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See JuliaLang/julia#55076 for details
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Can test locally by typing |
| root::GraphNode{T}, | ||
| cX::AbstractMatrix{T}, | ||
| operators::OperatorEnum, | ||
| loopVectorization::Val{true} |
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| loopVectorization::Val{true} | |
| ::EvalOptions{true} |
| op::UInt8 # (Possibly undefined) If operator, this is the index of the operator in the degree-specific operator enum | ||
| children::NTuple{D,Base.RefValue{GraphNode{T,D}}} # Children nodes | ||
| visited::Bool # search accounting, initialised to false | ||
| cache::AbstractArray{T} |
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Since this might not be backwards compatible, I wonder if an alternative would be to convert to a val type (T) where instead of val::T, you have val::Tuple{T,Bool,Array{T,1}}? Then you wouldn’t need to modify the GraphNode itself.
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Also see https://docs.julialang.org/en/v1/manual/performance-tips/#man-performance-abstract-container regarding the |
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Graph evaluator caching component from former PR
Graph evaluator caching
The GraphNode struct now has an additional property, the AbstractArray cache, not initialised during object creation.
This enables the result of each node evaluation to be stored and retrieved without the need for a dictionary lookup.
A GraphNode can now also have the constant property set to true during evaluation if it is an operator node with constant operand nodes. In such a case the val property will also be set to the result of the single operation required. This behaviour won't occur in sufficiently optimised expressions, as a subexpression consisting of operators with constant operand nodes could be replaced with a single constant node. This doesn't meaningfully mutate the expression during the evaluation, as the constant property is otherwise meaningless for nodes with degree >0.
In terms of the evaluator itself, there are two implemented versions: one using Base.map, and one using LoopVectorization.vmapnt which is used when the LoopVectorization package is loaded. Some rough tests I did found that, on a graph with no shared subexpressions, the graph evaluator takes 1.4x as long as the corresponding (with or without LoopVectorization) tree evaluator. I might do some more work on reducing that, one method would be to quickly identify whether shared subexpressions exist in the expression and choose a corresponding evaluator. The relative performance of the graph evaluator operating on an expression with shared subexpressions is entirely dependent on the number and size of the shared subexpressions but has a theoretically unbounded performance improvement.