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Transposed storage #30
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Codecov Report
@@ Coverage Diff @@
## master #30 +/- ##
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+ Coverage 80.68% 81.1% +0.41%
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Files 8 8
Lines 497 508 +11
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+ Hits 401 412 +11
Misses 96 96
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Yes, I can check if this works better. I'm actually trying out my own version as well! |
Merged
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Ready to merge? |
Benchmark Report for YaoArrayRegisterJob Properties
ResultsA ratio greater than
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoTargetBaseline |
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@GiggleLiu it seems that there are some regressions, do you have time to investigate them? |
Roger-luo
reviewed
Sep 18, 2019
src/instruct.jl
Outdated
| end | ||
| operator = sort_unitary(operator, locs) | ||
| locs_raw, ic = _prepare_instruct(state, operator, locs, control_locs, control_bits) | ||
| return _instruct!(state, autostatic(operator), locs_raw, ic) |
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I think you need to transpose the operator and state for general case in order to make memory contiguous for BLAS?
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state is transposed, transposing the operator is not nessesary. After all, we don't have BLAS...
it seems there are some performance regression against ["specialized", "single qubit multi control", "(\"T\", 24, 8)"]can you also run the benchmark on your laptop? some of the regression might just be noise. |
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batched register benchmarks are not defined yet, I'll do that later, meanwhile you can investigate the regression on single batch. |
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On Delta 102, the 1.5 time regresion looks not true # master branch
julia> results = run(SUITE["matrices"]["in-contiguous"]["ordered"][(1, "Complex{Float64}", "PermMatrix{Complex{Float64},Int64,Array{Complex{Float64},1},Array{Int64,1}}")])
BenchmarkTools.Trial:
memory estimate: 288 bytes
allocs estimate: 4
--------------
minimum time: 1.310 μs (0.00% GC)
median time: 1.740 μs (0.00% GC)
mean time: 1.622 μs (0.00% GC)
maximum time: 17.520 μs (0.00% GC)
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samples: 10000
evals/sample: 1
# this branch
julia> results = run(SUITE["matrices"]["in-contiguous"]["ordered"][(1, "Complex{Float64}", "PermMatrix{Complex{Float64},Int64,Array{Complex{Float64},1},Array{Int64,1}}")])
BenchmarkTools.Trial:
memory estimate: 288 bytes
allocs estimate: 4
--------------
minimum time: 1.135 μs (0.00% GC)
median time: 1.188 μs (0.00% GC)
mean time: 13.748 μs (0.00% GC)
maximum time: 125.430 ms (0.00% GC)
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samples: 10000
evals/sample: 1 |
Roger-luo
reviewed
Oct 6, 2019
| else | ||
| raw = zeros(T, nbatch, 1<<total) | ||
| raw[:,Int(bit_config)+1] .= 1 | ||
| raw = transpose(raw) |
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should copy here? since transpose is lazy.
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and state will always return a transposeed version so state(r) * mat still works in YaoBlocks? and add a new function storage to return the raw storage?
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we need Tranpose wrapper here to create a effective row major array.
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This PR currently breaks Test Summary: | Pass Error Total
test composite block | 258 7 265
test chain | 62 62
test kron | 44 44
test control | 28 28
test put | 26 7 33
construct | 1 1
apply! | 7 5 12
test swap gate | 17 17
rotation gate | 1 2 3
test repeated | 7 7
test concentrate | 11 11
test tag | 59 59
test pauli string | 15 15
test single block chsubblocks | 4 4
ERROR: LoadError: Some tests did not pass: 258 passed, 0 failed, 7 errored, 0 broken.
in expression starting at /Users/roger/.julia/dev/YaoBlocks/test/runtests.jl:7@GiggleLiu do you have time to fix it? |
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reverted @Roger-luo |
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Tranposed storage are more batch friendly, with better performance.
All changes are included in this commit: 86d74bd and 17ec5df
@Roger-luo Could you please do benchmark on this branch, and see how it work?