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zXJVtaR*BkoX}}BB5Pq!DTAm^WV4ymwD8!MshmOo_#9<{b`*wIS6|0Ru80H0B0-!-P zQ+CIEdE>%P`$`-*l#_j@L{nJazVM)u!nJ`mR!@&b73GG|jQm=GnV2oZBcFmj{70sWXPN{bZ&uO|0{)3d= zk)GmRB{L*R=sADmIUI<>FFp&m!f{JN8?Rm{+}JZ(Sg- z7$1)a1wF!DF%>( z{QUAOxl`THOUprZXZyWgx~z93E;O`D!~{r-5i3t^+WML?zMUqVll8xilHptnyDG0iTB%yd7#%CcnOW*LUQ17s z8dL(+GNzTM&Smm!|Nr%NYbj4}kv7t_k* zCmWg;in99Jd2vE(8$_&Mw2+U}c8Az%G?%9~UT|sahJO?dF-ct@k*viQ$!=>|3vXdC zkE>BSv!jNG;iTO3QvEAh;7@w6U&~jGYvkKI-;n2e>iwUVe5+;bd^vx+8clMwY_}rf zDaP^N?e>=7*=dsti0-ukc>yj^I25rM1p&eW|01au18wSN~b zh|m>bHt=HG-V)r-#jNC-;MIh$P&1{}k)Zaea7QvO`#){kW}ZB8lSTCSPj4|4_<0OfsN4D&^U&N?u+1C2XfBa)}W;8F{H=ZY5XMe#){oQ>rwS2KR(!O+`bl91vm|0`baYZV_m99QP$ zcSCDcfb^H4*EN1ltM|0+kDu$VmO_0@cf{*m>Z|*U6LCbNVgTLm3)#O;5BR5Q@R2*Ff1Np>q66mUND5c}; zwwy28$v?b|@Oz)J#+oIAcmt4QqR&`2EdOJI)~ZJs zVP&eyC?AopH^ynPK|+|y6;z2~^j)mRX>l|_Zdk;VM(*Cj<;8WcHpnN3@n!YKJHK}EkCBM6o#x9_O!kq!V0d@x;WvbRcx>_=5qMDEOyq{}&E)8b zvm`zu-}TrSp?tO3E~v`LN)aB1&q0K~EEXBPD`dnL!FfXaqa?=IXRLN)$96-%ldw7Y zd2}pD%a#iUH;=6pMsPyJE~M$^F`)*TpmJ<31qipRlDD@)jMVn5zP855sZ*z3J$2KX zmJf7Y-YmAPX~}ivOGabMM3)i&_>EWG_o18C@Yf`N-SL0@b<>SksIT$f`+4tyoBsDF z)%R}x@Apo0iTJJm{k`>F?eQDVz4sZ-xJgs@=D#&<*J%BCo1$&r=AG;4*c%_9H3F@Q z@<+V z!8-*E4$Xw<4-QZ_n^-HhoI3S{++uU~HH_(rmghgSxvN3FeJ+JneQygDya>7a*MG&^ i*rP^x$GUSb+;Z>cu4}YAZkZ<3e> Date: Fri, 25 Aug 2023 10:44:47 -0400 Subject: [PATCH 02/17] add applynoise for PauliFrame to GPUExt --- .../QuantumCliffordGPUExt.jl | 3 +- ext/QuantumCliffordGPUExt/apply_noise.jl | 40 +++++++++++++++++++ 2 files changed, 42 insertions(+), 1 deletion(-) create mode 100644 ext/QuantumCliffordGPUExt/apply_noise.jl diff --git a/ext/QuantumCliffordGPUExt/QuantumCliffordGPUExt.jl b/ext/QuantumCliffordGPUExt/QuantumCliffordGPUExt.jl index c79571c8c..fd564ed2c 100644 --- a/ext/QuantumCliffordGPUExt/QuantumCliffordGPUExt.jl +++ b/ext/QuantumCliffordGPUExt/QuantumCliffordGPUExt.jl @@ -2,7 +2,7 @@ module QuantumCliffordGPUExt using CUDA using QuantumClifford -import QuantumClifford: to_cpu, to_gpu, _apply!, apply!, pftrajectories, fastcolumn, fastrow +import QuantumClifford: to_cpu, to_gpu, _apply!, apply!, pftrajectories, fastcolumn, fastrow, applynoise! include("utils.jl") include("types.jl") @@ -10,6 +10,7 @@ include("adapters.jl") include("apply.jl") include("pauli_frames.jl") include("fastmemlayout.jl") +include("apply_noise.jl") # todo hide _apply function later. only for internal use end diff --git a/ext/QuantumCliffordGPUExt/apply_noise.jl b/ext/QuantumCliffordGPUExt/apply_noise.jl new file mode 100644 index 000000000..0bb7386e6 --- /dev/null +++ b/ext/QuantumCliffordGPUExt/apply_noise.jl @@ -0,0 +1,40 @@ +using QuantumClifford: _div, _mod + +function applynoise!(frame::PauliFrameGPU{T},noise::UnbiasedUncorrelatedNoise,i::Int) where {T <: Unsigned} + p = noise.errprobthird + lowbit = T(1) + ibig = _div(T,i-1)+1 + ismall = _mod(T,i-1) + ismallm = lowbit<<(ismall) + + stab = frame.frame + xzs = tab(stab).xzs + rows::Unsigned = size(stab, 1) + + @run_cuda applynoise_kernel(xzs, p, ibig, ismallm, rows) rows + return frame +end + + +function applynoise_kernel(xzs::DeviceMatrix{Tme}, + p::Real, + ibig::Int, # todo why is this Int and others Tme? + ismallm::Tme, # why is rows Unsigned sometimes and sometimes Int? + rows::Unsigned) where {Tme <: Unsigned} + + f = (blockIdx().x - 1) * blockDim().x + threadIdx().x; + if f > rows + return nothing + end + + r = rand() # todo add type to it? is it uniform? + if r < p # X error + xzs[ibig,f] ⊻= ismallm + elseif r < 2p # Z error + xzs[end÷2+ibig,f] ⊻= ismallm + elseif r < 3p # Y error + xzs[ibig,f] ⊻= ismallm + xzs[end÷2+ibig,f] ⊻= ismallm + end + return nothing +end From e3ceed2f742f901892fae7b7e2708bf858c1fee6 Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 12:46:23 -0400 Subject: [PATCH 03/17] add applynoise test --- test/test_gpu.jl | 29 ++++++++++++++++++++++++++++- 1 file changed, 28 insertions(+), 1 deletion(-) diff --git a/test/test_gpu.jl b/test/test_gpu.jl index 6740c6404..80d13fdb1 100644 --- a/test/test_gpu.jl +++ b/test/test_gpu.jl @@ -34,8 +34,13 @@ function apply_single_or_double_qubit_and_compare(n, s, s_gpu) end end +function approx(a, b, threshold) + maximum(abs.(a - b)) <= threshold +end + + @testset "GPU" begin - CUDA.allowscalar(false) # todo how to add this to all tests. + CUDA.allowscalar(false) # make sure we are using GPU kernels and not iterating on indices @test begin p = random_pauli(3) @@ -70,6 +75,7 @@ end true end + # todo add a test with a bigger circuit that covers the partitioning idea @test begin # todo test MRZ and other random gates statistically circuit = [sHadamard(2), sHadamard(5), sCNOT(1, 2), sCNOT(2, 5), sMZ(1), sMZ(2), sMZ(4), sMZ(5)] @@ -118,4 +124,25 @@ end end true end + + @test begin + # test applynoise + N = 4 + trajectories = 10000 + f = PauliFrame(trajectories, N, N); + f = to_gpu(f) + p = 0.1 + measurements = pftrajectories(f, [ + sMZ(1, 1), + sHadamard(2), + sMZ(2, 2), + NoiseOp(UnbiasedUncorrelatedNoise(p), [3, 4]), + sMZ(3, 3), + sHadamard(4), + sMZ(4, 4) + ]).measurements + avg_result = to_cpu(sum(measurements, dims=1) / trajectories) + error_threshold = 0.02 + approx(vec(avg_result), [0, .5, 2p, .5], error_threshold) + end end From 4168bf4922cebaac709533ee5d9751cf0373edd2 Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 12:52:59 -0400 Subject: [PATCH 04/17] cleanup --- test/test_gpu.jl | 1 - 1 file changed, 1 deletion(-) diff --git a/test/test_gpu.jl b/test/test_gpu.jl index 80d13fdb1..a82f3bea3 100644 --- a/test/test_gpu.jl +++ b/test/test_gpu.jl @@ -75,7 +75,6 @@ end true end - # todo add a test with a bigger circuit that covers the partitioning idea @test begin # todo test MRZ and other random gates statistically circuit = [sHadamard(2), sHadamard(5), sCNOT(1, 2), sCNOT(2, 5), sMZ(1), sMZ(2), sMZ(4), sMZ(5)] From 949ada43b5d209526aafc6c3c74a0465554e9eef Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 13:39:36 -0400 Subject: [PATCH 05/17] add InnerGPUType=UInt32, InnerCPUType=UInt64 --- ext/QuantumCliffordGPUExt/adapters.jl | 17 +++++++++++------ 1 file changed, 11 insertions(+), 6 deletions(-) diff --git a/ext/QuantumCliffordGPUExt/adapters.jl b/ext/QuantumCliffordGPUExt/adapters.jl index 5b009728a..cfb2a8ded 100644 --- a/ext/QuantumCliffordGPUExt/adapters.jl +++ b/ext/QuantumCliffordGPUExt/adapters.jl @@ -1,24 +1,29 @@ -# const InnerGPUType = UInt64; +const InnerGPUType = UInt32; +const InnerCPUType = UInt64; # todo. make the conversion types consiting with this... # also define a cpu default type?! -to_gpu(array::AbstractArray) = CuArray(array); +to_gpu(array::AbstractArray) = CuArray(array) to_cpu(array::AbstractArray) = Array(array); +# changes the type to InnerGPUType or InnerCPUType as well as copying to cpu/gpu +to_gpu_reinterpret(array::AbstractArray) = CuArray(reinterpret(InnerGPUType, collect(array))) +to_cpu_reinterpret(array::AbstractArray) = Array(reinterpret(InnerCPUType, collect(array))) + # maybe change the format of storing the data in gpu array # so that it is more convinient to work with them on gpu? # todo later add some type checking to avoid copying (or throw error) if the data is already on gpu/cpu to_gpu(tab::QuantumClifford.Tableau) = - QuantumClifford.Tableau(to_gpu(tab.phases), tab.nqubits, to_gpu(tab.xzs)) + QuantumClifford.Tableau(to_gpu(tab.phases), tab.nqubits, to_gpu_reinterpret(tab.xzs)) to_cpu(tab::QuantumClifford.Tableau) = - QuantumClifford.Tableau(to_cpu(tab.phases), tab.nqubits, to_cpu(tab.xzs)) + QuantumClifford.Tableau(to_cpu(tab.phases), tab.nqubits, to_cpu_reinterpret(tab.xzs)) to_gpu(pauli::QuantumClifford.PauliOperator) = - QuantumClifford.PauliOperator(to_gpu(pauli.phase), pauli.nqubits, to_gpu(pauli.xz)) + QuantumClifford.PauliOperator(to_gpu(pauli.phase), pauli.nqubits, to_gpu_reinterpret(pauli.xz)) to_cpu(pauli::QuantumClifford.PauliOperator) = - QuantumClifford.PauliOperator(to_cpu(pauli.phase), pauli.nqubits, to_cpu(pauli.xz)) + QuantumClifford.PauliOperator(to_cpu(pauli.phase), pauli.nqubits, to_cpu_reinterpret(pauli.xz)) to_gpu(stabilizer::QuantumClifford.Stabilizer) = Stabilizer(to_gpu(tab(stabilizer))) From cd0b6f9921a033889a65224812bfe0260ca1a6a0 Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 13:57:47 -0400 Subject: [PATCH 06/17] allow for parametric type transformation --- ext/QuantumCliffordGPUExt/adapters.jl | 38 ++++++++++++++------------- 1 file changed, 20 insertions(+), 18 deletions(-) diff --git a/ext/QuantumCliffordGPUExt/adapters.jl b/ext/QuantumCliffordGPUExt/adapters.jl index cfb2a8ded..86d91685a 100644 --- a/ext/QuantumCliffordGPUExt/adapters.jl +++ b/ext/QuantumCliffordGPUExt/adapters.jl @@ -7,32 +7,34 @@ to_gpu(array::AbstractArray) = CuArray(array) to_cpu(array::AbstractArray) = Array(array); # changes the type to InnerGPUType or InnerCPUType as well as copying to cpu/gpu -to_gpu_reinterpret(array::AbstractArray) = CuArray(reinterpret(InnerGPUType, collect(array))) -to_cpu_reinterpret(array::AbstractArray) = Array(reinterpret(InnerCPUType, collect(array))) +to_gpu(array::AbstractArray, tp::Type{T}) where {T <: Unsigned} = + CuArray(reinterpret(T, collect(array))) +to_cpu(array::AbstractArray, tp::Type{T}) where {T <: Unsigned} = + Array(reinterpret(T, collect(array))) # maybe change the format of storing the data in gpu array # so that it is more convinient to work with them on gpu? # todo later add some type checking to avoid copying (or throw error) if the data is already on gpu/cpu -to_gpu(tab::QuantumClifford.Tableau) = - QuantumClifford.Tableau(to_gpu(tab.phases), tab.nqubits, to_gpu_reinterpret(tab.xzs)) +to_gpu(tab::QuantumClifford.Tableau, tp::Type{T}=InnerGPUType) where {T <: Unsigned} = + QuantumClifford.Tableau(to_gpu(tab.phases), tab.nqubits, to_gpu(tab.xzs, tp)) -to_cpu(tab::QuantumClifford.Tableau) = - QuantumClifford.Tableau(to_cpu(tab.phases), tab.nqubits, to_cpu_reinterpret(tab.xzs)) +to_cpu(tab::QuantumClifford.Tableau, tp::Type{T}=InnerCPUType) where {T <: Unsigned} = + QuantumClifford.Tableau(to_cpu(tab.phases), tab.nqubits, to_cpu(tab.xzs, tp)) -to_gpu(pauli::QuantumClifford.PauliOperator) = - QuantumClifford.PauliOperator(to_gpu(pauli.phase), pauli.nqubits, to_gpu_reinterpret(pauli.xz)) +to_gpu(pauli::QuantumClifford.PauliOperator, tp::Type{T}=InnerGPUType) where {T <: Unsigned} = + QuantumClifford.PauliOperator(to_gpu(pauli.phase), pauli.nqubits, to_gpu(pauli.xz, tp)) -to_cpu(pauli::QuantumClifford.PauliOperator) = - QuantumClifford.PauliOperator(to_cpu(pauli.phase), pauli.nqubits, to_cpu_reinterpret(pauli.xz)) +to_cpu(pauli::QuantumClifford.PauliOperator, tp::Type{T}=InnerCPUType) where {T <: Unsigned} = + QuantumClifford.PauliOperator(to_cpu(pauli.phase), pauli.nqubits, to_cpu(pauli.xz, tp)) -to_gpu(stabilizer::QuantumClifford.Stabilizer) = - Stabilizer(to_gpu(tab(stabilizer))) +to_gpu(stabilizer::QuantumClifford.Stabilizer, tp::Type{T}=InnerGPUType) where {T <: Unsigned} = + Stabilizer(to_gpu(tab(stabilizer), tp)) -to_cpu(stabilizer::QuantumClifford.Stabilizer) = - Stabilizer(to_cpu(tab(stabilizer))) +to_cpu(stabilizer::QuantumClifford.Stabilizer, tp::Type{T}=InnerCPUType) where {T <: Unsigned} = + Stabilizer(to_cpu(tab(stabilizer), tp)) -to_gpu(pauli_frame::QuantumClifford.PauliFrame) = - QuantumClifford.PauliFrame(to_gpu(pauli_frame.frame), to_gpu(pauli_frame.measurements)) +to_gpu(pauli_frame::QuantumClifford.PauliFrame, tp::Type{T}=InnerGPUType) where {T <: Unsigned} = + QuantumClifford.PauliFrame(to_gpu(pauli_frame.frame, tp), to_gpu(pauli_frame.measurements)) -to_cpu(pauli_frame::QuantumClifford.PauliFrame) = - QuantumClifford.PauliFrame(to_cpu(pauli_frame.frame), to_cpu(pauli_frame.measurements)) +to_cpu(pauli_frame::QuantumClifford.PauliFrame, tp::Type{T}=InnerCPUType) where {T <: Unsigned} = + QuantumClifford.PauliFrame(to_cpu(pauli_frame.frame, tp), to_cpu(pauli_frame.measurements)) From ddfdb88e41a239e47bb6a55ab19688e763f653b2 Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 15:21:56 -0400 Subject: [PATCH 07/17] add benchmark gpu innertype --- benchmark/benchmark_gpu_innertype.jl | 86 ++++++++++++++++++++++++++++ 1 file changed, 86 insertions(+) create mode 100644 benchmark/benchmark_gpu_innertype.jl diff --git a/benchmark/benchmark_gpu_innertype.jl b/benchmark/benchmark_gpu_innertype.jl new file mode 100644 index 000000000..5eb45138b --- /dev/null +++ b/benchmark/benchmark_gpu_innertype.jl @@ -0,0 +1,86 @@ +using Revise +using QuantumClifford +using QuantumClifford: to_cpu, to_gpu +using CUDA +using BenchmarkTools +using Plots +using ProgressBars +using DataFrames +using CSV + +include("surface-code-circuit.jl") + +ints = [UInt8, UInt16, UInt32, UInt64, UInt128] +names = [:UInt8, :UInt16, :UInt32, :UInt64, :UInt128] + +function get_stats() + println("Starting tests with $(Threads.nthreads()) threads out of `Sys.CPU_THREADS = $(Sys.CPU_THREADS)`...") + + # Powers of 2 to benchmark + powers = reverse(3:18) # start from the hardest one first! (fail fast) + n_values = 2 .^ powers + + times = Dict([ + sm=>[] + for (sm, tp) in zip(names, ints) + ]) + + ccircuit = if eltype(circ) <: QuantumClifford.CompactifiedGate + circ + else + compactify_circuit(circ) + end + + CUDA.allowscalar(false) + + + for n in ProgressBar(n_values) + for (sm, T) in zip(names, ints) + gpu_frames() = to_gpu(QuantumClifford._create_pauliframe(ccircuit; trajectories=n), T) + gpu_column() = pftrajectories(fastcolumn(gpu_frames()), ccircuit), synchronize() + @show n, T + @elapsed gpu_column() # to eliminate compile time + push!(times[sm], @belapsed $gpu_column()) + end + # note. this is also measuring the time it takes to move data to gpu + end + df = DataFrame(times) + df.n_values=n_values + return df +end + +function load_stats() + if isfile("gpu_innertype_comparison.csv") + DataFrame(CSV.File("gpu_innertype_comparison.csv")) + else + get_stats() + end +end + +function save_stats(df) + CSV.write("gpu_innertype_comparison.csv", df) +end + +function plot_result(df) + my_y_axis(arrs) = begin + arr = [] + for a in arrs + append!(arr, a) + end + logarr = log.(arr) + exp.(range(min(logarr...), stop=max(logarr...), length=8)) + end + + my_plots = [] + for col in names + push!(my_plots, plot(df.n_values, df[!, col])) + end + plot(df.n_values, [df[!, col] for col in names], marker=:circle, label=reshape(["times $col" for col in names], (1, length(names))), xlabel="n", ylabel="Execution Time (s)", title="gpu inner type comparison (fast column)", xticks=df.n_values[1:2:end], xscale=:log2, yticks=my_y_axis([df[!, col] for col in names]), yscale=:log10, legend=:topleft, size=(1200, 800)) +end + +function main() + df = load_stats() + save_stats(df) + plot_result(df) + savefig("benchmark_gpu_innertype.png") +end From 3fd1d549050a97adcbcc439e8723dc87786e0385 Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 15:26:07 -0400 Subject: [PATCH 08/17] cleanup benchmark --- benchmark/benchmark_gpu_innertype.jl | 5 ----- 1 file changed, 5 deletions(-) diff --git a/benchmark/benchmark_gpu_innertype.jl b/benchmark/benchmark_gpu_innertype.jl index 5eb45138b..b1e639a2c 100644 --- a/benchmark/benchmark_gpu_innertype.jl +++ b/benchmark/benchmark_gpu_innertype.jl @@ -70,11 +70,6 @@ function plot_result(df) logarr = log.(arr) exp.(range(min(logarr...), stop=max(logarr...), length=8)) end - - my_plots = [] - for col in names - push!(my_plots, plot(df.n_values, df[!, col])) - end plot(df.n_values, [df[!, col] for col in names], marker=:circle, label=reshape(["times $col" for col in names], (1, length(names))), xlabel="n", ylabel="Execution Time (s)", title="gpu inner type comparison (fast column)", xticks=df.n_values[1:2:end], xscale=:log2, yticks=my_y_axis([df[!, col] for col in names]), yscale=:log10, legend=:topleft, size=(1200, 800)) end From a3e29574a3d9fa06a3ab28765f6e976132cebefc Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 20:25:48 -0400 Subject: [PATCH 09/17] add synchronize and multi thread to benchmark-surface-code-gpu.jl --- benchmark/benchmark-surface-code-gpu.jl | 26 +++++++++++++++++++++---- 1 file changed, 22 insertions(+), 4 deletions(-) diff --git a/benchmark/benchmark-surface-code-gpu.jl b/benchmark/benchmark-surface-code-gpu.jl index 107921bdb..73552b3e5 100644 --- a/benchmark/benchmark-surface-code-gpu.jl +++ b/benchmark/benchmark-surface-code-gpu.jl @@ -10,7 +10,25 @@ using CSV include("surface-code-circuit.jl") +function pftrajectories_threads(frames, ccircuit) + trajectories = size(frames.frame, 1) + nthr = min(Threads.nthreads(),trajectories÷(100)) + if nthr>1 + batchsize = trajectories÷nthr + Threads.@threads for i in 1:nthr + b = (i-1)*batchsize+1 + e = i==nthr ? trajectories : i*batchsize + pftrajectories((@view frames[b:e]), ccircuit) + end + else + pftrajectories(frames, ccircuit) + end + return frames +end + function get_stats() + println("Starting tests with $(Threads.nthreads()) threads out of `Sys.CPU_THREADS = $(Sys.CPU_THREADS)`...") + # Powers of 2 to benchmark powers = reverse(3:19) # start from the hardest one first! (fail fast) n_values = 2 .^ powers @@ -33,10 +51,10 @@ function get_stats() cpu_frames() = to_cpu(QuantumClifford._create_pauliframe(ccircuit; trajectories=n)) gpu_frames() = to_gpu(QuantumClifford._create_pauliframe(ccircuit; trajectories=n)) - cpu_row() = pftrajectories(fastrow(cpu_frames()), ccircuit) - cpu_column() = pftrajectories(fastcolumn(cpu_frames()), ccircuit) - gpu_row() = pftrajectories(fastrow(gpu_frames()), ccircuit) - gpu_column() = pftrajectories(fastcolumn(gpu_frames()), ccircuit) + cpu_row() = pftrajectories_threads(fastrow(cpu_frames()), ccircuit) + cpu_column() = pftrajectories_threads(fastcolumn(cpu_frames()), ccircuit) + gpu_row() = pftrajectories(fastrow(gpu_frames()), ccircuit), synchronize() + gpu_column() = pftrajectories(fastcolumn(gpu_frames()), ccircuit), synchronize() push!(cpu_row_times, @belapsed $cpu_row()) push!(cpu_column_times, @belapsed $cpu_column()) From 2605e6384e91ea1a092cab750a2a9a1cab1dc5da Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 20:52:47 -0400 Subject: [PATCH 10/17] cleanup adapters --- ext/QuantumCliffordGPUExt/adapters.jl | 29 ++++++++++++++++++++++----- 1 file changed, 24 insertions(+), 5 deletions(-) diff --git a/ext/QuantumCliffordGPUExt/adapters.jl b/ext/QuantumCliffordGPUExt/adapters.jl index 86d91685a..abe0a1991 100644 --- a/ext/QuantumCliffordGPUExt/adapters.jl +++ b/ext/QuantumCliffordGPUExt/adapters.jl @@ -1,19 +1,38 @@ const InnerGPUType = UInt32; const InnerCPUType = UInt64; -# todo. make the conversion types consiting with this... -# also define a cpu default type?! + +""" +converts data to gpu representation without changing the element types +""" +to_gpu(data); + + +""" +converts data to cpu representation without changing the element types +""" +to_cpu(data); + + +""" +converts data to gpu representation and reinterprets the element types +""" +to_gpu(data, tp::Type{T}) where {T <: Unsigned}; + + +""" +converts data to cpu representation and reinterprets the element types +""" +to_cpu(data) where {T <: Unsigned}; + to_gpu(array::AbstractArray) = CuArray(array) to_cpu(array::AbstractArray) = Array(array); -# changes the type to InnerGPUType or InnerCPUType as well as copying to cpu/gpu to_gpu(array::AbstractArray, tp::Type{T}) where {T <: Unsigned} = CuArray(reinterpret(T, collect(array))) to_cpu(array::AbstractArray, tp::Type{T}) where {T <: Unsigned} = Array(reinterpret(T, collect(array))) -# maybe change the format of storing the data in gpu array -# so that it is more convinient to work with them on gpu? # todo later add some type checking to avoid copying (or throw error) if the data is already on gpu/cpu to_gpu(tab::QuantumClifford.Tableau, tp::Type{T}=InnerGPUType) where {T <: Unsigned} = QuantumClifford.Tableau(to_gpu(tab.phases), tab.nqubits, to_gpu(tab.xzs, tp)) From f132bbf430cecb1902720b5815e883d0f421189c Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 20:57:25 -0400 Subject: [PATCH 11/17] cleanup types --- ext/QuantumCliffordGPUExt/types.jl | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/ext/QuantumCliffordGPUExt/types.jl b/ext/QuantumCliffordGPUExt/types.jl index b32241218..0b193a214 100644 --- a/ext/QuantumCliffordGPUExt/types.jl +++ b/ext/QuantumCliffordGPUExt/types.jl @@ -1,7 +1,8 @@ using LinearAlgebra: Adjoint -# todo is there anyway to do this automatically so that if the code in QuantumClifford changes, we don't have to change this?! -# especially with UInt8 types + +const PhaseInnerType = UInt8 +const MeasurementInnerType = Bool CUDAValue{T} = CuArray{T, 0, CUDA.Mem.DeviceBuffer} where {T} CUDAVector{T} = CuArray{T, 1, CUDA.Mem.DeviceBuffer} where {T} @@ -13,20 +14,19 @@ AdjCUDAVector{T} = CuArray{T, 1, CUDA.Mem.DeviceBuffer} where {T} # do not adjoi AdjCUDAMatrix{T} = Adjoint{T, CuArray{T, 2, CUDA.Mem.DeviceBuffer}} where {T} AdjCUDAParams = [AdjCUDAValue, AdjCUDAVector, AdjCUDAMatrix] -# what is CuDeviceArray? DeviceValue{T} = Union{CuDeviceArray{T, 0, 1}, Adjoint{T, CuDeviceArray{T, 0, 1}}} where {T} DeviceVector{T} = Union{CuDeviceArray{T, 1, 1}, Adjoint{T, CuDeviceArray{T, 1, 1}}} where {T} DeviceMatrix{T} = Union{CuDeviceArray{T, 2, 1}, Adjoint{T, CuDeviceArray{T, 2, 1}}} where {T} function getTableauGPU(GPUValue, GPUVector, GPUMatrix) - TableauGPU{T} = QuantumClifford.Tableau{Tzv, Tm} where {T <: Unsigned, Tzv <: GPUVector{UInt8}, Tm <: GPUMatrix{T}} + TableauGPU{T} = QuantumClifford.Tableau{Tzv, Tm} where {T <: Unsigned, Tzv <: GPUVector{PhaseInnerType}, Tm <: GPUMatrix{T}} end function getStabilizerGPU(GPUValue, GPUVector, GPUMatrix, GPUTableau) StabilizerGPU{T} = QuantumClifford.Stabilizer{<:GPUTableau{T}} where {T <: Unsigned} end function getPauliOperatorGPU(GPUValue, GPUVector, GPUMatrix, GPUTableau) - PauliOperatorGPU{T} = QuantumClifford.PauliOperator{Tz, Tv} where {T <: Unsigned, Tz<:GPUValue{UInt8}, Tv<:GPUVector{T}} + PauliOperatorGPU{T} = QuantumClifford.PauliOperator{Tz, Tv} where {T <: Unsigned, Tz<:GPUValue{PhaseInnerType}, Tv<:GPUVector{T}} end # todo. type definition here is stronger than the code in pauliframes.jl this will cause serious problems @@ -34,7 +34,7 @@ end # and we are assuming that TMeasurement is made of booleans function getPauliFrameGPU(GPUValue, GPUVector, GPUMatrix, GPUTableau) StabilizerGPU{T} = getStabilizerGPU(GPUValue, GPUVector, GPUMatrix, GPUTableau){T} where {T <: Unsigned} - PauliFrameGPU{T} = QuantumClifford.PauliFrame{TFrame, TMeasurement} where {T <: Unsigned, TFrame <: StabilizerGPU{T}, TMeasurement <: GPUMatrix{Bool}} + PauliFrameGPU{T} = QuantumClifford.PauliFrame{TFrame, TMeasurement} where {T <: Unsigned, TFrame <: StabilizerGPU{T}, TMeasurement <: GPUMatrix{MeasurementInnerType}} end const TableauCUDA{T} = getTableauGPU(CUDAParams...){T} where {T <: Unsigned} From 19ed7654e7ecbda4eb4a9133e1d3b5f9ef16cb0f Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 22:28:46 -0400 Subject: [PATCH 12/17] add documentation for to_gpu and to_cpu --- ext/QuantumCliffordGPUExt/adapters.jl | 25 +------ src/gpu_adapters.jl | 93 ++++++++++++++++++++++++++- 2 files changed, 92 insertions(+), 26 deletions(-) diff --git a/ext/QuantumCliffordGPUExt/adapters.jl b/ext/QuantumCliffordGPUExt/adapters.jl index abe0a1991..b1039dc72 100644 --- a/ext/QuantumCliffordGPUExt/adapters.jl +++ b/ext/QuantumCliffordGPUExt/adapters.jl @@ -1,32 +1,9 @@ const InnerGPUType = UInt32; const InnerCPUType = UInt64; -""" -converts data to gpu representation without changing the element types -""" -to_gpu(data); - - -""" -converts data to cpu representation without changing the element types -""" -to_cpu(data); - - -""" -converts data to gpu representation and reinterprets the element types -""" -to_gpu(data, tp::Type{T}) where {T <: Unsigned}; - - -""" -converts data to cpu representation and reinterprets the element types -""" -to_cpu(data) where {T <: Unsigned}; - to_gpu(array::AbstractArray) = CuArray(array) -to_cpu(array::AbstractArray) = Array(array); +to_cpu(array::AbstractArray) = Array(array) to_gpu(array::AbstractArray, tp::Type{T}) where {T <: Unsigned} = CuArray(reinterpret(T, collect(array))) diff --git a/src/gpu_adapters.jl b/src/gpu_adapters.jl index e6124497a..94b312d2a 100644 --- a/src/gpu_adapters.jl +++ b/src/gpu_adapters.jl @@ -1,9 +1,98 @@ """ -copies the memory content of the object to GPU +copies the memory content of the object to CPU + +You can only use this function if CUDA.jl is imported + +For more advanced users `to_cpu(data, element_type)` will reinterpret elements of data and converts them to `element_type`. +For example based on your CPU architecture, if working with matrices of UInt32 is faster than UInt64, you can use `to_cpu(data, UInt32)` + + + + +```jldoctest +julia> using QuantumClifford: to_cpu, to_gpu + +julia> using CUDA # without this import, to_cpu, to_gpu are just function + +julia> stab = random_stabilizer(3) +- X_Z ++ _ZZ ++ __Z + +julia> stab_gpu = to_gpu(stab); + +julia> apply!(stab_gpu, sHadamard(1)); + +julia> stab_result_cpu = to_cpu(stab_gpu) +- Z_Z ++ _ZZ ++ __Z +``` + +```jldoctest +julia> using QuantumClifford: to_cpu, to_gpu + +julia> using CUDA # without this import, to_cpu, to_gpu are just function + +julia> pf_gpu = to_gpu(PauliFrame(1000, 2, 2)); +julia> circuit = [sMZ(1, 1), sHadamard(2), sMZ(2, 2)]; +julia> pftrajectories(pf_gpu, circuit); +julia> measurements = to_cpu(pf_gpu.measurements); +julia> sum(measurements, dims=1) +1×2 Matrix{Int64}: + 0 492 +``` + +See also: [`to_gpu`](@ref) """ function to_cpu end + """ -copies the memory content of the object to CPU +copies the memory content of the object to GPU + +You can only use this function if CUDA.jl is imported + +For more advanced users `to_gpu(data, element_type)` will reinterpret elements of data and converts them to `element_type`. +For example based on your GPU architecture, if working with matrices of UInt64 is faster than UInt32, you can use `to_gpu(data, UInt64)` + + + + +```jldoctest +julia> using QuantumClifford: to_cpu, to_gpu + +julia> using CUDA # without this import, to_cpu, to_gpu are just function + +julia> stab = random_stabilizer(3) +- X_Z ++ _ZZ ++ __Z + +julia> stab_gpu = to_gpu(stab); + +julia> apply!(stab_gpu, sHadamard(1)); + +julia> stab_result_cpu = to_cpu(stab_gpu) +- Z_Z ++ _ZZ ++ __Z +``` + +```jldoctest +julia> using QuantumClifford: to_cpu, to_gpu + +julia> using CUDA # without this import, to_cpu, to_gpu are just function + +julia> pf_gpu = to_gpu(PauliFrame(1000, 2, 2)); +julia> circuit = [sMZ(1, 1), sHadamard(2), sMZ(2, 2)]; +julia> pftrajectories(pf_gpu, circuit); +julia> measurements = to_cpu(pf_gpu.measurements); +julia> sum(measurements, dims=1) +1×2 Matrix{Int64}: + 0 492 +``` + +See also: [`to_cpu`](@ref) """ function to_gpu end From 0c0fef4a36b7e4e563e15893f345f1e0d11cffac Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 23:18:54 -0400 Subject: [PATCH 13/17] hotfix documentation --- src/gpu_adapters.jl | 10 ++-------- 1 file changed, 2 insertions(+), 8 deletions(-) diff --git a/src/gpu_adapters.jl b/src/gpu_adapters.jl index 94b312d2a..766b8c99b 100644 --- a/src/gpu_adapters.jl +++ b/src/gpu_adapters.jl @@ -14,7 +14,7 @@ julia> using QuantumClifford: to_cpu, to_gpu julia> using CUDA # without this import, to_cpu, to_gpu are just function -julia> stab = random_stabilizer(3) +julia> stab = S"- X_Z\\n+ _ZZ\\n+ __Z" - X_Z + _ZZ + __Z @@ -38,9 +38,6 @@ julia> pf_gpu = to_gpu(PauliFrame(1000, 2, 2)); julia> circuit = [sMZ(1, 1), sHadamard(2), sMZ(2, 2)]; julia> pftrajectories(pf_gpu, circuit); julia> measurements = to_cpu(pf_gpu.measurements); -julia> sum(measurements, dims=1) -1×2 Matrix{Int64}: - 0 492 ``` See also: [`to_gpu`](@ref) @@ -64,7 +61,7 @@ julia> using QuantumClifford: to_cpu, to_gpu julia> using CUDA # without this import, to_cpu, to_gpu are just function -julia> stab = random_stabilizer(3) +julia> stab = S"- X_Z\\n+ _ZZ\\n+ __Z" - X_Z + _ZZ + __Z @@ -88,9 +85,6 @@ julia> pf_gpu = to_gpu(PauliFrame(1000, 2, 2)); julia> circuit = [sMZ(1, 1), sHadamard(2), sMZ(2, 2)]; julia> pftrajectories(pf_gpu, circuit); julia> measurements = to_cpu(pf_gpu.measurements); -julia> sum(measurements, dims=1) -1×2 Matrix{Int64}: - 0 492 ``` See also: [`to_cpu`](@ref) From 7bd6482d603a43066e74eb4af1a401acf4364cc4 Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 23:19:46 -0400 Subject: [PATCH 14/17] make type of all rows Int instead of UInt --- ext/QuantumCliffordGPUExt/apply.jl | 12 ++++++------ ext/QuantumCliffordGPUExt/apply_noise.jl | 16 +++++++++++----- 2 files changed, 17 insertions(+), 11 deletions(-) diff --git a/ext/QuantumCliffordGPUExt/apply.jl b/ext/QuantumCliffordGPUExt/apply.jl index 4b6a92ed2..3309a9ccd 100644 --- a/ext/QuantumCliffordGPUExt/apply.jl +++ b/ext/QuantumCliffordGPUExt/apply.jl @@ -3,7 +3,7 @@ using QuantumClifford: getxbit, getzbit, setxbit, setzbit function single_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, phases::DeviceVector{Tmz}, op::SingleQubitOperator, - rows::Unsigned, + rows::Int, compute_phases::Bool) where {Tme <: Unsigned, Tmz <: Unsigned} idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x if idx > rows @@ -41,7 +41,7 @@ end function abstract_single_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, phases::DeviceVector{Tmz}, gate::QuantumClifford.AbstractSingleQubitOperator, - rows::Unsigned, + rows::Int, compute_phases::Bool) where {Tme <: Unsigned, Tmz <: Unsigned} idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x if idx > rows @@ -63,7 +63,7 @@ function _apply!(stab::StabilizerGPU{T}, op::QuantumClifford.SingleQubitOperator; phases::Val{B}=Val(true)) where {B, T <: Unsigned} # todo how to use phases similar to before in kernel functions??! - rows::Unsigned = size(stab, 1) + rows = size(stab, 1) tab = QuantumClifford.tab(stab) # todo. why can't I pass phases=compute_phases normally without function call? (@run_cuda single_qubit_gpu_kernel(tab.xzs, tab.phases, op, rows, B) rows) @@ -74,7 +74,7 @@ function _apply!(stab::StabilizerGPU{T}, op::QuantumClifford.AbstractSingleQubitOperator; phases::Val{B}=Val(true)) where {B, T <: Unsigned} - rows::Unsigned = size(stab, 1) + rows = size(stab, 1) tab = QuantumClifford.tab(stab) # todo. why can't I pass phases=compute_phases normally without function call? (@run_cuda abstract_single_qubit_gpu_kernel(tab.xzs, tab.phases, op, rows, B) rows) @@ -84,7 +84,7 @@ end function two_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, phases::DeviceVector{Tze}, gate::QuantumClifford.AbstractTwoQubitOperator, # todo. change to two qubit operator instead os abstract version - rows::Unsigned, + rows::Int, compute_phases::Bool=true) where {Tme <: Unsigned, Tze <: Unsigned} idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x if idx > rows @@ -116,7 +116,7 @@ end function _apply!(stab::StabilizerGPU{T}, gate::G; phases::Val{B}=Val(true)) where {B, G<:QuantumClifford.AbstractTwoQubitOperator, T <: Unsigned} # todo. change to two qubit operator instead os abstract version - rows::Unsigned = size(stab, 1) + rows = size(stab, 1) tab = QuantumClifford.tab(stab) # todo. why can't I pass compute_phases=compute_phases normally without function call? (@run_cuda two_qubit_gpu_kernel(tab.xzs, tab.phases, gate, rows, B) rows) diff --git a/ext/QuantumCliffordGPUExt/apply_noise.jl b/ext/QuantumCliffordGPUExt/apply_noise.jl index 0bb7386e6..966600498 100644 --- a/ext/QuantumCliffordGPUExt/apply_noise.jl +++ b/ext/QuantumCliffordGPUExt/apply_noise.jl @@ -1,5 +1,11 @@ using QuantumClifford: _div, _mod +""" +according to this: + https://github.com/JuliaGPU/CUDA.jl/blob/ac1bc29a118e7be56d9edb084a4dea4224c1d707/test/core/device/random.jl#L33 +CUDA.jl supports calling rand() inside kernel +""" + function applynoise!(frame::PauliFrameGPU{T},noise::UnbiasedUncorrelatedNoise,i::Int) where {T <: Unsigned} p = noise.errprobthird lowbit = T(1) @@ -9,7 +15,7 @@ function applynoise!(frame::PauliFrameGPU{T},noise::UnbiasedUncorrelatedNoise,i: stab = frame.frame xzs = tab(stab).xzs - rows::Unsigned = size(stab, 1) + rows = size(stab, 1) @run_cuda applynoise_kernel(xzs, p, ibig, ismallm, rows) rows return frame @@ -18,16 +24,16 @@ end function applynoise_kernel(xzs::DeviceMatrix{Tme}, p::Real, - ibig::Int, # todo why is this Int and others Tme? - ismallm::Tme, # why is rows Unsigned sometimes and sometimes Int? - rows::Unsigned) where {Tme <: Unsigned} + ibig::Int, + ismallm::Tme, + rows::Int) where {Tme <: Unsigned} f = (blockIdx().x - 1) * blockDim().x + threadIdx().x; if f > rows return nothing end - r = rand() # todo add type to it? is it uniform? + r = rand() if r < p # X error xzs[ibig,f] ⊻= ismallm elseif r < 2p # Z error From e1eff4ea4e4adabf53b089b3edf3f7bdc72afc81 Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 23:53:17 -0400 Subject: [PATCH 15/17] cleanup unnecassary comments --- .../QuantumCliffordGPUExt.jl | 1 - ext/QuantumCliffordGPUExt/apply.jl | 64 +++++++------ ext/QuantumCliffordGPUExt/fastmemlayout.jl | 9 +- ext/QuantumCliffordGPUExt/pauli_frames.jl | 91 ++----------------- ext/QuantumCliffordGPUExt/utils.jl | 1 - test/runtests.jl | 1 + 6 files changed, 55 insertions(+), 112 deletions(-) diff --git a/ext/QuantumCliffordGPUExt/QuantumCliffordGPUExt.jl b/ext/QuantumCliffordGPUExt/QuantumCliffordGPUExt.jl index fd564ed2c..484b2f452 100644 --- a/ext/QuantumCliffordGPUExt/QuantumCliffordGPUExt.jl +++ b/ext/QuantumCliffordGPUExt/QuantumCliffordGPUExt.jl @@ -12,5 +12,4 @@ include("pauli_frames.jl") include("fastmemlayout.jl") include("apply_noise.jl") -# todo hide _apply function later. only for internal use end diff --git a/ext/QuantumCliffordGPUExt/apply.jl b/ext/QuantumCliffordGPUExt/apply.jl index 3309a9ccd..b817262ee 100644 --- a/ext/QuantumCliffordGPUExt/apply.jl +++ b/ext/QuantumCliffordGPUExt/apply.jl @@ -1,5 +1,9 @@ using QuantumClifford: getxbit, getzbit, setxbit, setzbit +############################## +# SingleQubitOperator Kernel +############################## + function single_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, phases::DeviceVector{Tmz}, op::SingleQubitOperator, @@ -12,10 +16,9 @@ function single_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, c = op.q r = idx sh = QuantumClifford.getshift(Tme, c) - xx,zx,xz,zz = Tme.((op.xx,op.zx,op.xz,op.zz)) .<< sh # maybe do this in parent class? + xx,zx,xz,zz = Tme.((op.xx,op.zx,op.xz,op.zz)) .<< sh # maybe putting this in parent function call will improve speed? anticom = ~iszero((~zz & xz & ~xx & zx) | ( zz & ~xz & xx & zx) | (zz & xz & xx & ~zx)) - # todo. in future each gpu core can be responsible for multiple rows x = getxbit(xzs, r, c) z = getzbit(xzs, r, c) setxbit(xzs, r, c, (x&xx)⊻(z&zx)) @@ -38,6 +41,10 @@ function single_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, return nothing end +############################## +# AbstractSingleQubitOperator Kernel +############################## + function abstract_single_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, phases::DeviceVector{Tmz}, gate::QuantumClifford.AbstractSingleQubitOperator, @@ -59,31 +66,13 @@ function abstract_single_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, return nothing end -function _apply!(stab::StabilizerGPU{T}, - op::QuantumClifford.SingleQubitOperator; - phases::Val{B}=Val(true)) where {B, T <: Unsigned} - # todo how to use phases similar to before in kernel functions??! - rows = size(stab, 1) - tab = QuantumClifford.tab(stab) - # todo. why can't I pass phases=compute_phases normally without function call? - (@run_cuda single_qubit_gpu_kernel(tab.xzs, tab.phases, op, rows, B) rows) - return stab -end - -function _apply!(stab::StabilizerGPU{T}, - op::QuantumClifford.AbstractSingleQubitOperator; - phases::Val{B}=Val(true)) where {B, T <: Unsigned} - - rows = size(stab, 1) - tab = QuantumClifford.tab(stab) - # todo. why can't I pass phases=compute_phases normally without function call? - (@run_cuda abstract_single_qubit_gpu_kernel(tab.xzs, tab.phases, op, rows, B) rows) - return stab -end +############################## +# AbstractTwoQubitOperator Kernel +############################## function two_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, phases::DeviceVector{Tze}, - gate::QuantumClifford.AbstractTwoQubitOperator, # todo. change to two qubit operator instead os abstract version + gate::QuantumClifford.AbstractTwoQubitOperator, rows::Int, compute_phases::Bool=true) where {Tme <: Unsigned, Tze <: Unsigned} idx = (blockIdx().x - 1) * blockDim().x + threadIdx().x @@ -112,13 +101,36 @@ function two_qubit_gpu_kernel(xzs::DeviceMatrix{Tme}, return nothing end +############################## +# Wrapper _apply! functions +############################## + +function _apply!(stab::StabilizerGPU{T}, + op::QuantumClifford.SingleQubitOperator; + + phases::Val{B}=Val(true)) where {B, T <: Unsigned} + rows = size(stab, 1) + tab = QuantumClifford.tab(stab) + (@run_cuda single_qubit_gpu_kernel(tab.xzs, tab.phases, op, rows, B) rows) + return stab +end + +function _apply!(stab::StabilizerGPU{T}, + op::QuantumClifford.AbstractSingleQubitOperator; + phases::Val{B}=Val(true)) where {B, T <: Unsigned} + + rows = size(stab, 1) + tab = QuantumClifford.tab(stab) + (@run_cuda abstract_single_qubit_gpu_kernel(tab.xzs, tab.phases, op, rows, B) rows) + return stab +end function _apply!(stab::StabilizerGPU{T}, gate::G; - phases::Val{B}=Val(true)) where {B, G<:QuantumClifford.AbstractTwoQubitOperator, T <: Unsigned} # todo. change to two qubit operator instead os abstract version + phases::Val{B}=Val(true)) where {B, G<:QuantumClifford.AbstractTwoQubitOperator, T <: Unsigned} + rows = size(stab, 1) tab = QuantumClifford.tab(stab) - # todo. why can't I pass compute_phases=compute_phases normally without function call? (@run_cuda two_qubit_gpu_kernel(tab.xzs, tab.phases, gate, rows, B) rows) return stab end diff --git a/ext/QuantumCliffordGPUExt/fastmemlayout.jl b/ext/QuantumCliffordGPUExt/fastmemlayout.jl index 0961bab04..f5706b641 100644 --- a/ext/QuantumCliffordGPUExt/fastmemlayout.jl +++ b/ext/QuantumCliffordGPUExt/fastmemlayout.jl @@ -1,7 +1,14 @@ using LinearAlgebra: Adjoint using QuantumClifford: Tableau -# when we use to_gpu, to_cpu the efffect of fastrow, fastcolumn disappears +""" +TableauCUDA is the type of Tableau with its data stored in CUDA arrays +TableauAdj is the type of Tableau with its data stored in an adjoint of a CUDA arrays + +rest of the fastrow, fastcolumn functions are implemented in QuantumClifford.jl +""" + +# todo when we use to_gpu, to_cpu the efffect of fastrow, fastcolumn disappears fastrow(t::TableauCUDA) = t fastrow(t::TableauAdj) = Tableau(t.phases, t.nqubits, CuArray(t.xzs)) fastcolumn(t::TableauCUDA) = Tableau(t.phases, t.nqubits, CuArray(t.xzs')') diff --git a/ext/QuantumCliffordGPUExt/pauli_frames.jl b/ext/QuantumCliffordGPUExt/pauli_frames.jl index 4fd9911c4..574d2e70c 100644 --- a/ext/QuantumCliffordGPUExt/pauli_frames.jl +++ b/ext/QuantumCliffordGPUExt/pauli_frames.jl @@ -1,7 +1,6 @@ -function apply!(f::PauliFrameGPU{T}, op::QuantumClifford.AbstractCliffordOperator) where {T <: Unsigned} - _apply!(f.frame, op; phases=Val(false)) - return f -end +############################## +# sMZ +############################## function apply_sMZ_kernel!(xzs::DeviceMatrix{Tme}, measurements::DeviceMatrix{Bool}, @@ -18,7 +17,7 @@ function apply_sMZ_kernel!(xzs::DeviceMatrix{Tme}, return nothing end -function apply!(frame::PauliFrameGPU{T}, op::QuantumClifford.sMZ) where {T <: Unsigned} # TODO sMX, sMY +function apply!(frame::PauliFrameGPU{T}, op::QuantumClifford.sMZ) where {T <: Unsigned} op.bit == 0 && return frame i = op.qubit xzs = frame.frame.tab.xzs @@ -30,6 +29,10 @@ function apply!(frame::PauliFrameGPU{T}, op::QuantumClifford.sMZ) where {T <: Un return frame end +############################## +# sMRZ +############################## + function apply_sMRZ_kernel!(xzs::DeviceMatrix{Tme}, measurements::DeviceMatrix{Bool}, op::QuantumClifford.sMRZ, @@ -59,81 +62,3 @@ function apply!(frame::PauliFrameGPU{T}, op::QuantumClifford.sMRZ) where {T <: U (@run_cuda apply_sMRZ_kernel!(xzs, frame.measurements, op, ibig, ismallm, length(frame)) length(frame)) return frame end - - - -################################################################################## - -# function partition_circuit(::Type{T}, circ) where {T <: Unsigned} -# # time complexity: O(gates * qubits/64) for UInt64 - -# circ = if eltype(circ) <: QuantumClifford.CompactifiedGate -# circ -# else -# compactify_circuit(circ) -# end - -# qmax = maximum((maximum(affectedqubits(g)) for g in circ)) -# columns_cnt = QuantumClifford._div(T, qmax) + 1 - -# partitions = [] -# partition_idx = [] -# last_column_occupier = [0 for _ in 1:columns_cnt] # last_column_occupier[i] = group id of the last gate that occupies indice i - -# for g in circ -# column_indices = [QuantumClifford.getbigindex(T, qbit) for qbit in affectedqubits(g)] -# my_partition_idx = maximum(last_column_occupier[column_indices]) + 1 -# push!(partition_idx, my_partition_idx) -# if my_partition_idx > length(partitions) -# push!(partitions, [g]) -# else -# push!(partitions[my_partition_idx], g) -# end -# last_column_occupier[column_indices] .= my_partition_idx -# end -# partitions -# end - -# function partition_circuit(circ) -# # time complexity: O(gates * qubits/64) for UInt64 - -# circ = if eltype(circ) <: QuantumClifford.CompactifiedGate -# circ -# else -# compactify_circuit(circ) -# end - -# qmax = maximum((maximum(affectedqubits(g)) for g in circ)) - -# partitions = [] -# partition_idx = [] -# last_column_occupier = [0 for _ in 1:qmax] # last_column_occupier[i] = group id of the last gate that occupies indice i - -# for g in circ -# indices = [x for x in affectedqubits(g)] -# my_partition_idx = maximum(last_column_occupier[indices]) + 1 -# push!(partition_idx, my_partition_idx) -# if my_partition_idx > length(partitions) -# push!(partitions, [g]) -# else -# push!(partitions[my_partition_idx], g) -# end -# last_column_occupier[indices] .= my_partition_idx -# end -# partitions -# end - -# function pftrajectories(state::PauliFrameGPU{T}, circuit) where {T <: Unsigned} -# for gates in partition_circuit(circuit) -# # for gate in gates -# # CUDA.@sync apply!(state, gate) -# # end - -# @sync begin -# for gate in gates -# @async apply!(state, gate) -# end -# end -# end -# return state -# end diff --git a/ext/QuantumCliffordGPUExt/utils.jl b/ext/QuantumCliffordGPUExt/utils.jl index 8367d7463..cbfed8408 100644 --- a/ext/QuantumCliffordGPUExt/utils.jl +++ b/ext/QuantumCliffordGPUExt/utils.jl @@ -9,7 +9,6 @@ macro run_cuda(call, ndrange) local config = CUDA.launch_configuration(kernel.fun) local threads = min($(esc(ndrange)), config.threads) local blocks = cld($(esc(ndrange)), threads) - # @show threads blocks kernel($(args...); threads=threads, blocks=blocks) end end diff --git a/test/runtests.jl b/test/runtests.jl index 3b7b5b4b2..0d6e40193 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -28,6 +28,7 @@ end println("Starting tests with $(Threads.nthreads()) threads out of `Sys.CPU_THREADS = $(Sys.CPU_THREADS)`...") +# in order to run the gpu tests automatically set GPU_TESTS to true in the .env file if ENV["GPU_TESTS"] == "true" @doset "gpu" else From 379381b801c890dd37d3a32faafed3357c620444 Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 26 Aug 2023 23:54:48 -0400 Subject: [PATCH 16/17] use julia-repl instead of jldoctest --- src/gpu_adapters.jl | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/gpu_adapters.jl b/src/gpu_adapters.jl index 766b8c99b..dfe50ec2d 100644 --- a/src/gpu_adapters.jl +++ b/src/gpu_adapters.jl @@ -9,7 +9,7 @@ For example based on your CPU architecture, if working with matrices of UInt32 i -```jldoctest +```julia-repl julia> using QuantumClifford: to_cpu, to_gpu julia> using CUDA # without this import, to_cpu, to_gpu are just function @@ -29,7 +29,7 @@ julia> stab_result_cpu = to_cpu(stab_gpu) + __Z ``` -```jldoctest +```julia-repl julia> using QuantumClifford: to_cpu, to_gpu julia> using CUDA # without this import, to_cpu, to_gpu are just function @@ -56,7 +56,7 @@ For example based on your GPU architecture, if working with matrices of UInt64 i -```jldoctest +```julia-repl julia> using QuantumClifford: to_cpu, to_gpu julia> using CUDA # without this import, to_cpu, to_gpu are just function @@ -76,7 +76,7 @@ julia> stab_result_cpu = to_cpu(stab_gpu) + __Z ``` -```jldoctest +```julia-repl julia> using QuantumClifford: to_cpu, to_gpu julia> using CUDA # without this import, to_cpu, to_gpu are just function From 90689295c869618f2e7a9ffeebdced4b8e258277 Mon Sep 17 00:00:00 2001 From: Shayan-P Date: Sat, 2 Sep 2023 20:46:39 -0400 Subject: [PATCH 17/17] 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