 = adapt(device, zeros(Float64, ngen))
c1 = adapt(device, zeros(Float64, ngen))
c0 = adapt(device, zeros(Float64, ngen))

Pmin = Float64[data.generators[g].Pmin for g in 1:ngen]
Pmax = Float64[data.generators[g].Pmax for g in 1:ngen]
Expand Down Expand Up @@ -666,16 +666,16 @@ function get_bus_data(data::OPFData, device; use_gpu=false)
Vmin = Float64[data.buses[i].Vmin for i=1:nbus]
Vmax = Float64[data.buses[i].Vmax for i=1:nbus]

cuFrIdx = KAArray{Int}(length(FrIdx), device)
cuToIdx = KAArray{Int}(length(ToIdx), device)
cuGenIdx = KAArray{Int}(length(GenIdx), device)
cuFrStart = KAArray{Int}(length(FrStart), device)
cuToStart = KAArray{Int}(length(ToStart), device)
cuGenStart = KAArray{Int}(length(GenStart), device)
cuPd = KAArray{Float64}(nbus, device)
cuQd = KAArray{Float64}(nbus, device)
cuVmax = KAArray{Float64}(nbus, device)
cuVmin = KAArray{Float64}(nbus, device)
cuFrIdx = adapt(device, zeros(Int, length(FrIdx)))
cuToIdx = adapt(device, zeros(Int, length(ToIdx)))
cuGenIdx = adapt(device, zeros(Int, length(GenIdx)))
cuFrStart = adapt(device, zeros(Int, length(FrStart)))
cuToStart = adapt(device, zeros(Int, length(ToStart)))
cuGenStart = adapt(device, zeros(Int, length(GenStart)))
cuPd = adapt(device, zeros(Float64, nbus))
cuQd = adapt(device, zeros(Float64, nbus))
cuVmax = adapt(device, zeros(Float64, nbus))
cuVmin = adapt(device, zeros(Float64, nbus))

copyto!(cuFrIdx, FrIdx)
copyto!(cuToIdx, ToIdx)
Expand Down Expand Up @@ -777,21 +777,22 @@ function get_branch_data(data::OPFData, device; use_gpu::Bool=false, tight_facto
end
rateA = [ data.lines[l].rateA == 0.0 ? 1e3 : tight_factor*(data.lines[l].rateA / data.baseMVA)^2 for l=1:nline ]

cuYshR = KAArray{Float64}(length(ybus.YshR), device)
cuYshI = KAArray{Float64}(length(ybus.YshI), device)
cuYffR = KAArray{Float64}(nline, device)
cuYffI = KAArray{Float64}(nline, device)
cuYftR = KAArray{Float64}(nline, device)
cuYftI = KAArray{Float64}(nline, device)
cuYttR = KAArray{Float64}(nline, device)
cuYttI = KAArray{Float64}(nline, device)
cuYtfR = KAArray{Float64}(nline, device)
cuYtfI = KAArray{Float64}(nline, device)
cuFrVmBound = KAArray{Float64}(2*nline, device)
cuToVmBound = KAArray{Float64}(2*nline, device)
cuFrVaBound = KAArray{Float64}(2*nline, device)
cuToVaBound = KAArray{Float64}(2*nline, device)
cuRateA = KAArray{Float64}(nline, device)
cuYshR = adapt(device, zeros(Float64, length(ybus.YshR)))
cuYshI = adapt(device, zeros(Float64, length(ybus.YshI)))
cuYffR = adapt(device, zeros(Float64, nline))
cuYffI = adapt(device, zeros(Float64, nline))
cuYftR = adapt(device, zeros(Float64, nline))

cuYftI = adapt(device, zeros(Float64, nline))
cuYttR = adapt(device, zeros(Float64, nline))
cuYttI = adapt(device, zeros(Float64, nline))
cuYtfR = adapt(device, zeros(Float64, nline))
cuYtfI = adapt(device, zeros(Float64, nline))
cuFrVmBound = adapt(device, zeros(Float64, 2*nline))
cuToVmBound = adapt(device, zeros(Float64, 2*nline))
cuFrVaBound = adapt(device, zeros(Float64, 2*nline))
cuToVaBound = adapt(device, zeros(Float64, 2*nline))
cuRateA = adapt(device, zeros(Float64, nline))
copyto!(cuYshR, ybus.YshR)
copyto!(cuYshI, ybus.YshI)
copyto!(cuYffR, ybus.YffR)
Expand Down Expand Up @@ -836,7 +837,7 @@ function get_branch_bus_index(data::OPFData, device; use_gpu=false)

brBusIdx = Int[ x for l=1:nline for x in (BusIdx[lines[l].from], BusIdx[lines[l].to]) ]

cu_brBusIdx = KAArray{Int}(2*nline, device)
cu_brBusIdx = adapt(device, zeros(Int, 2*nline))
copyto!(cu_brBusIdx, brBusIdx)
return cu_brBusIdx
end
Expand Down Expand Up @@ -869,9 +870,9 @@ end
function get_generator_bus_data(data::OPFData, device; use_gpu=false)
ngen = length(data.generators)

vgmin = KAArray{Float64}(ngen, device)
vgmax = KAArray{Float64}(ngen, device)
vm_setpoint = KAArray{Float64}(ngen, device)
vgmin = adapt(device, zeros(Float64, ngen))
vgmax = adapt(device, zeros(Float64, ngen))
vm_setpoint = adapt(device, zeros(Float64, ngen))

Vgmin = Float64[data.buses[data.BusIdx[data.generators[g].bus]].Vmin for g in 1:ngen]
Vgmax = Float64[data.buses[data.BusIdx[data.generators[g].bus]].Vmax for g in 1:ngen]
Expand Down Expand Up @@ -909,8 +910,8 @@ end
function get_generator_primary_control(data::OPFData, device; droop::Float64=0.04, use_gpu=false)
ngen = length(data.generators)

alpha_g = KAArray{Float64}(ngen, device)
pg_setpoint = KAArray{Float64}(ngen, device)
alpha_g = adapt(device, zeros(Float64, ngen))
pg_setpoint = adapt(device, zeros(Float64, ngen))

Alpha_g = Float64[-((1/droop)*data.generators[g].Pmax) for g in 1:ngen]
Pg_setpoint = Float64[(data.generators[g].Pmin + data.generators[g].Pmax)/2 for g in 1:ngen]
Expand Down Expand Up @@ -966,13 +967,13 @@ function get_storage_data(data::OPFData, device; use_gpu=false)
eta_dis = Float64[data.storages[s].eta_dischg for s=1:nstorage]
energy_setpoint = Float64[data.storages[s].energy_setpoint for s=1:nstorage]

cuChg_min = KAArray{Float64}(nstorage, device)
cuChg_max = KAArray{Float64}(nstorage, device)
cuEnergy_min = KAArray{Float64}(nstorage, device)
cuEnergy_max = KAArray{Float64}(nstorage, device)
cuEta_chg = KAArray{Float64}(nstorage, device)
cuEta_dis = KAArray{Float64}(nstorage, device)
cuEnergy_setpoint = KAArray{Float64}(nstorage, device)
cuChg_min = adapt(device, zeros(Float64, nstorage))
cuChg_max = adapt(device, zeros(Float64, nstorage))
cuEnergy_min = adapt(device, zeros(Float64, nstorage))
cuEnergy_max = adapt(device, zeros(Float64, nstorage))
cuEta_chg = adapt(device, zeros(Float64, nstorage))
cuEta_dis = adapt(device, zeros(Float64, nstorage))
cuEnergy_setpoint = adapt(device, zeros(Float64, nstorage))

copyto!(cuChg_min, chg_min)
copyto!(cuChg_max, chg_max)
Expand Down Expand Up @@ -1010,8 +1011,8 @@ function get_bus_storage_index(data::OPFData, device; use_gpu=false)
StorageIdx = Int[s for b=1:nbus for s in data.BusStorages[b]]
StorageStart = accumulate(+, vcat([1], [length(data.BusStorages[b]) for b=1:nbus]))

cuStorageIdx = KAArray{Int}(length(StorageIdx), device)
cuStorageStart = KAArray{Int}(length(StorageStart), device)
cuStorageIdx = adapt(device, zeros(Int, length(StorageIdx)))
cuStorageStart = adapt(device, zeros(Int, length(StorageStart)))

copyto!(cuStorageIdx, StorageIdx)
copyto!(cuStorageStart, StorageStart)
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2 changes: 1 addition & 1 deletion src/utils/utilities_ka.jl
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Expand Up @@ -45,7 +45,7 @@ function LinearAlgebra.norm(x::CuArray, device::Nothing)
end

function LinearAlgebra.norm(x, device)
y = KAArray{Float64}(1, device)
y = adapt(device, zeros(eltype(x), 1))
n = length(x)
norm_kernel(device)(Val{n}(), x, y, ndrange=n)
KA.synchronize(device)
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14 changes: 3 additions & 11 deletions test/algorithms/acopf_update_ka.jl
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Expand Up @@ -4,18 +4,10 @@ using KernelAbstractions
KA = KernelAbstractions
devices = []
if CUDA.has_cuda_gpu() || AMDGPU.has_rocm_gpu()
if CUDA.has_cuda_gpu()
function ExaAdmm.KAArray{T}(n::Int, device::CUDABackend) where {T}
return CuArray{T}(undef, n)
end
push!(devices, CUDABackend())
end
if CUDA.has_cuda_gpu()
push!(devices, CUDABackend())
end
if AMDGPU.has_rocm_gpu()
# Set for crusher login node to avoid other users
AMDGPU.default_device!(AMDGPU.devices()[2])
function ExaAdmm.KAArray{T}(n::Int, device::ROCBackend) where {T}
return ROCArray{T}(undef, n)
end
push!(devices, ROCBackend())
end
end
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14 changes: 3 additions & 11 deletions test/algorithms/qpsub_update_ka.jl
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Expand Up @@ -4,18 +4,10 @@ using KernelAbstractions
KA = KernelAbstractions
devices = []
if CUDA.has_cuda_gpu() || AMDGPU.has_rocm_gpu()
if CUDA.has_cuda_gpu()
function ExaAdmm.KAArray{T}(n::Int, device::CUDABackend) where {T}
return CuArray{T}(undef, n)
end
push!(devices, CUDABackend())
end
if CUDA.has_cuda_gpu()
push!(devices, CUDABackend())
end
if AMDGPU.has_rocm_gpu()
# Set for crusher login node to avoid other users
AMDGPU.default_device!(AMDGPU.devices()[2])
function ExaAdmm.KAArray{T}(n::Int, device::ROCBackend) where {T}
return ROCArray{T}(undef, n)
end
push!(devices, ROCBackend())
end
end
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