Remove threading #186
Remove threading #186
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Pull Request Test Coverage Report for Build 3577834801
💛 - Coveralls |
src/Interfaces/dictvectors.jl
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| """ | ||
| fciqmc_step!(working_memory, curr_dv, prev_dv, ham, shift, dτ) -> stat_names, stats, working_memory, curr_dv, prev_dv | ||
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| Perform a single matrix(/operator)-vector multiplication: | ||
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| ```math | ||
| v^{(n + 1)} = [1 - dτ(\\hat{H} - S)]⋅v^{(n)} , | ||
| ``` | ||
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| where `Ĥ == ham` and `S == shift`. | ||
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| Whether the operation is performed in stochastic, semistochastic, or determistic way is | ||
| controlled by the trait `StochasticStyle(w)`. See [`StochasticStyle`](@ref). | ||
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| Returns the step stats generated by the `StochasticStyle`, the current and previous vectors | ||
| and the working memory. | ||
| """ |
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This docstring (same for working_memory and sort_into_targets!) is no longer picked up by Documenter. It used to live in the documentation web page under API>Rimu.
Why do we need these functions in Interfaces?
src/Interfaces/dictvectors.jl
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| # Now, working_memory holds the new values and curr_dv holds previous values. | ||
| # Swap curr and prev, then sort the wm into the (new) curr. | ||
| curr_dv, prev_dv = (prev_dv, curr_dv) | ||
| curr_dv, working_memory, stats = sort_into_targets!(curr_dv, working_memory, stats) |
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I like this idea. It is elegant in avoiding the copying when not needed. Care must be taken to use the returned vectors for further work, though, so maybe we should put a warning into the docstring.
Note that also sort_into_targets! might swap.
| function apply_memory_noise!(w::Union{AbstractArray{T},AbstractDVec{K,T}}, | ||
| v, shift, dτ, pnorm, m | ||
| ) where {K,T<:Real} | ||
| function apply_memory_noise!(w, v, shift, dτ, pnorm, m) | ||
| apply_memory_noise!(StochasticStyle(w), w, v, real(shift), dτ, real(pnorm), m) | ||
| end | ||
| # only use real part of the shift and norm if the coefficients are real | ||
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| # otherwise, pass on complex shift in generic method | ||
| function apply_memory_noise!(w::Union{AbstractArray,AbstractDVec}, args...) | ||
| apply_memory_noise!(StochasticStyle(w), w, args...) | ||
| end | ||
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| function apply_memory_noise!(ws::NTuple, args...) | ||
| apply_memory_noise!(StochasticStyle(first(ws)), ws, args...) | ||
| end |
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This function is now called after sort_into_targets! on the full vector (not localpart). These methods don't work with MPIData because it's not a vector or dvec. I also don't understand how you could get into a situation where shift and norm are complex, but the vector is real (which is what the first method handles).
src/Interfaces/dictvectors.jl
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| working_memory(dv) = similar(localpart(dv)) | ||
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| """ | ||
| fciqmc_step!(working_memory, curr_dv, prev_dv, ham, shift, dτ) -> stat_names, stats, working_memory, curr_dv, prev_dv |
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| fciqmc_step!(working_memory, curr_dv, prev_dv, ham, shift, dτ) -> stat_names, stats, working_memory, curr_dv, prev_dv | |
| fciqmc_step!(v2, working_memory, v, ham, shift, dτ) -> curr_v, working_memory, prev_v, stat_names, stats |
Here is a just a thought for the calling signature. Only the first two arguments are mutated. The v argument is not mutated. Currently a reference is returned as prev_v, but this could be skipped (and assigning prev_v could be delegated to the calling code).
The docstring would have to explain that v^{(n)} == v and a reference to it is passed back as prev_v, that v^{(n+1)} == curr_v, and that v2 and working_memory have to be suitable containers (with v2 having the same type as v) that will be mutated and references could change.
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Right, that makes sense. Perhaps in this signature, curr_dv and prev_dv could be called source and target as well.
src/lomc.jl
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| hamiltonian::H | ||
| v::V # vector | ||
| pv::V # previous vector. | ||
| w::W # working memory. Maybe working memories could be shared among replicas? |
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| w::W # working memory. Maybe working memories could be shared among replicas? | |
| wm::W # working memory. Maybe working memories could be shared among replicas? |
I would suggest renaming to wm as this is what the keyword argument in lomc! is called. It also makes the function more apparent.
| If you want FCIQMC runs to be reproducible, make sure to seed the RNG with | ||
| [Random.seed!](https://docs.julialang.org/en/v1/stdlib/Random/#Random.seed!) and to use [`lomc!`](@ref) in single-threaded mode by passing it the `threading=false` keyword argument. | ||
| [Random.seed!](https://docs.julialang.org/en/v1/stdlib/Random/#Random.seed!). |
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This will be true in the future when threading is fixed, but it won't be with this update?
mtsch
dismissed stale reviews from joachimbrand and christofbradly
via
4f89c97
Co-authored-by: Joachim Brand <j.brand@massey.ac.nz>
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