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implementation: started writing interpreter section; finished CPU-side part; also found error with interpreter
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Daniel
2025-04-27 13:17:35 +02:00
parent e571fa5bd6
commit 101b13e7e7
8 changed files with 278 additions and 57 deletions
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10
package/src/ExpressionExecutorCuda.jl
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@ -26,7 +26,10 @@ function interpret_gpu(exprs::Vector{Expr}, X::Matrix{Float32}, p::Vector{Vector
ncols = size(X, 2)
results = Matrix{Float32}(undef, ncols, length(exprs))
# TODO: create CuArray for variables here already, as they never change
# TODO: create CuArray for variables here already, as they never change
# could/should be done even before calling this, but I guess it would be diminishing returns
# TODO: test how this would impact performance, if it gets faster, adapt implementation section
# TODO: create CuArray for expressions here already. They also do not change over the course of parameter optimisation and therefore a lot of unnecessary calls to expr_to_postfix can be save (even though a cache is used, this should still be faster)
for i in 1:repetitions # Simulate parameter tuning -> local search (X remains the same, p gets changed in small steps and must be performed sequentially, which it is with this impl)
results = Interpreter.interpret(exprs, X, p)
@ -41,7 +44,10 @@ function evaluate_gpu(exprs::Vector{Expr}, X::Matrix{Float32}, p::Vector{Vector{
ncols = size(X, 2)
results = Matrix{Float32}(undef, ncols, length(exprs))
# TODO: create CuArray for variables here already, as they never change
# TODO: create CuArray for variables here already, as they never change
# could/should be done even before calling this, but I guess it would be diminishing returns
# TODO: test how this would impact performance, if it gets faster, adapt implementation section
# TODO: create CuArray for expressions here already. They also do not change over the course of parameter optimisation and therefore a lot of unnecessary calls to expr_to_postfix can be save (even though a cache is used, this should still be faster)
for i in 1:repetitions # Simulate parameter tuning -> local search (X remains the same, p gets changed in small steps and must be performed sequentially, which it is with this impl)
results = Transpiler.evaluate(exprs, X, p)