Souper requires an `i1` condition value, we don't and will implicitly check
against 0. We were truncating conditions but should actually be doing the
comparison against `0`.
We have some operations defined on DataFlowGraph purely to work around borrow-checker issues with InstructionData and other data on DataFlowGraph. Part of the problem is that indexing the DFG directly hides the fact that we're only indexing the insts field of the DFG.
This PR makes the insts field of the DFG public, but wraps it in a newtype that only allows indexing. This means that the borrow checker is better able to tell when operations on memory held by the DFG won't conflict, which comes up frequently when mutating ValueLists held by InstructionData.
Remove the boolean types from cranelift, and the associated instructions breduce, bextend, bconst, and bint. Standardize on using 1/0 for the return value from instructions that produce scalar boolean results, and -1/0 for boolean vector elements.
Fixes#3205
Co-authored-by: Afonso Bordado <afonso360@users.noreply.github.com>
Co-authored-by: Ulrich Weigand <ulrich.weigand@de.ibm.com>
Co-authored-by: Chris Fallin <chris@cfallin.org>
Move from passing and returning u8 and u16 values to u32 in many of
the functions. This removes a number of type conversions and gives
a small compilation time speedup, around ~0.7% on my aarch64 machine.
Copyright (c) 2022, Arm Limited.
It turns out that Souper does not allow a constant to be assigned to a variable,
they may only be used as operands. The 2.0.0 version of the `souper-ir` crate
correctly reflects this. In the `cranelift_codegen::souper_harvest` module, we
need to modify our Souper IR harvester so that it delays converting `iconst` and
`bconst` into Souper IR until their values are used as operands. Finally, some
unit tests in the `peepmatic-souper` crate need some small updates as well.
Given a clif function, harvest all its integer subexpressions, so that they can
be fed into [Souper](https://github.com/google/souper) as candidates for
superoptimization. For some of these candidates, Souper will successfully
synthesize a right-hand side that is equivalent but has lower cost than the
left-hand side. Then, we can combine these left- and right-hand sides into a
complete optimization, and add it to our peephole passes.
To harvest the expression that produced a given value `x`, we do a post-order
traversal of the dataflow graph starting from `x`. As we do this traversal, we
maintain a map from clif values to their translated Souper values. We stop
traversing when we reach anything that can't be translated into Souper IR: a
memory load, a float-to-int conversion, a block parameter, etc. For values
produced by these instructions, we create a Souper `var`, which is an input
variable to the optimization. For instructions that have a direct mapping into
Souper IR, we get the Souper version of each of its operands and then create the
Souper version of the instruction itself. It should now be clear why we do a
post-order traversal: we need an instruction's translated operands in order to
translate the instruction itself. Once this instruction is translated, we update
the clif-to-souper map with this new translation so that any other instruction
that uses this result as an operand has access to the translated value. When the
traversal is complete we return the translation of `x` as the root of left-hand
side candidate.
