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Ordered effects currently are not allowed in multi-device computations. This is too restrictive sometimes, e.g., `io_callback(ordered=True)` uses maximal sharding on one device and the callback would be issued only once even in multi-device computations. Here we add support for ordered shardable effects, which behave like ordered effects except they are allowed in SPMD computations. Currently, only `callback.IOOrderedEffect` is declared shardable. In general, if the sharding of the side-effecting operation is not maximal, then such effects would appear in a partial order, with effects appearing ordered by program point and unordered among the different devices at a given program point. We also generalize the mechanism for tracking runtime tokens and token buffers to work with multiple devices. PiperOrigin-RevId: 566242557
121 lines
4.6 KiB
Python
121 lines
4.6 KiB
Python
# Copyright 2023 The JAX Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""JAX effects.
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JAX uses effects to describe computations that may have side-effects. Effects
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are associated with JAX primitive instances and Jaxprs.
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A primitive instance with an effect will be protected from dead-code elimination
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even if its result is unused.
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A special class of effects are the **ordered** effects
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(members of `effects.ordered_effects`).
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The lowering of a computation with ordered effects will have one additional
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input and one additional output for each ordered effect. These appear before
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the regular inputs/outputs, and are of type `i1[0]`. These tokens
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are threaded through the instructions with ordered effects to ensure that the
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compiler will not eliminate, replicate, or reordered the corresponding
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instructions.
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To ensure the ordering across multiple computations we maintain a
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per-thread set of the tokens returned by the last dispatched computation. There
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is one token per ordered effect, and it may be sharded over the devices
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used by the last dispatched computation. Upon dispatching a
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new computation with ordered effects we take the current token, we shard it
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on the devices for the computation to be dispatched and we pass it as an input.
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Then we update the current token to refer to the token output of
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the dispatched computation.
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When we have ordered effects, we also use the current token to implement
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`jax.barrier` which waits until the current tokens are ready.
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The implementation of `jax.barrier` for unordered effects is a bit different,
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because for these effects we do not thread tokens in and out of dispatched
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computation. Instead, we use a `RuntimeToken`, which is an object returned when
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dispatching a computation and on which we can block until is ready. We store
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for each thread the `RuntimeToken` returned by the last dispatched computation.
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For more details, see the design note:
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https://jax.readthedocs.io/en/latest/jep/10657-sequencing-effects.html.
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"""
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from __future__ import annotations
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from collections.abc import Iterable
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from typing import Any
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class Effect:
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"""A generic side-effect."""
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Effects = set[Effect]
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class JaxprInputEffect(Effect):
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"""A side-effect associated with the input of a jaxpr.
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Note that the `input_index` includes constvars.
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"""
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def __init__(self, input_index: Any):
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self.input_index = input_index
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def replace(self, *, input_index: Any | None = None):
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if input_index is None:
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input_index = self.input_index
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return self.__class__(input_index)
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def __eq__(self, other):
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if not isinstance(other, JaxprInputEffect):
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return NotImplemented
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return self.input_index == other.input_index
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def __hash__(self):
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return hash((self.__class__, self.input_index))
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def __repr__(self):
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return f"{self.__class__.__name__}({self.input_index})"
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class EffectTypeSet:
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def __init__(self):
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self._effect_types: set[type[Effect]] = set()
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def add_type(self, effect_type: type[Effect]):
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self._effect_types.add(effect_type)
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def contains(self, eff: Effect) -> bool:
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return any(isinstance(eff, eff_type) for eff_type in self._effect_types)
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def filter_in(self, effects: Iterable[Effect]) -> list[Effect]:
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return [eff for eff in effects if self.contains(eff)]
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def filter_not_in(self, effects: Iterable[Effect]) -> list[Effect]:
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return [eff for eff in effects if not self.contains(eff)]
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no_effects: Effects = set()
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ordered_effects: EffectTypeSet = EffectTypeSet()
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# By default, ordered effects are not allowed in multi-device computations,
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# because we cannot ensure a total order. Optionally, an effect can be
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# declared as shardable, which means that effects will appear in program order
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# but for a given program point we may see several side effects on the
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# participating devices, and there is no guarantee of their relative ordering.
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shardable_ordered_effects: EffectTypeSet = EffectTypeSet()
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lowerable_effects: EffectTypeSet = EffectTypeSet()
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control_flow_allowed_effects: EffectTypeSet = EffectTypeSet()
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custom_derivatives_allowed_effects: EffectTypeSet = EffectTypeSet()
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remat_allowed_effects: EffectTypeSet = EffectTypeSet()
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