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If an outfeed instruction has a config, schedule it early. If an infeed instruction has a config, schedule it late.

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PiperOrigin-RevId: 314666537
Change-Id: Ia3c6e981e1c6926a882b82a565b2ca04891f79f6
This commit is contained in:
Dimitris Vardoulakis 2020-06-03 22:08:39 -07:00 committed by TensorFlower Gardener
parent 0aca2efde5
commit b7531bd3c7
1 changed files with 13 additions and 1 deletions

14
tensorflow/compiler/xla/service/hlo_memory_scheduler.cc
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@ -27,6 +27,7 @@ limitations under the License.
#include "tensorflow/compiler/xla/service/dfs_hlo_visitor_with_default.h"
#include "tensorflow/compiler/xla/service/heap_simulator.h"
#include "tensorflow/compiler/xla/service/hlo_computation.h"
#include "tensorflow/compiler/xla/service/hlo_opcode.h"
#include "tensorflow/compiler/xla/service/hlo_schedule.h"
#include "tensorflow/compiler/xla/service/tuple_points_to_analysis.h"
#include "tensorflow/compiler/xla/shape_util.h"
@ -211,6 +212,18 @@ class ListScheduler {
// improve accounting for subcomputation memory (b/65409243).
int64 BytesFreedIfScheduled(const ReadyListEntry& entry) {
auto instruction = entry.instruction;
auto opcode = instruction->opcode();
// Scheduling the outfeed early and the infeed late gives more time to the
// communicating processor to do its work.
if (opcode == HloOpcode::kOutfeed &&
!instruction->outfeed_config().empty()) {
return INT_MAX;
}
if (opcode == HloOpcode::kInfeed && !instruction->infeed_config().empty()) {
return INT_MIN;
}
int64 freed_bytes = 0;
for (const auto& kv : entry.used_buffer_unscheduled_use_counts) {
auto buffer = kv->first;
@ -232,7 +245,6 @@ class ListScheduler {
}
}
int64 bytes_defined;
auto opcode = instruction->opcode();
if (max_subcomputation_bytes > 0 &&
(opcode == HloOpcode::kWhile || opcode == HloOpcode::kCall ||
opcode == HloOpcode::kConditional)) {