Side Effects & Speculation
This document outlines how MLIR models side effects and how speculation works in MLIR.
This rationale only applies to operations used in CFG regions. Side effect modeling in graph regions is TBD.
[TOC]
Overview ¶
Many MLIR operations don’t exhibit any behavior other than consuming and producing SSA values. These operations can be reordered with other operations as long as they obey SSA dominance requirements and can be eliminated or even introduced (e.g. for rematerialization) as needed.
However, a subset of MLIR operations have implicit behavior than isn’t reflected in their SSA data-flow semantics. These operations need special handing, and cannot be reordered, eliminated or introduced without additional analysis.
This doc introduces a categorization of these operations and shows how these operations are modeled in MLIR.
Categorization ¶
Operations with implicit behaviors can be broadly categorized as follows:
- Operations with memory effects. These operations read from and write to some
mutable system resource, e.g. the heap, the stack, HW registers, the console.
They may also interact with the heap in other ways, like by allocating and
freeing memory. E.g. standard memory reads and writes,
printf
(which can be modeled as “writing” to the console and reading from the input buffers). - Operations with undefined behavior. These operations are not defined on certain inputs or in some situations – we do not specify what happens when such illegal inputs are passed, and instead say that behavior is undefined and can assume it does not happen. In practice, in such cases these ops may do anything from producing garbage results to crashing the program or corrupting memory. E.g. integer division which has UB when dividing by zero, loading from a pointer that has been freed.
- Operations that don’t terminate. E.g. an
scf.while
where the condition is always true. - Operations with non-local control flow. These operations may pop their
current frame of execution and return directly to an older frame. E.g.
longjmp
, operations that throw exceptions.
Finally, a given operation may have a combination of the above implicit behaviors.
Modeling ¶
Modeling these behaviors has to walk a fine line – we need to empower more complicated passes to reason about the nuances of such behaviors while simultaneously not overburdening simple passes that only need a coarse grained “can this op be freely moved” query.
MLIR has two op interfaces to represent these implicit behaviors:
- The
MemoryEffectsOpInterface
op interface is used to track memory effects. - The
ConditionallySpeculatable
op interface is used to track undefined behavior and infinite loops.
Both of these are op interfaces which means operations can dynamically introspect themselves (e.g. by checking input types or attributes) to infer what memory effects they have and whether they are speculatable.
We don’t have proper modeling yet to fully capture non-local control flow semantics.
When adding a new op, ask:
- Does it read from or write to the heap or stack? It should probably implement
MemoryEffectsOpInterface
. - Does it have side effects that must be preserved, like a volatile store or a
syscall? It should probably implement
MemoryEffectsOpInterface
and model the effect as a read from or write to an abstractResource
. Please start an RFC if your operation has a novel side effect that cannot be adequately captured byMemoryEffectsOpInterface
. - Is it well defined in all inputs or does it assume certain runtime
restrictions on its inputs, e.g. the pointer operand must point to valid
memory? It should probably implement
ConditionallySpeculatable
. - Can it infinitely loop on certain inputs? It should probably implement
ConditionallySpeculatable
. - Does it have non-local control flow (e.g.
longjmp
)? We don’t have proper modeling for these yet, patches welcome! - Is your operation free of side effects and can be freely hoisted, introduced
and eliminated? It should probably be marked
Pure
. (TODO: revisit this name since it has overloaded meanings in C++.)