gh-112320: Implement on-trace confidence tracking for branches (#112321)

We track the confidence as a scaled int.
This commit is contained in:
Guido van Rossum 2023-12-12 13:43:08 -08:00 committed by GitHub
parent dfaa9e060b
commit 7316dfb0eb
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6 changed files with 56 additions and 3 deletions

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@ -114,6 +114,7 @@ typedef struct _optimization_stats {
uint64_t trace_too_short;
uint64_t inner_loop;
uint64_t recursive_call;
uint64_t low_confidence;
UOpStats opcode[512];
uint64_t unsupported_opcode[256];
uint64_t trace_length_hist[_Py_UOP_HIST_SIZE];

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@ -2985,6 +2985,37 @@ def testfunc(n, m):
uops = {opname for opname, _, _ in ex}
self.assertIn("_FOR_ITER_TIER_TWO", uops)
def test_confidence_score(self):
def testfunc(n):
bits = 0
for i in range(n):
if i & 0x01:
bits += 1
if i & 0x02:
bits += 1
if i&0x04:
bits += 1
if i&0x08:
bits += 1
if i&0x10:
bits += 1
if i&0x20:
bits += 1
return bits
opt = _testinternalcapi.get_uop_optimizer()
with temporary_optimizer(opt):
x = testfunc(20)
self.assertEqual(x, 40)
ex = get_first_executor(testfunc)
self.assertIsNotNone(ex)
ops = [opname for opname, _, _ in ex]
count = ops.count("_GUARD_IS_TRUE_POP")
# Because Each 'if' halves the score, the second branch is
# too much already.
self.assertEqual(count, 1)
@unittest.skipUnless(support.Py_GIL_DISABLED, 'need Py_GIL_DISABLED')
class TestPyThreadId(unittest.TestCase):

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@ -0,0 +1,4 @@
The Tier 2 translator now tracks the confidence level for staying "on trace"
(i.e. not exiting back to the Tier 1 interpreter) for branch instructions
based on the number of bits set in the branch "counter". Trace translation
ends when the confidence drops below 1/3rd.

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@ -409,6 +409,9 @@ BRANCH_TO_GUARD[4][2] = {
#define TRACE_STACK_SIZE 5
#define CONFIDENCE_RANGE 1000
#define CONFIDENCE_CUTOFF 333
/* Returns 1 on success,
* 0 if it failed to produce a worthwhile trace,
* and -1 on an error.
@ -431,6 +434,7 @@ translate_bytecode_to_trace(
_Py_CODEUNIT *instr;
} trace_stack[TRACE_STACK_SIZE];
int trace_stack_depth = 0;
int confidence = CONFIDENCE_RANGE; // Adjusted by branch instructions
#ifdef Py_DEBUG
char *python_lltrace = Py_GETENV("PYTHON_LLTRACE");
@ -513,7 +517,6 @@ translate_bytecode_to_trace(
uint32_t oparg = instr->op.arg;
uint32_t extras = 0;
if (opcode == EXTENDED_ARG) {
instr++;
extras += 1;
@ -543,11 +546,22 @@ translate_bytecode_to_trace(
int counter = instr[1].cache;
int bitcount = _Py_popcount32(counter);
int jump_likely = bitcount > 8;
if (jump_likely) {
confidence = confidence * bitcount / 16;
}
else {
confidence = confidence * (16 - bitcount) / 16;
}
if (confidence < CONFIDENCE_CUTOFF) {
DPRINTF(2, "Confidence too low (%d)\n", confidence);
OPT_STAT_INC(low_confidence);
goto done;
}
uint32_t uopcode = BRANCH_TO_GUARD[opcode - POP_JUMP_IF_FALSE][jump_likely];
_Py_CODEUNIT *next_instr = instr + 1 + _PyOpcode_Caches[_PyOpcode_Deopt[opcode]];
DPRINTF(4, "%s(%d): counter=%x, bitcount=%d, likely=%d, uopcode=%s\n",
DPRINTF(2, "%s(%d): counter=%x, bitcount=%d, likely=%d, confidence=%d, uopcode=%s\n",
_PyUOpName(opcode), oparg,
counter, bitcount, jump_likely, _PyUOpName(uopcode));
counter, bitcount, jump_likely, confidence, _PyUOpName(uopcode));
ADD_TO_TRACE(uopcode, max_length, 0, target);
if (jump_likely) {
_Py_CODEUNIT *target_instr = next_instr + oparg;

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@ -233,6 +233,7 @@ print_optimization_stats(FILE *out, OptimizationStats *stats)
fprintf(out, "Optimization trace too short: %" PRIu64 "\n", stats->trace_too_short);
fprintf(out, "Optimization inner loop: %" PRIu64 "\n", stats->inner_loop);
fprintf(out, "Optimization recursive call: %" PRIu64 "\n", stats->recursive_call);
fprintf(out, "Optimization low confidence: %" PRIu64 "\n", stats->low_confidence);
print_histogram(out, "Trace length", stats->trace_length_hist);
print_histogram(out, "Trace run length", stats->trace_run_length_hist);

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@ -386,6 +386,7 @@ def get_optimization_stats(self) -> dict[str, tuple[int, int | None]]:
trace_too_short = self._data["Optimization trace too short"]
inner_loop = self._data["Optimization inner loop"]
recursive_call = self._data["Optimization recursive call"]
low_confidence = self._data["Optimization low confidence"]
return {
"Optimization attempts": (attempts, None),
@ -396,6 +397,7 @@ def get_optimization_stats(self) -> dict[str, tuple[int, int | None]]:
"Trace too short": (trace_too_short, attempts),
"Inner loop found": (inner_loop, attempts),
"Recursive call": (recursive_call, attempts),
"Low confidence": (low_confidence, attempts),
"Traces executed": (executed, None),
"Uops executed": (uops, executed),
}