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feat: add shard execution workflow #1557
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427a434
refactor: bring changes from nx_iree
polvalente 3a24374
fix: optional function support
polvalente f49daab
test: test anonymous functions
polvalente aa2ffe7
feat: start producing shard execution processes
polvalente f6eed5a
wip: make code compile
polvalente 6315546
wip: shard execution implementation
polvalente 5a5fbaf
refactor: use Registry and :erpc.multicall for process registration
polvalente eecbb28
fix: use local get function
polvalente 553a5b8
refactor: use uniform sharding only
polvalente 14e558f
feat: sharding concurrent execution proof of concept working
polvalente fafaa0d
feat: minimal e2e example of shard execution working
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3 changes: 3 additions & 0 deletions
3
nx/lib/nx/defn/sharding_compiler/passes/graph_splitter/stage.ex
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,3 @@ | ||
defmodule Nx.Defn.ShardingCompiler.Passes.GraphSplitter.Stage do | ||
defstruct [:id, :category, :expr, :arguments, :argument_sources] | ||
end |
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I'm not sure we want to have this here, actually.
In fact, I think we might actually want to go with gen_stage for the execution, since the whole "chain of processes producing data to one another" smells a lot like gen_stage.
Thoughts?
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We should talk about it but I doubt GenStage will be helpful here. One of the biggest pitfalls in GenStage is that people move data around too much, when they should not. It is cheaper to move computations than to move data.
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Plus the whole demand approach is unnecessary here. Here is either pending or done (like a promise), no?