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BUG with `put` function.
MWE:
julia> using CuYao
julia> c1 = put(10, (7,8,9)=>chain(3, chain(3, chain(3, chain(3, put(3, 1=>Ry(pi)), put(3, 2=>Ry(pi)))))))
nqubits: 10
put on (7, 8, 9)
└─ chain
└─ chain
└─ chain
└─ chain
├─ put on (1)
│ └─ rot(Y gate, 3.141592653589793)
└─ put on (2)
└─ rot(Y gate, 3.141592653589793)
julia> rand_state(10, nbatch = 1000) |> cu |> c1
ArrayReg{1000, Complex{Float64}, CuArray...}
active qubits: 10/10
julia> c2 = put(11, (7,8,9,10)=>chain(4, chain(4, chain(4, chain(4, put(4, 1=>Ry(pi)), put(4, 2=>Ry(pi)))))))
nqubits: 11
put on (7, 8, 9, 10)
└─ chain
└─ chain
└─ chain
└─ chain
├─ put on (1)
│ └─ rot(Y gate, 3.141592653589793)
└─ put on (2)
└─ rot(Y gate, 3.141592653589793)
julia> rand_state(11, nbatch = 1000) |> cu |> c2
ERROR: CUDA error: device kernel image is invalid (code #200, ERROR_INVALID_IMAGE)
julia> c3 = put(11, (7,8,9)=>chain(3, chain(3, chain(3, chain(3, put(3, 1=>Ry(pi)), put(3, 2=>Ry(pi)))))))
nqubits: 11
put on (7, 8, 9)
└─ chain
└─ chain
└─ chain
└─ chain
├─ put on (1)
│ └─ rot(Y gate, 3.141592653589793)
└─ put on (2)
└─ rot(Y gate, 3.141592653589793)
julia> rand_state(11, nbatch = 1000) |> cu |> c3
ArrayReg{1000, Complex{Float64}, CuArray...}
active qubits: 11/11
register
Not registered in the new registry?
supports cu(hamiltonian)
current it seems the cu(state) is ok, but when we want to utilize expect(hamiltonian, cu(reg))
seems the hamilitonian is not supported by the current cu function.
can we add this function to fully use the gpu power for some case, that we need expectation value?
Many thanks,
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Use GPUfy loops to avoid type piracy and compatibility issue
Line 28 in 6273725
Implement in-place kron and batched_kron
Wouldn't it be enough define
function kron!(C::CuArray{T3}, A::Union{CuArray{T1}, Adjoint{<:Any, <:CuArray{T1}}}, B::Union{CuArray{T2}, Adjoint{<:Any, <:CuArray{T2}}}) where {T1, T2, T3} by reusing the out-of-place version
Lines 76 to 91 in ba08a02
but replace res with C and adding some bounds checks etc.?
Would the samee apply to batched_kron!?
convert to package extension in Yao
#84 reminds me of this. It will make release much easier if we just ship as a package extension of CUDA. So there is no need to wait for a release of Yao and then tag CuYao. And I think this is now the recommended way of supporting CUDA acceleration in 1.9+.
update CI on gitlab
CI seems disconnected
Error tagging new release
The tag name "v0.1" is not of the appropriate SemVer form (vX.Y.Z).
cc: @GiggleLiu
update this package against latest YaoBase and YaoArrayRegister updates
Just in case we forget.
[Discussion] CuArrays in Julia1.5 is faster! But why?
Julia 1.4.1
julia> using CuYao
(@v1.4) pkg> st CuYao
Status `~/.julia/environments/v1.4/Project.toml`
[b48ca7a8] CuYao v0.2.2 [`~/.julia/dev/CuYao`]
julia> using CuArrays
julia> using BenchmarkTools
julia> reg = rand_state(25) |> cu
ArrayReg{1, Complex{Float64}, CuArray...}
active qubits: 25/25
(@v1.4) pkg> st CuArrays
Status `~/.julia/environments/v1.4/Project.toml`
[3a865a2d] CuArrays v2.2.0
julia> @benchmark @CuArrays.sync $reg |> $(put(25, 5=>X))
BenchmarkTools.Trial:
memory estimate: 3.31 KiB
allocs estimate: 95
--------------
minimum time: 3.137 ms (0.00% GC)
median time: 3.298 ms (0.00% GC)
mean time: 3.295 ms (0.00% GC)
maximum time: 3.439 ms (0.00% GC)
--------------
samples: 1507
evals/sample: 1
julia> @benchmark @CuArrays.sync $reg |> $(cnot(25, 3, 9))
BenchmarkTools.Trial:
memory estimate: 3.81 KiB
allocs estimate: 107
--------------
minimum time: 1.809 ms (0.00% GC)
median time: 1.996 ms (0.00% GC)
mean time: 2.021 ms (0.00% GC)
maximum time: 2.305 ms (0.00% GC)
--------------
samples: 2466
evals/sample: 1
julia> @benchmark @CuArrays.sync $reg |> $(put(25, 5=>Rx(0.5)))
BenchmarkTools.Trial:
memory estimate: 11.34 KiB
allocs estimate: 181
--------------
minimum time: 3.175 ms (0.00% GC)
median time: 3.409 ms (0.00% GC)
mean time: 3.408 ms (0.00% GC)
maximum time: 3.712 ms (0.00% GC)
--------------
samples: 1456
evals/sample: 1Julia1.5-beta
julia> using CuYao
julia> reg = rand_state(25) |> cu
ArrayReg{1, Complex{Float64}, CuArray...}
active qubits: 25/25
julia> @benchmark @CuArrays.sync $reg |> $(put(25, 5=>X))
ERROR: LoadError: UndefVarError: @benchmark not defined
in expression starting at REPL[3]:1
julia> using BenchmarkTools
u[ Info: Precompiling BenchmarkTools [6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf]
sing C
julia> using CuArrays
julia> using BenchmarkTools
julia> @benchmark @CuArrays.sync $reg |> $(put(25, 5=>X))
BenchmarkTools.Trial:
memory estimate: 3.61 KiB
allocs estimate: 88
--------------
minimum time: 1.916 ms (0.00% GC)
median time: 2.122 ms (0.00% GC)
mean time: 2.114 ms (0.00% GC)
maximum time: 7.800 ms (0.00% GC)
--------------
samples: 2362
evals/sample: 1
(@v1.5) pkg> st CuYao
Status `~/.julia/environments/v1.5/Project.toml`
[b48ca7a8] CuYao v0.2.2 `~/.julia/dev/CuYao`
(@v1.5) pkg> st CuArrays
Status `~/.julia/environments/v1.5/Project.toml`
[3a865a2d] CuArrays v2.2.0
julia> @benchmark @CuArrays.sync $reg |> $(cnot(25, 3, 9))
BenchmarkTools.Trial:
memory estimate: 4.13 KiB
allocs estimate: 100
--------------
minimum time: 1.054 ms (0.00% GC)
median time: 1.091 ms (0.00% GC)
mean time: 1.109 ms (0.00% GC)
maximum time: 9.261 ms (0.00% GC)
--------------
samples: 4504
evals/sample: 1
julia> @benchmark @CuArrays.sync $reg |> $(put(25, 5=>Rx(0.5)))
BenchmarkTools.Trial:
memory estimate: 11.35 KiB
allocs estimate: 169
--------------
minimum time: 2.000 ms (0.00% GC)
median time: 2.200 ms (0.00% GC)
mean time: 2.195 ms (0.00% GC)
maximum time: 7.010 ms (0.00% GC)
--------------
samples: 2275
evals/sample: 1Calculating gradients with cureg
Not sure if it should an enhancement or fix, but I noticed that quantum backpropagation does not work with a GPU register (reg |> cu). It raises "scalar getindex is disallowed" warning. Is there a workaround? GPU operation for expect'(..) can speed up calculations by a lot.
Apply! on cuzero_state register throws "clocs not defined error" in instruct! call.
A (seemingly) simple setup of trying to run apply!() on a cuzero_state(4) register:
proxy_reg = zero_state(4) |> CuYao.cu
apply!(proxy_reg, pqc_circuit)This, however, throws an error:
UndefVarError: clocs not defined
Stacktrace:
[1] instruct!(#unused#::Val{2}, state::CuArray{ComplexF64, 1, CUDA.Mem.DeviceBuffer}, U1::SparseArrays.SparseMatrixCSC{ComplexF64, Int64}, locs::Tuple{Int64})
@ CuYao C:\Users\trothe.julia\packages\CuYao\P3wMR\src\gpuapplys.jl:49
And indeed the referenced source in CuYao declares:
function instruct!(::Val{2}, state::DenseCuVecOrMat, U1::SDSparseMatrixCSC, locs::Tuple{Int})
instruct!(Val(2), state, Matrix(U1), locs, clocs, cval)
endWhich obviously can't work. Anyone knows why this piece is in the source in this way? And what makes my case special in that I couldn't find a similar issue in the issue trace? This seems as something that happens even for the most simple YaoBlocks and registers. The non-cuda version in Yao works just fine.
If that helps, the pqc_circuit mentioned above is the following:
pqc_circuit = nqubits: 4
chain
├─ Subroutine: (1, 2, 3, 4)
│ └─ kron
│ ├─ 1=>rot(Z, -1.0300292665315807)
│ ├─ 2=>rot(Z, -0.5556806707931512)
│ ├─ 3=>rot(Z, -1.6820465862121425)
│ └─ 4=>rot(Z, -1.6440950194679396)
├─ Subroutine: (1, 2, 3, 4)
│ └─ kron
│ ├─ 1=>rot(Y, 0.3001850517270027)
│ ├─ 2=>rot(Y, 0.41386690250976577)
│ ├─ 3=>rot(Y, -0.6562405862159898)
│ └─ 4=>rot(Y, 0.6502920336992778)
├─ control(1)
│ └─ (2,) X
├─ control(3)
│ └─ (4,) X
├─ Subroutine: (1, 2, 3, 4)
│ └─ kron
│ ├─ 1=>rot(Z, 2.4875529584638456)
│ ├─ 2=>rot(Z, 1.9337138528264264)
│ ├─ 3=>rot(Z, -1.3241302236114942)
│ └─ 4=>rot(Z, -0.6202813142456156)
├─ Subroutine: (1, 2, 3, 4)
│ └─ kron
│ ├─ 1=>rot(Y, 0.017415280987295396)
│ ├─ 2=>rot(Y, -0.8955835562683527)
│ ├─ 3=>rot(Y, 0.2029372375119746)
│ └─ 4=>rot(Y, -0.23288875605647713)
├─ control(2)
│ └─ (3,) X
├─ Subroutine: (1, 2, 3, 4)
│ └─ kron
│ ├─ 1=>rot(Z, -0.47153618078694515)
│ ├─ 2=>rot(Z, -1.2530556792651808)
│ ├─ 3=>rot(Z, 0.07989281174479339)
│ └─ 4=>rot(Z, -0.3709523749972201)
├─ Subroutine: (1, 2, 3, 4)
│ └─ kron
│ ├─ 1=>rot(Y, -0.8946015745750833)
│ ├─ 2=>rot(Y, 2.025043826440464)
│ ├─ 3=>rot(Y, 1.3762548604704439)
│ └─ 4=>rot(Y, 0.10249825960394013)
├─ control(1)
│ └─ (2,) X
├─ control(3)
│ └─ (4,) X
├─ Subroutine: (1, 2, 3, 4)
│ └─ kron
│ ├─ 1=>rot(Z, 1.9134004355076004)
│ ├─ 2=>rot(Z, 3.0154690647788396)
│ ├─ 3=>rot(Z, 0.15234390317820548)
│ └─ 4=>rot(Z, -1.4601520334711449)
├─ Subroutine: (1, 2, 3, 4)
│ └─ kron
│ ├─ 1=>rot(Y, -0.24473432855217372)
│ ├─ 2=>rot(Y, 2.6328232746477367)
│ ├─ 3=>rot(Y, 0.5156461987188995)
│ └─ 4=>rot(Y, -0.24391982101446646)
└─ control(2)
└─ (3,) X
I'm using latest CuYao v0.3.3 and other CUDA.jl related things are running fine. Julia v1.9.0 on Windows 11, CUDA v11.8.0.
Incorrect promotion rule
Line 80 in ac4d158
Should use LinearAlgebra.promote_op for consistency with Base
Merge kernels
Now the launch overhead is more than 99%
➜ modules git:(GPUdemo) ✗ nvprof julia QCBMS.jl
==22279== NVPROF is profiling process 22279, command: julia QCBMS.jl
==22279== Profiling application: julia QCBMS.jl
==22279== Profiling result:
Type Time(%) Time Calls Avg Min Max Name
GPU activities: 70.36% 77.0104s 810000 95.074us 74.113us 279.72us ptxcall_simple_kernel_2
28.96% 31.6927s 720000 44.017us 32.896us 113.19us ptxcall_simple_kernel_3
0.68% 748.96ms 10000 74.895us 72.801us 79.361us ptxcall_anonymous23_1
0.00% 1.1371ms 4 284.27us 1.7600us 1.0389ms [CUDA memcpy HtoD]
API calls: 99.11% 90.5692s 1540000 58.811us 6.5610us 9.6723ms cuLaunchKernel
0.43% 389.37ms 1540034 252ns 145ns 649.65us cuCtxGetCurrent
0.23% 210.94ms 1 210.94ms 210.94ms 210.94ms cuCtxCreate
0.14% 129.13ms 1 129.13ms 129.13ms 129.13ms cuCtxDestroy
0.07% 65.987ms 3 21.996ms 47.171us 65.891ms cuModuleUnload
0.01% 13.700ms 27 507.41us 439.26us 724.08us cuMemAlloc
0.00% 2.5056ms 3 835.19us 348.68us 1.7719ms cuModuleLoadDataEx
0.00% 1.4557ms 4 363.94us 43.000us 1.1706ms cuMemcpyHtoD
0.00% 36.489us 8 4.5610us 3.6320us 8.1710us cuDeviceGetPCIBusId
0.00% 15.972us 30 532ns 167ns 2.4170us cuDeviceGetAttribute
0.00% 9.0610us 9 1.0060us 283ns 4.6000us cuDeviceGet
0.00% 3.2120us 3 1.0700us 1.0430us 1.0890us cuModuleGetFunction
0.00% 2.6260us 3 875ns 707ns 1.0060us cuCtxGetDevice
0.00% 2.4400us 1 2.4400us 2.4400us 2.4400us cuDriverGetVersion
0.00% 2.0020us 2 1.0010us 282ns 1.7200us cuDeviceGetCount
Problems with `Measure`
MWE:
julia> using CuYao
[ Info: Precompiling CuYao [b48ca7a8-dd42-11e8-2b8e-1b7706800275]
julia> reg = rand_state(3, nbatch=1000) |> cu
ArrayReg{1000, Complex{Float64}, CuArray...}
active qubits: 3/3
julia> c = Measure(3, locs=(1:2), collapseto=0)
Measure(3;locs=(1, 2), collapseto=000 ₍₂₎)
julia> reg |> c
[ Info: Building the CUDAnative run-time library for your sm_50 device, this might take a while...
ERROR: scalar getindex is disallowed
BUG when increasing `nbatch`.
julia> using CuYao
julia> c4 = concentrate(12, chain(4, chain(4, chain(4, chain(4, put(4, 2=>Ry(pi)))))), 8:11)
nqubits: 12
Concentrator: (8, 9, 10, 11)
└─ chain
└─ chain
└─ chain
└─ chain
└─ put on (2)
└─ rot(Y gate, 3.141592653589793)
julia> c5 = concentrate(12, chain(4, chain(4, chain(4, chain(4, control(4, 4, (2,3)=>ConstGate.SWAP))))), 8:11)
nqubits: 12
Concentrator: (8, 9, 10, 11)
└─ chain
└─ chain
└─ chain
└─ chain
└─ control(4)
└─ (2, 3) SWAP gate
julia> m = 4095
4095
julia> rand_state(12, nbatch = m) |> cu |> c4
ArrayReg{2000, Complex{Float64}, CuArray...}
active qubits: 12/12
julia> rand_state(12, nbatch = m) |> cu |> c5
ArrayReg{2000, Complex{Float64}, CuArray...}
active qubits: 12/12
julia> m2 = 4096
4096
julia> rand_state(12, nbatch = m2) |> cu |> c4
ERROR: CUDA error: invalid argument (code #1, ERROR_INVALID_VALUE)
julia> rand_state(12, nbatch = m2) |> cu |> c5
ERROR: CUDA error: invalid argument (code #1, ERROR_INVALID_VALUE)
Seems GPU not works to calculate the gradient
Hi,
I notice seems the gradient calculation through GPU is not properly working as expected.
Is that I make some mistakes?
The test code as follows
"""
using Yao, YaoExtensions
using Profile
using CuYao
n = 18; depth = 1000;
circuit = dispatch!(
variational_circuit(n, depth),
:random);
gatecount(circuit)
nparameters(circuit)
h = heisenberg(n);
cureg = cu(zero_state(n))
@time expect(h, cureg =>circuit)
@time _, grad = expect'(h, cureg=>circuit)
for 14 qubits, it is around 6 times difference
for 12, around 4 times
for 16
@Profile _, grad = expect'(h, cureg=>circuit)
Profile.print(format=:flat)
"""
and its profile
nohup: ignoring input
26.439291 seconds (52.09 M allocations: 2.923 GiB, 4.33% gc time, 17.06% compilation time)
18.178448 seconds (42.04 M allocations: 2.142 GiB, 6.94% gc time, 3.21% compilation time)
Count Overhead File Line Function
===== ======== ==== ==== ========
19 19 @Base/Base.jl 33 getproperty
3600 0 @Base/Base.jl 386 include(mod::Module, _path::String)
3 3 @Base/Base.jl 34 setproperty!
12 12 @Base/Base.jl 65 time_ns
1 0 @Base/abstractarray.jl 1197 _getindex
1 0 @Base/abstractarray.jl 70 axes
2 0 @Base/abstractarray.jl 89 axes
1349 0 @Base/abstractarray.jl 1056 copyto_axcheck!
1 0 @Base/abstractarray.jl 1170 getindex
1 0 @Base/abstractarray.jl 250 length
136 0 @Base/abstractarray.jl 784 similar
136 0 @Base/abstractarray.jl 785 similar
7 2 @Base/abstractarraymath.jl 70 #dropdims#187
1 1 @Base/abstractarraymath.jl 71 _dropdims(A::CUDA.CuArray{ComplexF64, 2, CUDA.Mem....
1 0 @Base/abstractarraymath.jl 74 _dropdims(A::CUDA.CuArray{ComplexF64, 2, CUDA.Mem....
3 0 @Base/abstractarraymath.jl 85 _dropdims(A::CUDA.CuArray{ComplexF64, 2, CUDA.Mem....
7 0 @Base/abstractarraymath.jl 70 dropdims##kw
24 0 @Base/abstractarraymath.jl 41 vec
32 0 @Base/abstractdict.jl 17 haskey
1 0 @Base/array.jl 1643 #reverse#91
1353 0 @Base/array.jl 540 Array
31 0 @Base/array.jl 670 _array_for
5 5 @Base/array.jl 884 _growend!
39 0 @Base/array.jl 449 fill
39 0 @Base/array.jl 451 fill
1 0 @Base/array.jl 335 fill!
2 2 @Base/array.jl ? get!(constructor::CUDA.var"#192#193", x::CUDA.PerD...
2 2 @Base/array.jl ? getindex
9 0 @Base/array.jl 391 getindex
20 20 @Base/array.jl 801 getindex
1 1 @Base/array.jl 205 isassigned
5 1 @Base/array.jl 777 iterate
5 0 @Base/array.jl 929 push!
1 0 @Base/array.jl 1643 reverse
2 2 @Base/array.jl 839 setindex!
1 1 @Base/array.jl 839 setindex!(A::Vector{Float64}, x::Float64, i1::Int64)
1 1 @Base/array.jl ? task_local_state!()
31 0 @Base/array.jl 108 vect
3 0 @Base/arraymath.jl 52 *(A::ComplexF64, B::Vector{ComplexF64})
2 0 @Base/arraymath.jl 55 *(A::Vector{ComplexF64}, B::ComplexF64)
10 0 @Base/arraymath.jl 39 -(A::LinearAlgebra.Diagonal{ComplexF64, Vector{Com...
68 0 @Base/arraymath.jl 30 conj(A::CUDA.CuArray{ComplexF64, 1, CUDA.Mem.Devic...
1 0 @Base/asyncevent.jl 21 Base.AsyncCondition()
1 0 @Base/asyncevent.jl 45 AsyncCondition
1 0 @Base/asyncevent.jl 101 _trywait(t::Timer)
1 0 @Base/asyncevent.jl 104 _trywait(t::Base.AsyncCondition)
2044 0 @Base/asyncevent.jl 111 _trywait(t::Timer)
3 0 @Base/asyncevent.jl 113 _trywait(t::Timer)
1 0 @Base/asyncevent.jl 171 _uv_hook_close(t::Timer)
1 0 @Base/asyncevent.jl 47 macro expansion
1072 20 @Base/asyncevent.jl 129 wait
6 6 @Base/atomics.jl 405 atomic_add!
1 1 @Base/atomics.jl 358 getindex
1 0 @Base/bool.jl 106 *
84 68 @Base/boot.jl 448 Array
4 4 @Base/boot.jl 450 Array
75 0 @Base/boot.jl 457 Array
4 0 @Base/boot.jl 458 Array
4 4 @Base/boot.jl 460 Array
10 0 @Base/boot.jl 465 Array
9 0 @Base/boot.jl 467 Array
1353 0 @Base/boot.jl 472 Array
3600 2 @Base/boot.jl 360 eval
2 2 @Base/boot.jl 362 kwfunc(f::Any)
3 0 @Base/broadcast.jl 621 _broadcast_getindex
3 2 @Base/broadcast.jl 648 _broadcast_getindex_evalf
1 0 @Base/broadcast.jl 207 axes
83 0 @Base/broadcast.jl 872 broadcast_preserving_zero_d
1 0 @Base/broadcast.jl 484 combine_axes
15 0 @Base/broadcast.jl 908 copy
3 0 @Base/broadcast.jl 930 copy
4 0 @Base/broadcast.jl 936 copyto!
4 0 @Base/broadcast.jl 983 copyto!
2 0 @Base/broadcast.jl 1078 copyto_nonleaf!(dest::Vector{Float64}, bc::Base.Br...
1 0 @Base/broadcast.jl 1080 copyto_nonleaf!(dest::Vector{Float64}, bc::Base.Br...
3 0 @Base/broadcast.jl 575 getindex
1 0 @Base/broadcast.jl 266 instantiate
2 0 @Base/broadcast.jl 984 macro expansion
291 0 @Base/broadcast.jl 883 materialize
10 0 @Base/broadcast.jl 196 similar
10 0 @Base/broadcast.jl 197 similar
3600 0 @Base/client.jl 485 _start()
3600 0 @Base/client.jl 285 exec_options(opts::Base.JLOptions)
2 0 @Base/complex.jl 277 *
1 0 @Base/complex.jl 333 /
1 1 @Base/complex.jl 12 Complex
1 1 @Base/complex.jl 849 cos(z::ComplexF64)
1 0 @Base/complex.jl 863 cos(z::ComplexF64)
5 0 @Base/complex.jl 864 cos(z::ComplexF64)
1 0 @Base/complex.jl 844 sin(z::ComplexF64)
2 0 @Base/condition.jl 124 #notify#515
15 1 @Base/condition.jl 73 lock
2 0 @Base/condition.jl 124 notify
2 0 @Base/condition.jl 130 notify(c::Base.GenericCondition{Base.Threads.SpinL...
2 0 @Base/condition.jl 74 unlock
3081 0 @Base/condition.jl 106 wait(c::Base.GenericCondition{ReentrantLock})
6 0 @Base/dict.jl 505 get
2 0 @Base/dict.jl 506 get(h::Dict{UInt64, Any}, key::UInt64, default::No...
3 0 @Base/dict.jl 169 hashindex
1 1 @Base/dict.jl ? ht_keyindex(h::Dict{UInt64, Any}, key::UInt64)
1 0 @Base/dict.jl 283 ht_keyindex(h::Dict{UInt64, Any}, key::UInt64)
3 0 @Base/dict.jl 284 ht_keyindex(h::Dict{CUDA.CuContext, Dict{UInt64, A...
1 0 @Base/dict.jl 288 ht_keyindex(h::Dict{CUDA.CuContext, Dict{UInt64, A...
1 1 @Base/dict.jl 292 ht_keyindex(h::Dict{CUDA.CuContext, Dict{UInt64, A...
1 0 @Base/dict.jl 171 isslotempty
1 0 @Base/div.jl 229 cld
1 0 @Base/div.jl 273 div
40 40 @Base/env.jl 38 _getenv(var::String)
40 0 @Base/env.jl 42 access_env
40 0 @Base/env.jl 80 get
2 0 @Base/essentials.jl 602 isempty
1 0 @Base/essentials.jl 767 isempty
7 7 @Base/float.jl 332 *
2 2 @Base/float.jl 326 +
1 1 @Base/float.jl 365 ==
1 0 @Base/float.jl 401 ==
2 2 @Base/float.jl 339 muladd
2 0 @Base/float.jl 296 round
2 2 @Base/float.jl 307 round
1 0 @Base/floatfuncs.jl 281 #isapprox#659
1 1 @Base/floatfuncs.jl 5 copysign
1 0 @Base/floatfuncs.jl 281 isapprox
5 5 @Base/gcutils.jl 121 enable_finalizers
6 6 @Base/gcutils.jl 48 finalizer
1 0 @Base/generator.jl 44 iterate
4 0 @Base/hashing.jl 18 hash
38 0 @Base/hashing.jl 23 hash
8 0 @Base/hashing.jl 71 hash
4 0 @Base/hashing.jl 72 hash
8 0 @Base/hashing.jl 73 hash
1 0 @Base/hashing.jl 29 hash_64_64
5 0 @Base/hashing.jl 30 hash_64_64
1 0 @Base/hashing.jl 31 hash_64_64
3 0 @Base/hashing.jl 32 hash_64_64
2 0 @Base/hashing.jl 33 hash_64_64
4 0 @Base/hashing.jl 34 hash_64_64
1 0 @Base/hashing.jl 35 hash_64_64
7 0 @Base/hashing.jl 63 hash_uint
10 0 @Base/hashing.jl 62 hash_uint64
33 31 @Base/iddict.jl 87 get
26 26 @Base/iddict.jl 92 getindex
32 0 @Base/iddict.jl 174 in
2 2 @Base/int.jl 88 *
1 0 @Base/int.jl 923 *
4 4 @Base/int.jl 87 +
1 0 @Base/int.jl 921 +
2 2 @Base/int.jl 86 -
4 4 @Base/int.jl 83 <
3 3 @Base/int.jl 441 <
3 0 @Base/int.jl 448 <
1 1 @Base/int.jl 457 <<
1 0 @Base/int.jl 464 <<
8 8 @Base/int.jl 456 >>
8 0 @Base/int.jl 462 >>
2 2 @Base/int.jl 262 rem
1 1 @Base/int.jl 477 rem
4 4 @Base/int.jl 333 xor
1 1 @Base/int.jl 285 ~
1 0 @Base/iterators.jl 110 iterate
2 0 @Base/iterators.jl 158 iterate
2 0 @Base/iterators.jl 159 iterate
1 0 @Base/iterators.jl 449 iterate
1 0 @Base/iterators.jl 116 reverse
1 1 @Base/libc.jl 355 malloc
4 4 @Base/libuv.jl 48 iolock_begin
1 0 @Base/libuv.jl 57 preserve_handle
505 505 @Base/libuv.jl 104 process_events
1 0 @Base/linked_list.jl 113 list_deletefirst!
1 0 @Base/linked_list.jl 86 popfirst!(q::Base.InvasiveLinkedList{Task})
3600 0 @Base/loading.jl 1148 _include(mapexpr::Function, mod::Module, _path::St...
3600 0 @Base/loading.jl 1094 include_string(mapexpr::typeof(identity), mod::Mod...
1 1 @Base/lock.jl 332 Event
3 3 @Base/lock.jl 86 lock(rl::ReentrantLock)
13 0 @Base/lock.jl 91 lock(rl::ReentrantLock)
1 1 @Base/lock.jl 108 lock(rl::ReentrantLock)
1 1 @Base/lock.jl 348 notify(e::Base.Event)
1 0 @Base/lock.jl 353 notify(e::Base.Event)
3 3 @Base/lock.jl 119 unlock(rl::ReentrantLock)
2 0 @Base/lock.jl 127 unlock(rl::ReentrantLock)
2 0 @Base/lock.jl 138 unlock(rl::ReentrantLock)
3 0 @Base/lock.jl 139 unlock(rl::ReentrantLock)
1037 0 @Base/lock.jl 340 wait(e::Base.Event)
1 1 @Base/locks-mt.jl 43 _get
1 1 @Base/locks-mt.jl 50 _set!
4 4 @Base/locks-mt.jl 36 _xchg!
9 9 @Base/locks-mt.jl 61 lock(l::Base.Threads.SpinLock)
3 0 @Base/locks-mt.jl 63 lock(l::Base.Threads.SpinLock)
4 0 @Base/locks-mt.jl 65 lock(l::Base.Threads.SpinLock)
25 0 @Base/locks-mt.jl 66 lock(l::Base.Threads.SpinLock)
2 2 @Base/locks-mt.jl 89 unlock(l::Base.Threads.SpinLock)
1 0 @Base/locks-mt.jl 91 unlock(l::Base.Threads.SpinLock)
3 0 @Base/locks-mt.jl 92 unlock(l::Base.Threads.SpinLock)
3 3 @Base/locks-mt.jl 94 unlock(l::Base.Threads.SpinLock)
2 2 @Base/logging.jl 477 current_logger_for_env(std_level::Base.CoreLogging...
1 0 @Base/logging.jl 478 current_logger_for_env(std_level::Base.CoreLogging...
50 2 @Base/logging.jl 479 current_logger_for_env(std_level::Base.CoreLogging...
1 1 @Base/logging.jl 473 current_logstate
2 2 @Base/logging.jl 519 env_override_minlevel(group::Symbol, _module::Module)
40 0 @Base/logging.jl 520 env_override_minlevel(group::Symbol, _module::Module)
5 5 @Base/logging.jl 521 env_override_minlevel(group::Symbol, _module::Module)
1 0 @Base/logging.jl 540 env_override_minlevel(group::Symbol, _module::Module)
54 2 @Base/logging.jl 356 macro expansion
1 1 @Base/logging.jl 357 macro expansion
2 0 @Base/math.jl 131 evalpoly
4 0 @Base/math.jl 407 log
2 0 @Base/math.jl 132 macro expansion
1 1 @Base/multidimensional.jl 399 __inc
1 0 @Base/multidimensional.jl 380 iterate
344 0 none ? #call#239
275 4 none ? call(::CUDA.HostKernel{CuYao.var"#kernel#26"{BitBa...
344 0 none ? call##kw
391 95 none ? (::CUDA.var"#call##kw")(::NamedTuple{(:threads, :b...
615 0 none ? convert_arguments
615 0 none ? macro expansion
526 2 none ? pack_arguments(::CUDA.var"#39#40"{Bool, Int64, CUD...
2 0 @Base/operators.jl 204 !=
7 0 @Base/operators.jl 560 *
3 0 @Base/operators.jl 560 +
8 0 @Base/operators.jl 938 ComposedFunction
1 0 @Base/operators.jl 1131 in
1354 0 @Base/operators.jl 858 |>
31 31 @Base/promotion.jl 410 ==
1 0 @Base/range.jl 22 Colon
1 1 @Base/range.jl 208 StepRange
1 0 @Base/range.jl 263 StepRange
1 0 @Base/range.jl 24 _colon
1 0 @Base/range.jl 1045 _reverse
6 0 @Base/reduce.jl 160 #mapfoldl#214
6 0 @Base/reduce.jl 287 #mapreduce#218
6 0 @Base/reduce.jl 456 #reduce#220
1 0 @Base/reduce.jl 880 _any
1 0 @Base/reduce.jl 56 _foldl_impl(op::Base.FilteringRF{BitBasis.var"#35#...
1 0 @Base/reduce.jl 415 _mapreduce(f::YaoBlocks.var"#117#118"{ArrayReg{2, ...
1 1 @Base/reduce.jl 144 _xfadjoint
1 0 @Base/reduce.jl 871 any
1 0 @Base/reduce.jl 48 foldl_impl(op::Base.FilteringRF{BitBasis.var"#35#3...
1 1 @Base/reduce.jl 53 getproperty
1 0 @Base/reduce.jl 245 macro expansion
6 0 @Base/reduce.jl 160 mapfoldl
3 0 @Base/reduce.jl 43 mapfoldl_impl(f::typeof(identity), op::typeof(+), ...
3 2 @Base/reduce.jl 44 mapfoldl_impl(f::typeof(identity), op::typeof(+), ...
6 0 @Base/reduce.jl 287 mapreduce
1 0 @Base/reduce.jl 243 mapreduce_impl(f::YaoBlocks.var"#117#118"{ArrayReg...
1 0 @Base/reduce.jl 257 mapreduce_impl
6 0 @Base/reduce.jl 456 reduce
793 0 @Base/reducedim.jl 899 #_sum#701
793 0 @Base/reducedim.jl 900 #_sum#702
1 0 @Base/reducedim.jl 310 #mapreduce#672
793 0 @Base/reducedim.jl 873 #sum#679
1 0 @Base/reducedim.jl 318 _mapreduce_dim
793 0 @Base/reducedim.jl 899 _sum
793 0 @Base/reducedim.jl 900 _sum
1 0 @Base/reducedim.jl 310 mapreduce
793 0 @Base/reducedim.jl 873 sum##kw
31 31 @Base/reflection.jl 291 objectid
4 0 @Base/refpointer.jl 135 Ref
4 4 @Base/refvalue.jl 7 RefValue
1 0 @Base/refvalue.jl 56 getindex
24 0 @Base/reshapedarray.jl 116 reshape
1 1 @Base/simdloop.jl ? macro expansion
3 0 @Base/simdloop.jl 77 macro expansion
1 0 @Base/simdloop.jl 79 macro expansion
1 1 @Base/sort.jl 729 sort!(v::Vector{Int64}; alg::Base.Sort.QuickSortAl...
3 2 @Base/sort.jl 747 sort!(v::Vector{Int64}; alg::Base.Sort.QuickSortAl...
1 1 @Base/sort.jl 597 sort!(v::Vector{Int64}, lo::Int64, hi::Int64, a::B...
4 0 @Base/sort.jl 735 sort!
1 1 @Base/special/hyperbolic.jl 119 cosh(x::Float64)
3 0 @Base/special/hyperbolic.jl 82 sinh(x::Float64)
1 0 @Base/special/hyperbolic.jl 48 sinh_kernel(x::Float64)
2 0 @Base/special/hyperbolic.jl 50 sinh_kernel(x::Float64)
1 0 @Base/special/log.jl 275 log(x::Float64)
3 0 @Base/special/log.jl 279 log(x::Float64)
1 0 @Base/special/log.jl 158 log_proc1
1 0 @Base/special/log.jl 171 log_proc1
1 0 @Base/special/log.jl 178 log_proc1
1 0 @Base/special/trig.jl 81 sin_kernel
1 0 @Base/special/trig.jl 177 sincos(x::Float64)
1 0 @Base/special/trig.jl 209 sincos_kernel
998 0 @Base/task.jl 406 (::Base.var"#578#579"{CUDA.var"#47#48"{CUDA.var"#1...
2 0 @Base/task.jl 642 schedule(t::Task, arg::Any; error::Bool)
4 4 @Base/task.jl 126 current_task
3 3 @Base/task.jl 572 enq_work(t::Task)
3 3 @Base/task.jl 573 enq_work(t::Task)
3 0 @Base/task.jl 574 enq_work(t::Task)
52 5 @Base/task.jl 585 enq_work(t::Task)
68 68 @Base/task.jl 595 enq_work(t::Task)
6 0 @Base/task.jl 243 get_task_tls
7 7 @Base/task.jl 246 get_task_tls
6 6 @Base/task.jl 165 getproperty
47 0 @Base/task.jl 382 macro expansion
1 1 @Base/task.jl ? popfirst!(W::Base.InvasiveLinkedListSynchronized{T...
11 11 @Base/task.jl 541 popfirst!(W::Base.InvasiveLinkedListSynchronized{T...
13 2 @Base/task.jl 542 popfirst!(W::Base.InvasiveLinkedListSynchronized{T...
6 6 @Base/task.jl 543 popfirst!(W::Base.InvasiveLinkedListSynchronized{T...
6 5 @Base/task.jl 544 popfirst!(W::Base.InvasiveLinkedListSynchronized{T...
3 0 @Base/task.jl 546 popfirst!(W::Base.InvasiveLinkedListSynchronized{T...
1 1 @Base/task.jl 752 poptask(W::Base.InvasiveLinkedListSynchronized{Task})
39 0 @Base/task.jl 753 poptask(W::Base.InvasiveLinkedListSynchronized{Task})
1 1 @Base/task.jl 754 poptask(W::Base.InvasiveLinkedListSynchronized{Task})
92430 92427 @Base/task.jl 755 poptask(W::Base.InvasiveLinkedListSynchronized{Task})
1 1 @Base/task.jl 758 poptask(W::Base.InvasiveLinkedListSynchronized{Task})
6 6 @Base/task.jl 515 push!(W::Base.InvasiveLinkedListSynchronized{Task}...
16 1 @Base/task.jl 516 push!(W::Base.InvasiveLinkedListSynchronized{Task}...
8 8 @Base/task.jl 517 push!(W::Base.InvasiveLinkedListSynchronized{Task}...
6 6 @Base/task.jl 518 push!(W::Base.InvasiveLinkedListSynchronized{Task}...
5 2 @Base/task.jl 520 push!(W::Base.InvasiveLinkedListSynchronized{Task}...
2 2 @Base/task.jl 522 push!(W::Base.InvasiveLinkedListSynchronized{Task}...
47 0 @Base/task.jl 599 schedule
2 0 @Base/task.jl 633 schedule##kw
89352 0 @Base/task.jl 489 task_done_hook(t::Task)
16 0 @Base/task.jl 241 task_local_storage
3 2 @Base/task.jl 237 threadid
4 4 @Base/task.jl 693 try_yieldto(undo::typeof(Base.ensure_rescheduled))
12 12 @Base/task.jl 694 try_yieldto(undo::typeof(Base.ensure_rescheduled))
5 5 @Base/task.jl 695 try_yieldto(undo::typeof(Base.ensure_rescheduled))
1 0 @Base/task.jl 700 try_yieldto(undo::typeof(Base.ensure_rescheduled))
2 0 @Base/task.jl 708 try_yieldto(undo::typeof(Base.ensure_rescheduled))
1 1 @Base/task.jl 738 trypoptask(W::Base.InvasiveLinkedListSynchronized{...
39 2 @Base/task.jl 739 trypoptask
1 0 @Base/task.jl 762 wait
92472 2 @Base/task.jl 763 wait
23 0 @Base/task.jl 764 wait
505 0 @Base/task.jl 765 wait
1 1 @Base/task.jl 653 yield()
82 2 @Base/task.jl 655 yield()
9 9 @Base/task.jl 656 yield()
568 0 @Base/task.jl 657 yield()
1072 0 @Base/threadingconstructs.jl 169 (::CUDA.var"#14#17"{CUDA.CuStream, Timer, CUDA.CuD...
1038 0 @Base/threadingconstructs.jl 169 (::CUDA.var"#15#18"{Timer, Base.Event})()
47 0 @Base/threadingconstructs.jl 178 macro expansion
6 0 @Base/timing.jl 286 macro expansion
235 0 @Base/timing.jl 287 macro expansion
6 0 @Base/timing.jl 288 macro expansion
46 0 @Base/tuple.jl 303 Tuple
46 41 @Base/tuple.jl 334 _totuple
1 1 @Base/tuple.jl 29 getindex
2 2 @Base/tuple.jl 86 indexed_iterate
1 0 @Base/tuple.jl 66 iterate
1 1 @Base/tuple.jl 213 map
3 2 @Base/tuple.jl 214 map
1 0 @Base/tuple.jl 215 map
1 1 @Base/tuple.jl 216 map(f::typeof(CUDA.cudaconvert), t::Tuple{typeof(i...
1 0 @Base/tuple.jl 216 map
1 0 @Base/tuple.jl 480 prod
3 0 @Base/util.jl 450 #PTXCompilerTarget#11
3 0 @Base/util.jl 450 Type##kw
1 1 @Base/version.jl ? hash(v::VersionNumber, h::UInt64)
1 1 @Base/version.jl 199 hash(v::VersionNumber, h::UInt64)
4 0 @Base/version.jl 201 hash(v::VersionNumber, h::UInt64)
1 0 @Base/version.jl 203 hash(v::VersionNumber, h::UInt64)
3 0 ....6/LinearAlgebra/src/diagonal.jl 174 *
4 0 ....6/LinearAlgebra/src/diagonal.jl 157 -
1 0 ...gebra/src/structuredbroadcast.jl 123 fzero
1 0 ...gebra/src/structuredbroadcast.jl 110 fzeropreserving
1 0 ...gebra/src/structuredbroadcast.jl 128 similar
4 0 ...gebra/src/structuredbroadcast.jl 131 similar
1 1 @Adapt/src/Adapt.jl 40 adapt(to::CUDA.Adaptor, x::Function)
4 0 @Adapt/src/Adapt.jl 40 adapt
1 0 @Adapt/src/base.jl 31 #7
3 1 @Adapt/src/base.jl 11 adapt_structure
1 0 @Adapt/src/base.jl 30 adapt_structure
1 0 @Adapt/src/base.jl 30 adapt_structure(to::CUDA.Adaptor, bc::Base.Broadca...
4 0 @BitBasis/src/iterate_control.jl 107 group_shift!(nbits::Int64, positions::Vector{Int64})
5 0 @BitBasis/src/iterate_control.jl 108 group_shift!(nbits::Int64, positions::Vector{Int64})
4 0 @BitBasis/src/iterate_control.jl 109 group_shift!(nbits::Int64, positions::Vector{Int64})
4 0 @BitBasis/src/iterate_control.jl 115 group_shift!(nbits::Int64, positions::Vector{Int64})
2 0 @BitBasis/src/iterate_control.jl 116 group_shift!(nbits::Int64, positions::Vector{Int64})
1 1 @BitBasis/src/iterate_control.jl 53 itercontrol(nbits::Int64, positions::Vector{Int64}...
7 0 @BitBasis/src/iterate_control.jl 54 itercontrol(nbits::Int64, positions::Vector{Int64}...
19 0 @BitBasis/src/iterate_control.jl 55 itercontrol(nbits::Int64, positions::Vector{Int64}...
58 12 @BitBasis/src/iterate_control.jl 57 itercontrol(nbits::Int64, positions::Vector{Int64}...
1 0 @BitBasis/src/iterate_control.jl 80 length
1 0 @BitBasis/src/operations.jl 107 bmask
7 0 @BitBasis/src/operations.jl 110 bmask
1 0 @BitBasis/src/operations.jl 114 bmask
10 0 @CUDA/lib/cudadrv/devices.jl 175 attribute
1 0 @CUDA/lib/cudadrv/devices.jl 65 convert
2 0 @CUDA/lib/cudadrv/devices.jl 23 current_device
5 0 @CUDA/lib/cudadrv/devices.jl 186 warpsize
67 0 @CUDA/lib/cudadrv/error.jl 80 initialize_context
1134 0 @CUDA/lib/cudadrv/error.jl 97 macro expansion
505 2 @CUDA/lib/cudadrv/execution.jl 69 #39
615 8 @CUDA/lib/cudadrv/execution.jl 136 #44
1 0 @CUDA/lib/cudadrv/execution.jl 147 #47
615 0 @CUDA/lib/cudadrv/execution.jl 135 #cudacall#43
7 7 @CUDA/lib/cudadrv/execution.jl 52 launch(::CUDA.CuFunction, ::CUDA.KernelState, ::Fu...
470 0 @CUDA/lib/cudadrv/execution.jl 62 #launch#38
67 11 @CUDA/lib/cudadrv/execution.jl 62 launch(::CUDA.CuFunction, ::CUDA.KernelState, ::Fu...
1 0 @CUDA/lib/cudadrv/execution.jl 146 #launch#46
5 0 @CUDA/lib/cudadrv/execution.jl 159 #launch#46
615 0 @CUDA/lib/cudadrv/execution.jl 135 cudacall##kw
11 11 @CUDA/lib/cudadrv/execution.jl 52 (::CUDA.var"#launch##kw")(::NamedTuple{(:threads, ...
595 24 @CUDA/lib/cudadrv/execution.jl 55 (::CUDA.var"#launch##kw")(::NamedTuple{(:threads, ...
6 0 @CUDA/lib/cudadrv/execution.jl 146 launch##kw
19 0 @CUDA/lib/cudadrv/execution.jl 32 macro expansion
505 0 @CUDA/lib/cudadrv/execution.jl 33 macro expansion
615 0 @CUDA/lib/cudadrv/execution.jl 95 macro expansion
10 10 @CUDA/lib/cudadrv/libcuda.jl 59 macro expansion
13 13 @CUDA/lib/cudadrv/libcuda.jl 144 macro expansion
1 0 @CUDA/lib/cudadrv/libcuda.jl 597 macro expansion
214 214 @CUDA/lib/cudadrv/libcuda.jl 598 macro expansion
2 0 @CUDA/lib/cudadrv/libcuda.jl 1031 macro expansion
29 29 @CUDA/lib/cudadrv/libcuda.jl 1032 macro expansion
7 0 @CUDA/lib/cudadrv/libcuda.jl 1226 macro expansion
494 494 @CUDA/lib/cudadrv/libcuda.jl 1227 macro expansion
5 5 @CUDA/lib/cudadrv/libcuda.jl 1254 macro expansion
18 0 @CUDA/lib/cudadrv/libcuda.jl 1633 macro expansion
149 140 @CUDA/lib/cudadrv/libcuda.jl 1634 macro expansion
1 0 @CUDA/lib/cudadrv/libcuda.jl 2221 macro expansion
84 84 @CUDA/lib/cudadrv/libcuda.jl 2222 macro expansion
4 0 @CUDA/lib/cudadrv/libcuda.jl 2266 macro expansion
113 ┌ Warning: Assignment to grad in soft scope is ambiguous because a global variable by the same name exists: grad will be treated as a new local. Disambiguate by using local grad to suppress this warning or global grad to assign to the existing global variable.
└ @ /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.6/Profile/src/Profile.jl:28
113 @CUDA/lib/cudadrv/libcuda.jl 2267 macro expansion
2 2 @CUDA/lib/cudadrv/libcuda.jl 150 unsafe_cuCtxGetDevice
1 0 @CUDA/lib/cudadrv/libcuda.jl 882 unsafe_cuPointerGetAttribute(data::Base.RefValue{U...
8 8 @CUDA/lib/cudadrv/libcuda.jl 883 unsafe_cuPointerGetAttribute(data::Base.RefValue{U...
2 2 @CUDA/lib/cudadrv/libcuda.jl 1023 unsafe_cuStreamQuery(hStream::CUDA.CuStream)
33 0 @CUDA/lib/cudadrv/libcuda.jl 1024 unsafe_cuStreamQuery(hStream::CUDA.CuStream)
308 308 @CUDA/lib/cudadrv/libcuda.jl 1025 unsafe_cuStreamQuery(hStream::CUDA.CuStream)
2 0 @CUDA/lib/cudadrv/memory.jl 77 #alloc#1
117 0 @CUDA/lib/cudadrv/memory.jl 83 #alloc#1
1 0 @CUDA/lib/cudadrv/memory.jl 89 #alloc#1
85 0 @CUDA/lib/cudadrv/memory.jl 97 #free#2
216 0 @CUDA/lib/cudadrv/memory.jl 397 #unsafe_copyto!#8
120 0 @CUDA/lib/cudadrv/memory.jl 75 alloc##kw
85 0 @CUDA/lib/cudadrv/memory.jl 93 free##kw
10 0 @CUDA/lib/cudadrv/memory.jl 849 is_pinned
219 0 @CUDA/lib/cudadrv/memory.jl 397 (::Base.var"#unsafe_copyto!##kw")(::NamedTuple{(:a...
1 0 ...A/lib/cudadrv/module/function.jl 27 hash(fun::CUDA.CuFunction, h::UInt64)
10 2 @CUDA/lib/cudadrv/occupancy.jl 61 (::CUDA.var"#52#54"{ComposedFunction{CUDA.var"#com...
1 0 @CUDA/lib/cudadrv/occupancy.jl 56 launch_configuration(fun::CUDA.CuFunction; shmem::...
1 0 @CUDA/lib/cudadrv/occupancy.jl 57 launch_configuration(fun::CUDA.CuFunction; shmem::...
85 2 @CUDA/lib/cudadrv/occupancy.jl 59 #launch_configuration#51
1 1 @CUDA/lib/cudadrv/occupancy.jl 61 launch_configuration(fun::CUDA.CuFunction; shmem::...
98 98 @CUDA/lib/cudadrv/occupancy.jl 62 launch_configuration(fun::CUDA.CuFunction; shmem::...
89 4 @CUDA/lib/cudadrv/occupancy.jl 63 launch_configuration(fun::CUDA.CuFunction; shmem::...
35 0 @CUDA/lib/cudadrv/occupancy.jl 56 launch_configuration
241 1 @CUDA/lib/cudadrv/occupancy.jl 56 launch_configuration##kw
2 0 @CUDA/lib/cudadrv/state.jl 162 context!(f::CUDA.var"#210#211"{CUDA.CuArray{Comple...
2 2 @CUDA/lib/cudadrv/state.jl 163 context!(f::CUDA.var"#210#211"{CUDA.CuArray{Comple...
1 1 @CUDA/lib/cudadrv/state.jl 163 #context!#63
107 1 @CUDA/lib/cudadrv/state.jl 164 context!(f::CUDA.var"#210#211"{CUDA.CuArray{Comple...
1346 1 @CUDA/lib/cudadrv/state.jl 164 #context!#63
26 2 @CUDA/lib/cudadrv/state.jl 106 active_state
7 0 @CUDA/lib/cudadrv/state.jl 107 active_state
3 0 @CUDA/lib/cudadrv/state.jl 122 context
2 0 @CUDA/lib/cudadrv/state.jl 140 context!(ctx::CUDA.CuContext)
1347 0 @CUDA/lib/cudadrv/state.jl 161 context!
112 1 @CUDA/lib/cudadrv/state.jl 161 (::CUDA.var"#context!##kw")(::NamedTuple{(:skip_de...
6 1 @CUDA/lib/cudadrv/state.jl 185 device
3 2 @CUDA/lib/cudadrv/state.jl 193 device_context
1 1 @CUDA/lib/cudadrv/state.jl 189 device_contexts()
1 0 @CUDA/lib/cudadrv/state.jl 314 deviceid
2 2 @CUDA/lib/cudadrv/state.jl 440 get!(constructor::CUDA.var"#192#193", x::CUDA.PerD...
3 0 @CUDA/lib/cudadrv/state.jl 443 get!(constructor::CUDA.var"#192#193", x::CUDA.PerD...
1 1 @CUDA/lib/cudadrv/state.jl 422 get_values(x::CUDA.PerDevice{Base.RefValue{Union{N...
54 8 @CUDA/lib/cudadrv/state.jl 88 prepare_cuda_state
13 0 @CUDA/lib/cudadrv/state.jl 94 prepare_cuda_state
18 1 @CUDA/lib/cudadrv/state.jl 346 stream
5 0 @CUDA/lib/cudadrv/state.jl 347 stream
4 4 @CUDA/lib/cudadrv/state.jl 350 stream
1 0 @CUDA/lib/cudadrv/state.jl 80 task_local_state()
1 0 @CUDA/lib/cudadrv/state.jl 81 task_local_state()
13 13 @CUDA/lib/cudadrv/state.jl 68 task_local_state!()
16 0 @CUDA/lib/cudadrv/state.jl 69 task_local_state!()
31 0 @CUDA/lib/cudadrv/state.jl 70 task_local_state!()
34 1 @CUDA/lib/cudadrv/state.jl 71 task_local_state!()
1 1 @CUDA/lib/cudadrv/state.jl 73 task_local_state!()
8 8 @CUDA/lib/cudadrv/state.jl 60 validate_task_local_state
1 0 @CUDA/lib/cudadrv/stream.jl 159 #13
1 1 @CUDA/lib/cudadrv/stream.jl 121 synchronize(stream::CUDA.CuStream; blocking::Nothing)
38 0 @CUDA/lib/cudadrv/stream.jl 128 synchronize(stream::CUDA.CuStream; blocking::Nothing)
31 0 @CUDA/lib/cudadrv/stream.jl 132 synchronize(stream::CUDA.CuStream; blocking::Nothing)
2 0 @CUDA/lib/cudadrv/stream.jl 134 synchronize(stream::CUDA.CuStream; blocking::Nothing)
2 2 @CUDA/lib/cudadrv/stream.jl 32 default_stream
349 7 @CUDA/lib/cudadrv/stream.jl 103 isdone
1 1 @CUDA/lib/cudadrv/stream.jl 104 isdone
34 0 @CUDA/lib/cudadrv/stream.jl 165 macro expansion
1072 0 @CUDA/lib/cudadrv/stream.jl 169 macro expansion
13 0 @CUDA/lib/cudadrv/stream.jl 182 macro expansion
1038 0 @CUDA/lib/cudadrv/stream.jl 183 macro expansion
49 0 @CUDA/lib/cudadrv/stream.jl 139 nonblocking_synchronize
9 9 @CUDA/lib/cudadrv/stream.jl 148 nonblocking_synchronize
668 4 @CUDA/lib/cudadrv/stream.jl 150 nonblocking_synchronize
301 0 @CUDA/lib/cudadrv/stream.jl 152 nonblocking_synchronize
1 0 @CUDA/lib/cudadrv/stream.jl 157 nonblocking_synchronize
6 0 @CUDA/lib/cudadrv/stream.jl 158 nonblocking_synchronize
47 0 @CUDA/lib/cudadrv/stream.jl 164 nonblocking_synchronize
72 0 @CUDA/lib/cudadrv/stream.jl 122 synchronize
13 0 @CUDA/lib/utils/call.jl 26 cuCtxGetCurrent
10 0 @CUDA/lib/utils/call.jl 26 cuDeviceGetAttribute
5 0 @CUDA/lib/utils/call.jl 26 cuLaunchHostFunc(hStream::CUDA.CuStream, fn::Ptr{N...
503 2 @CUDA/lib/utils/call.jl 26 cuLaunchKernel(f::CUDA.CuFunction, gridDimX::UInt3...
117 0 @CUDA/lib/utils/call.jl 26 cuMemAllocAsync(dptr::Base.RefValue{CUDA.CuPtr{Not...
85 0 @CUDA/lib/utils/call.jl 26 cuMemFreeAsync(dptr::CUDA.Mem.DeviceBuffer, hStrea...
216 1 @CUDA/lib/utils/call.jl 26 cuMemcpyDtoHAsync_v2(dstHost::Ptr{ComplexF64}, src...
169 2 @CUDA/lib/utils/call.jl 26 cuOccupancyMaxPotentialBlockSize(minGridSize::Base...
31 0 @CUDA/lib/utils/call.jl 26 cuStreamSynchronize(hStream::CUDA.CuStream)
1 0 @CUDA/lib/utils/memoization.jl 71 macro expansion
4 0 @CUDA/lib/utils/memoization.jl 74 macro expansion
1 1 @CUDA/lib/utils/memoization.jl 76 macro expansion
2 0 @CUDA/lib/utils/threading.jl 25 #get!#6
1 0 @CUDA/lib/utils/threading.jl 28 #get!#6
3 0 @CUDA/lib/utils/threading.jl 25 get!
106 2 @CUDA/src/array.jl 79 #210
1053 0 @CUDA/src/array.jl 410 (::CUDA.var"#217#218"{ComplexF64, Array{ComplexF64...
219 0 @CUDA/src/array.jl 413 (::CUDA.var"#217#218"{ComplexF64, Array{ComplexF64...
72 0 @CUDA/src/array.jl 420 (::CUDA.var"#217#218"{ComplexF64, Array{ComplexF64...
20 0 @CUDA/src/array.jl 42 CuArray
126 0 @CUDA/src/array.jl 42 CUDA.CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}...
7 7 @CUDA/src/array.jl 44 CUDA.CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}...
2 0 @CUDA/src/array.jl 45 CuArray
1 0 @CUDA/src/array.jl 45 CUDA.CuArray{ComplexF64, 2, CUDA.Mem.DeviceBuffer}...
129 0 @CUDA/src/array.jl 125 CuArray
129 0 @CUDA/src/array.jl 136 CuArray
19 0 @CUDA/src/array.jl 50 Type##kw
19 19 @CUDA/src/array.jl 51 _#208
5 0 @CUDA/src/array.jl 727 _derived_array
20 0 @CUDA/src/array.jl 732 _derived_array
3 0 @CUDA/src/array.jl 734 derived_array
1 1 @CUDA/src/array.jl 238 context
1349 1 @CUDA/src/array.jl 360 copyto!
1349 0 @CUDA/src/array.jl 364 copyto!
28 0 @CUDA/src/array.jl 719 reshape(a::CUDA.CuArray{ComplexF64, 2, CUDA.Mem.De...
28 0 @CUDA/src/array.jl 164 similar
1 1 @CUDA/src/array.jl 404 unsafe_copyto!(dest::Array{ComplexF64, 0}, doffs::...
1347 0 @CUDA/src/array.jl 406 unsafe_copyto!(dest::Array{ComplexF64, 0}, doffs::...
135 0 @CUDA/src/array.jl 99 unsafe_finalize!(xs::CUDA.CuArray{ComplexF64, 1, C...
3 3 @CUDA/src/array.jl 68 unsafe_free!(xs::CUDA.CuArray{ComplexF64, 2, CUDA....
5 0 @CUDA/src/array.jl 70 unsafe_free!(xs::CUDA.CuArray{ComplexF64, 2, CUDA....
9 4 @CUDA/src/array.jl 72 unsafe_free!(xs::CUDA.CuArray{ComplexF64, 0, CUDA....
1 0 @CUDA/src/array.jl 76 unsafe_free!(xs::CUDA.CuArray{ComplexF64, 1, CUDA....
1 1 @CUDA/src/array.jl 77 unsafe_free!(xs::CUDA.CuArray{ComplexF64, 3, CUDA....
113 0 @CUDA/src/array.jl 78 unsafe_free!(xs::CUDA.CuArray{ComplexF64, 1, CUDA....
1 1 @CUDA/src/array.jl 86 unsafe_free!(xs::CUDA.CuArray{ComplexF64, 4, CUDA....
95 0 @CUDA/src/broadcast.jl 11 similar
34 0 @CUDA/src/broadcast.jl 14 similar
1 1 @CUDA/src/compiler/exceptions.jl 26 check_exceptions()
1 1 @CUDA/src/compiler/exceptions.jl 38 check_exceptions()
14 14 @CUDA/src/compiler/execution.jl 483 (::CUDA.HostKernel{typeof(CUDA.partial_mapreduce_g...
345 0 @CUDA/src/compiler/execution.jl 484 ##260
555 139 @CUDA/src/compiler/execution.jl 484 (::CUDA.HostKernel{CuYao.var"#kernel#26"{BitBasis....
1 1 @CUDA/src/compiler/execution.jl ? cufunction(f::CuYao.var"#kernel#26"{BitBasis.IterC...
2 2 @CUDA/src/compiler/execution.jl 292 cufunction(f::CuYao.var"#kernel#26"{BitBasis.IterC...
26 0 @CUDA/src/compiler/execution.jl 293 cufunction(f::CuYao.var"#kernel#26"{BitBasis.IterC...
4 0 @CUDA/src/compiler/execution.jl 294 cufunction(f::CuYao.var"#kernel#28", tt::Type{Tupl...
22 0 @CUDA/src/compiler/execution.jl 296 cufunction(f::CuYao.var"#kernel#29", tt::Type{Tupl...
371 28 @CUDA/src/compiler/execution.jl 299 cufunction(f::CuYao.var"#kernel#29", tt::Type{Tupl...
25 19 @CUDA/src/compiler/execution.jl 304 cufunction(f::CuYao.var"#kernel#28", tt::Type{Tupl...
15 13 @CUDA/src/compiler/execution.jl 305 cufunction(f::CuYao.var"#kernel#29", tt::Type{Tupl...
6 6 @CUDA/src/compiler/execution.jl 314 cufunction(f::CuYao.var"#kernel#29", tt::Type{Tupl...
10 10 @CUDA/src/compiler/execution.jl 483 (::Core.var"#Any##kw")(::NamedTuple{(:threads, :bl...
743 6 @CUDA/src/compiler/execution.jl 484 Any##kw
196 19 @CUDA/src/compiler/execution.jl 484 (::Core.var"#Any##kw")(::NamedTuple{(:threads, :bl...
6 1 @CUDA/src/compiler/execution.jl 152 cudaconvert
345 2 @CUDA/src/compiler/execution.jl 293 cufunction
17 0 @CUDA/src/compiler/execution.jl 293 cufunction(f::CuYao.var"#kernel#26"{BitBasis.IterC...
99 1 @CUDA/src/compiler/execution.jl 293 cufunction##kw
16 0 @CUDA/src/compiler/execution.jl 293 (::CUDA.var"#cufunction##kw")(::NamedTuple{(:name,...
4 0 @CUDA/src/compiler/execution.jl 320 cufunction_cache
5 0 @CUDA/src/compiler/execution.jl 99 macro expansion
493 16 @CUDA/src/compiler/execution.jl 102 macro expansion
829 15 @CUDA/src/compiler/execution.jl 104 macro expansion
615 0 @CUDA/src/compiler/execution.jl 204 macro expansion
1 0 @CUDA/src/compiler/execution.jl 528 nextwarp(dev::CUDA.CuDevice, threads::Int64)
4 0 @CUDA/src/compiler/execution.jl 533 prevwarp
3 0 @CUDA/src/compiler/execution.jl 534 prevwarp
22 1 @CUDA/src/compiler/gpucompiler.jl 51 #CUDACompilerTarget#238
22 0 @CUDA/src/compiler/gpucompiler.jl 51 CUDACompilerTarget
5 5 @CUDA/src/compiler/gpucompiler.jl ? device_properties(dev::CUDA.CuDevice)
2 2 @CUDA/src/compiler/gpucompiler.jl 6 device_properties(dev::CUDA.CuDevice)
3 0 @CUDA/src/compiler/gpucompiler.jl 7 device_properties(dev::CUDA.CuDevice)
9 4 @CUDA/src/compiler/gpucompiler.jl 47 device_properties(dev::CUDA.CuDevice)
727 0 @CUDA/src/gpuarrays.jl 30 #gpu_call#281
7 7 @CUDA/src/gpuarrays.jl ? #launch_heuristic#280
217 0 @CUDA/src/gpuarrays.jl 17 #launch_heuristic#280
35 0 @CUDA/src/gpuarrays.jl 22 #launch_heuristic#280
50 0 @CUDA/src/gpuarrays.jl 24 #launch_heuristic#280
728 1 @CUDA/src/gpuarrays.jl 30 (::GPUArrays.var"#gpu_call##kw")(::NamedTuple{(:na...
2 2 @CUDA/src/gpuarrays.jl 15 (::GPUArrays.var"#launch_heuristic##kw")(::NamedTu...
309 0 @CUDA/src/gpuarrays.jl 17 (::GPUArrays.var"#launch_heuristic##kw")(::NamedTu...
1 1 @CUDA/src/mapreduce.jl ? mapreducedim!(f::typeof(identity), op::typeof(Base...
1 0 @CUDA/src/mapreduce.jl 173 mapreducedim!(f::typeof(identity), op::typeof(Base...
6 0 @CUDA/src/mapreduce.jl 174 mapreducedim!(f::typeof(identity), op::typeof(Base...
5 0 @CUDA/src/mapreduce.jl 200 mapreducedim!(f::typeof(identity), op::typeof(Base...
1 0 @CUDA/src/mapreduce.jl 213 mapreducedim!(f::typeof(identity), op::typeof(Base...
1 0 @CUDA/src/mapreduce.jl 220 mapreducedim!(f::typeof(identity), op::typeof(Base...
79 0 @CUDA/src/mapreduce.jl 234 mapreducedim!(f::typeof(identity), op::typeof(Base...
191 0 @CUDA/src/mapreduce.jl 236 mapreducedim!(f::typeof(identity), op::typeof(Base...
1 0 @CUDA/src/mapreduce.jl 249 mapreducedim!(f::typeof(identity), op::typeof(Base...
137 0 @CUDA/src/mapreduce.jl 261 mapreducedim!(f::typeof(identity), op::typeof(Base...
28 0 @CUDA/src/mapreduce.jl 264 mapreducedim!(f::typeof(identity), op::typeof(Base...
304 0 @CUDA/src/mapreduce.jl 272 mapreducedim!(f::typeof(identity), op::typeof(Base...
244 0 @CUDA/src/mapreduce.jl 275 mapreducedim!(f::typeof(identity), op::typeof(Base...
5 0 @CUDA/src/mapreduce.jl 164 big_mapreduce_threshold
8 1 @CUDA/src/mapreduce.jl 223 compute_threads
759 3 @CUDA/src/mapreduce.jl 172 mapreducedim!##kw
7 0 @CUDA/src/pool.jl 309 #_alloc#202
139 0 @CUDA/src/pool.jl 313 #_alloc#202
2 0 @CUDA/src/pool.jl 364 #_free#205
2 0 @CUDA/src/pool.jl 368 #_free#205
2 0 @CUDA/src/pool.jl 369 #_free#205
5 0 @CUDA/src/pool.jl 371 #_free#205
89 0 @CUDA/src/pool.jl 375 #_free#205
4 4 @CUDA/src/pool.jl 38 actual_alloc(bytes::Int64; async::Bool, stream::CU...
121 0 @CUDA/src/pool.jl 39 actual_alloc(bytes::Int64; async::Bool, stream::CU...
2 2 @CUDA/src/pool.jl 51 actual_alloc(bytes::Int64; async::Bool, stream::CU...
89 0 @CUDA/src/pool.jl 57 #actual_free#187
146 0 @CUDA/src/pool.jl 299 #alloc#201
1 1 @CUDA/src/pool.jl 346 #free#204
103 0 @CUDA/src/pool.jl 347 #free#204
1 1 @CUDA/src/pool.jl 308 (::CUDA.var"#_alloc##kw")(::NamedTuple{(:stream,),...
146 0 @CUDA/src/pool.jl 309 (::CUDA.var"#_alloc##kw")(::NamedTuple{(:stream,),...
100 0 @CUDA/src/pool.jl 364 (::CUDA.var"#_free##kw")(::NamedTuple{(:stream,), ...
127 0 @CUDA/src/pool.jl 38 actual_alloc##kw
89 0 @CUDA/src/pool.jl 57 actual_free##kw
146 0 @CUDA/src/pool.jl 295 alloc
104 0 @CUDA/src/pool.jl 342 (::CUDA.var"#free##kw")(::NamedTuple{(:stream,), T...
120 0 @CUDA/src/pool.jl 41 macro expansion
85 0 @CUDA/src/pool.jl 58 macro expansion
127 0 @CUDA/src/pool.jl 232 macro expansion
5 0 @CUDA/src/pool.jl 314 macro expansion
3 0 @CUDA/src/pool.jl 315 macro expansion
100 0 @CUDA/src/pool.jl 348 macro expansion
8 0 @CUDA/src/pool.jl 83 pool_mark(dev::CUDA.CuDevice)
8 0 @CUDA/src/pool.jl 78 pool_status
1 0 @CUDA/src/pool.jl 70 stream_ordered(dev::CUDA.CuDevice)
6 0 @CUDA/src/pool.jl 71 stream_ordered(dev::CUDA.CuDevice)
1354 0 @CuYao/src/CUDApatch.jl 66 as_scalar
125 0 @CuYao/src/gpuapplys.jl 107 _instruct!
16 0 @CuYao/src/gpuapplys.jl 109 _instruct!(state::CUDA.CuArray{ComplexF64, 1, CUDA...
77 1 @CuYao/src/gpuapplys.jl 112 _instruct!(state::CUDA.CuArray{ComplexF64, 1, CUDA...
1 0 @CuYao/src/gpuapplys.jl 114 _instruct!(state::CUDA.CuArray{ComplexF64, 1, CUDA...
206 4 @CuYao/src/gpuapplys.jl 121 _instruct!(state::CUDA.CuArray{ComplexF64, 1, CUDA...
12 0 @CuYao/src/gpuapplys.jl 165 _instruct!(state::CUDA.CuArray{ComplexF64, 1, CUDA...
177 0 @CuYao/src/gpuapplys.jl 175 _instruct!(state::CUDA.CuArray{ComplexF64, 1, CUDA...
13 0 @CuYao/src/gpuapplys.jl 52 instruct!(#unused#::Val{2}, state::CUDA.CuArray{Co...
21 0 @CuYao/src/gpuapplys.jl 56 instruct!(#unused#::Val{2}, state::CUDA.CuArray{Co...
14 14 @CuYao/src/gpuapplys.jl 59 instruct!(#unused#::Val{2}, state::CUDA.CuArray{Co...
295 3 @CuYao/src/gpuapplys.jl 65 instruct!(#unused#::Val{2}, state::CUDA.CuArray{Co...
14 0 @CuYao/src/gpuapplys.jl 88 instruct!(#unused#::Val{2}, state::CUDA.CuArray{Co...
197 0 @CuYao/src/gpuapplys.jl 98 instruct!(#unused#::Val{2}, state::CUDA.CuArray{Co...
1 0 @CuYao/src/gpuapplys.jl 214 instruct!
315 0 @CuYao/src/gpuapplys.jl 218 instruct!
175 0 @CuYao/src/gpuapplys.jl 226 instruct!
242 2 @GPUArrays/src/device/execution.jl 68 #gpu_call#1
625 2 @GPUArrays/src/device/execution.jl 72 #gpu_call#1
105 0 @GPUArrays/src/device/execution.jl 76 #gpu_call#1
494 1 @GPUArrays/src/device/execution.jl 48 (::GPUArrays.var"#gpu_call##kw")(::NamedTuple{(:el...
479 0 @GPUArrays/src/device/execution.jl 48 gpu_call##kw
72 1 @GPUArrays/src/host/broadcast.jl 73 _copyto!
105 0 @GPUArrays/src/host/broadcast.jl 77 _copyto!
272 0 @GPUArrays/src/host/broadcast.jl 47 copy
177 0 @GPUArrays/src/host/broadcast.jl 56 copyto!
2 2 @GPUArrays/src/host/mapreduce.jl 35 _mapreduce(f::typeof(identity), op::typeof(Base.ad...
34 0 @GPUArrays/src/host/mapreduce.jl 64 _mapreduce(f::typeof(identity), op::typeof(Base.ad...
759 0 @GPUArrays/src/host/mapreduce.jl 69 _mapreduce(f::typeof(identity), op::typeof(Base.ad...
793 0 @GPUArrays/src/host/mapreduce.jl 31 #mapreduce#20
793 0 @GPUArrays/src/host/mapreduce.jl 37 _mapreduce##kw
793 0 @GPUArrays/src/host/mapreduce.jl 31 mapreduce##kw
1 0 @GPUArrays/src/host/quirks.jl 25 _axes
1 0 @GPUArrays/src/host/quirks.jl 22 combine_axes
3 3 @GPUCompiler/src/cache.jl 66 cached_compilation(cache::Dict{UInt64, Any}, job::...
290 190 @GPUCompiler/src/cache.jl 71 cached_compilation(cache::Dict{UInt64, Any}, job::...
1 0 @GPUCompiler/src/cache.jl 72 cached_compilation(cache::Dict{UInt64, Any}, job::...
18 0 @GPUCompiler/src/cache.jl 78 cached_compilation(cache::Dict{UInt64, Any}, job::...
7 7 @GPUCompiler/src/cache.jl 79 cached_compilation(cache::Dict{UInt64, Any}, job::...
2 0 @GPUCompiler/src/cache.jl 80 cached_compilation(cache::Dict{UInt64, Any}, job::...
9 2 @GPUCompiler/src/cache.jl 101 cached_compilation(cache::Dict{UInt64, Any}, job::...
1 1 @GPUCompiler/src/interface.jl 73 hash(spec::GPUCompiler.FunctionSpec{CuYao.var"#ker...
3 0 @GPUCompiler/src/interface.jl 74 hash(spec::GPUCompiler.FunctionSpec{CuYao.var"#ker...
2 0 @GPUCompiler/src/interface.jl 75 hash(spec::GPUCompiler.FunctionSpec{CuYao.var"#ker...
2 0 @GPUCompiler/src/interface.jl 76 hash(spec::GPUCompiler.FunctionSpec{CuYao.var"#ker...
2 1 @GPUCompiler/src/interface.jl 77 hash(spec::GPUCompiler.FunctionSpec{CuYao.var"#ker...
4 0 @GPUCompiler/src/interface.jl 78 hash(spec::GPUCompiler.FunctionSpec{CuYao.var"#ker...
33 0 @GPUCompiler/src/interface.jl 160 hash(job::GPUCompiler.CompilerJob{GPUCompiler.PTXC...
13 0 @GPUCompiler/src/interface.jl 161 hash(job::GPUCompiler.CompilerJob{GPUCompiler.PTXC...
1 0 @GPUCompiler/src/interface.jl 162 hash(job::GPUCompiler.CompilerJob{GPUCompiler.PTXC...
3 0 @GPUCompiler/src/interface.jl 163 hash(job::GPUCompiler.CompilerJob{GPUCompiler.PTXC...
1 1 @GPUCompiler/src/interface.jl 164 hash(job::GPUCompiler.CompilerJob{GPUCompiler.PTXC...
3 3 @GPUCompiler/src/ptx.jl 8 PTXCompilerTarget
3 3 @GPUCompiler/src/ptx.jl 26 hash(target::GPUCompiler.PTXCompilerTarget, h::UIn...
2 0 @GPUCompiler/src/ptx.jl 27 hash(target::GPUCompiler.PTXCompilerTarget, h::UIn...
4 0 @GPUCompiler/src/ptx.jl 28 hash(target::GPUCompiler.PTXCompilerTarget, h::UIn...
2 0 @GPUCompiler/src/ptx.jl 31 hash(target::GPUCompiler.PTXCompilerTarget, h::UIn...
1 0 @GPUCompiler/src/ptx.jl 32 hash(target::GPUCompiler.PTXCompilerTarget, h::UIn...
6 0 @GPUCompiler/src/ptx.jl 34 hash(target::GPUCompiler.PTXCompilerTarget, h::UIn...
6 1 @GPUCompiler/src/ptx.jl 35 hash(target::GPUCompiler.PTXCompilerTarget, h::UIn...
6 2 @GPUCompiler/src/ptx.jl 36 hash(target::GPUCompiler.PTXCompilerTarget, h::UIn...
5 0 @GPUCompiler/src/ptx.jl 37 hash(target::GPUCompiler.PTXCompilerTarget, h::UIn...
39 0 @LuxurySparse/src/arraymath.jl 29 *
2 0 @LuxurySparse/src/arraymath.jl 34 *(A::LuxurySparse.SDPermMatrix{ComplexF64, Int64, ...
2 0 @LuxurySparse/src/arraymath.jl 35 *
176 0 @YaoArrayRegister/src/instruct.jl 30 instruct!
894 1 @YaoArrayRegister/src/instruct.jl 40 instruct!
8 1 @YaoArrayRegister/src/register.jl 192 nactive
4 0 @YaoBase/src/utils/math.jl 349 logdi(x::Int64, d::Int64)
2 0 @YaoBase/src/utils/math.jl 350 logdi(x::Int64, d::Int64)
1 0 @YaoBase/src/utils/math.jl 351 logdi(x::Int64, d::Int64)
2 2 @YaoBlocks/src/abstract_block.jl 332 _check_size(r::ArrayReg{2, ComplexF64, CUDA.CuArra...
8 0 @YaoBlocks/src/abstract_block.jl 333 _check_size(r::ArrayReg{2, ComplexF64, CUDA.CuArra...
10 0 @YaoBlocks/src/abstract_block.jl 9 apply!
1147 0 @YaoBlocks/src/abstract_block.jl 10 apply!
66 2 @YaoBlocks/src/abstract_block.jl 101 mat_matchreg
620 0 @YaoBlocks/src/abstract_block.jl 41 |>
3299 0 ...locks/src/autodiff/apply_back.jl 171 apply_back(st::Tuple{ArrayReg{2, ComplexF64, CUDA....
3299 0 ...locks/src/autodiff/apply_back.jl 170 apply_back(st::Tuple{ArrayReg{2, ComplexF64, CUDA....
2686 1 ...locks/src/autodiff/apply_back.jl 42 apply_back!(st::Tuple{ArrayReg{2, ComplexF64, CUDA...
247 0 ...locks/src/autodiff/apply_back.jl 43 apply_back!(st::Tuple{ArrayReg{2, ComplexF64, CUDA...
205 0 ...locks/src/autodiff/apply_back.jl 44 apply_back!(st::Tuple{ArrayReg{2, ComplexF64, CUDA...
44 0 ...locks/src/autodiff/apply_back.jl 79 apply_back!(st::Tuple{ArrayReg{2, ComplexF64, CUDA...
68 0 ...locks/src/autodiff/apply_back.jl 80 apply_back!(st::Tuple{ArrayReg{2, ComplexF64, CUDA...
41 0 ...locks/src/autodiff/apply_back.jl 82 apply_back!(st::Tuple{ArrayReg{2, ComplexF64, CUDA...
1 0 ...locks/src/autodiff/apply_back.jl 122 apply_back!(st::Tuple{ArrayReg{2, ComplexF64, CUDA...
3299 7 ...locks/src/autodiff/apply_back.jl 123 apply_back!(st::Tuple{ArrayReg{2, ComplexF64, CUDA...
2490 0 ...locks/src/autodiff/apply_back.jl 156 backward_params!(st::Tuple{ArrayReg{2, ComplexF64,...
193 0 ...locks/src/autodiff/apply_back.jl 160 backward_params!(st::Tuple{ArrayReg{2, ComplexF64,...
68 0 ...f/outerproduct_and_projection.jl 54 outerprod(outδ::ArrayReg{2, ComplexF64, CUDA.CuArr...
3598 0 ...ocks/src/autodiff/specializes.jl 9 (::LinearAlgebra.Adjoint{Any, typeof(expect)})(op:...
295 0 ...ocks/src/autodiff/specializes.jl 14 expect_g(op::Add{2}, circuit::Pair{ArrayReg{2, Com...
1 0 ...ocks/src/autodiff/specializes.jl 15 expect_g(op::Add{2}, circuit::Pair{ArrayReg{2, Com...
3299 0 ...ocks/src/autodiff/specializes.jl 16 expect_g(op::Add{2}, circuit::Pair{ArrayReg{2, Com...
3 0 ...ocks/src/autodiff/specializes.jl 17 expect_g(op::Add{2}, circuit::Pair{ArrayReg{2, Com...
1 0 @YaoBlocks/src/composite/chain.jl 94 _apply!(r::ArrayReg{2, ComplexF64, CUDA.CuArray{Co...
295 8 @YaoBlocks/src/composite/chain.jl 95 _apply!(r::ArrayReg{2, ComplexF64, CUDA.CuArray{Co...
93 0 @YaoBlocks/src/composite/control.jl 141 _apply!(r::ArrayReg{2, ComplexF64, CUDA.CuArray{Co...
83 0 @YaoBlocks/src/composite/control.jl 141 _apply!
191 0 ...locks/src/composite/put_block.jl 83 _apply!(r::ArrayReg{2, ComplexF64, CUDA.CuArray{Co...
447 0 ...locks/src/composite/put_block.jl 83 _apply!
321 0 ...locks/src/composite/put_block.jl 93 _apply!
1 0 @YaoBlocks/src/composite/reduce.jl 32 (::YaoBlocks.var"#117#118"{ArrayReg{2, ComplexF64,...
1 0 @YaoBlocks/src/composite/reduce.jl 32 _apply!(r::ArrayReg{2, ComplexF64, CUDA.CuArray{Co...
1 0 @YaoBlocks/src/composite/reduce.jl 33 _apply!(r::ArrayReg{2, ComplexF64, CUDA.CuArray{Co...
1 0 ...Blocks/src/composite/repeated.jl 122 _apply!(r::ArrayReg{2, ComplexF64, CUDA.CuArray{Co...
64 1 ...s/src/primitive/rotation_gate.jl 87 mat(#unused#::Type{ComplexF64}, R::RotationGate{2,...
Total snapshots: 154589
Incorrect overloading of math functions
Line 19 in ac4d158
This will cause the CPU version dispatch to wrong place, since it overloads the angle in Base instead of CUDAnative
Type conversion interface
This package should provide a gpu function that do the following, like FluxML/Flux.jl#513
some_circuit |> gpu(Float32)
some_cricuit |> cpu(Float64)Make use GPUArrays interface
The kernel codes should be similar, but GPUArrays contains a fake GPU Array that can run on CPU which make it easier to test and it would just work on AMD GPUs (e.g for MacOS)
Getting WARNING about `YaoBase.batched_kron`
Haven't debugged to get an MWE to demonstrate the warning but it doesn't affect the code running. The full content of the warning is as follow:
WARNING: using YaoBase.batched_kron in module CuYao conflicts with an existing identifier.
Benchmark Results
9 qubit QCBM circuit with depth 8
Batched Performance
julia> @benchmark zero_state(n, 1000) |> cu |> $(qcbm.circuit) seconds = 2
BenchmarkTools.Trial:
memory estimate: 17.13 MiB
allocs estimate: 15549
--------------
minimum time: 9.164 ms (0.00% GC)
median time: 78.108 ms (2.70% GC)
mean time: 76.510 ms (7.66% GC)
maximum time: 105.105 ms (91.49% GC)
--------------
samples: 27
evals/sample: 1
julia> @benchmark zero_state(n, 1000) |> $(cqcbm.circuit) seconds = 2
BenchmarkTools.Trial:
memory estimate: 8.02 MiB
allocs estimate: 2478
--------------
minimum time: 868.712 ms (0.00% GC)
median time: 938.671 ms (0.00% GC)
mean time: 926.054 ms (0.08% GC)
maximum time: 970.780 ms (0.24% GC)
--------------
samples: 3
evals/sample: 1Single Run Performance
julia> @benchmark zero_state(n) |> cu |> $(qcbm.circuit) seconds = 2
BenchmarkTools.Trial:
memory estimate: 1.50 MiB
allocs estimate: 15293
--------------
minimum time: 3.071 ms (0.00% GC)
median time: 3.295 ms (0.00% GC)
mean time: 3.750 ms (8.93% GC)
maximum time: 10.285 ms (54.88% GC)
--------------
samples: 531
evals/sample: 1
julia> @benchmark zero_state(n) |> $(cqcbm.circuit) seconds = 2
BenchmarkTools.Trial:
memory estimate: 234.52 KiB
allocs estimate: 2781
--------------
minimum time: 217.369 μs (0.00% GC)
median time: 222.433 μs (0.00% GC)
mean time: 292.978 μs (18.22% GC)
maximum time: 8.223 ms (96.29% GC)
--------------
samples: 6768
evals/sample: 1Platform
CPU:
Intel(R) Core(TM) i5-7200U CPU @ 2.50GHz
GPU:
Nvidia GeForce 940MX
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Tencent
China tencent open source team.