You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
116 lines
4.2 KiB
Python
116 lines
4.2 KiB
Python
from dataclasses import dataclass
|
|
from typing import Dict, List, Optional, Tuple
|
|
|
|
import numpy as np
|
|
from hivemind import PeerID, get_logger
|
|
|
|
from petals.data_structures import RemoteModuleInfo, ServerState
|
|
|
|
__all__ = ["choose_best_blocks", "should_choose_other_blocks"]
|
|
|
|
logger = get_logger(__file__)
|
|
|
|
|
|
@dataclass
|
|
class Span:
|
|
start: int
|
|
end: int
|
|
throughput: float
|
|
|
|
@property
|
|
def length(self):
|
|
return self.end - self.start
|
|
|
|
def move_to(self, new_start: int) -> None:
|
|
self.start, self.end = new_start, new_start + self.length
|
|
|
|
|
|
def _compute_spans(module_infos: List[Optional[RemoteModuleInfo]]) -> Tuple[Dict[PeerID, Span], np.ndarray]:
|
|
spans = {}
|
|
throughputs = np.zeros(len(module_infos))
|
|
for block, module in enumerate(module_infos):
|
|
if module is None:
|
|
continue
|
|
|
|
# We sort servers here to ensure that we get exactly the same throughputs for a given set of servers.
|
|
# If the order were not defined, we would get slightly different values due to floating point errors,
|
|
# which may cause excess block replacements.
|
|
for peer_id, server in sorted(module.servers.items()):
|
|
if server.state == ServerState.OFFLINE:
|
|
continue
|
|
|
|
if peer_id in spans:
|
|
spans[peer_id].start = min(spans[peer_id].start, block)
|
|
spans[peer_id].end = max(spans[peer_id].start, block + 1)
|
|
else:
|
|
spans[peer_id] = Span(start=block, end=block + 1, throughput=server.throughput)
|
|
|
|
throughputs[block] += server.throughput
|
|
|
|
return spans, throughputs
|
|
|
|
|
|
def _choose_best_start(throughputs: np.ndarray, num_blocks: int) -> int:
|
|
options = ((sorted(throughputs[i : i + num_blocks]), i) for i in range(0, len(throughputs) - num_blocks + 1))
|
|
return min(options)[-1]
|
|
|
|
|
|
def choose_best_blocks(num_blocks: int, module_infos: List[Optional[RemoteModuleInfo]]) -> List[int]:
|
|
_, throughputs = _compute_spans(module_infos)
|
|
start = _choose_best_start(throughputs, num_blocks)
|
|
return list(range(start, start + num_blocks))
|
|
|
|
|
|
def should_choose_other_blocks(
|
|
local_peer_id: PeerID, module_infos: List[Optional[RemoteModuleInfo]], balance_quality: float
|
|
) -> bool:
|
|
if balance_quality > 1.0:
|
|
return True # Forces rebalancing on each check (may be used for debugging purposes)
|
|
|
|
spans, throughputs = _compute_spans(module_infos)
|
|
initial_throughput = throughputs.min()
|
|
eps = 1e-3
|
|
|
|
assert local_peer_id in spans, "Span served by this server is not present in the DHT"
|
|
local_span = spans[local_peer_id]
|
|
throughputs[local_span.start : local_span.end] -= local_span.throughput * (1 + eps)
|
|
# Without (1 + eps) here, we would sometimes subtract a value slightly less than local_span.throughput
|
|
# due to the floating point error, which would cause excess block replacements.
|
|
# Also, subtracting local_span.throughput * (1 + eps) makes _choose_best_start() prefer
|
|
# the previous server position in case of other things being almost equal.
|
|
|
|
new_start = _choose_best_start(throughputs, local_span.length)
|
|
if local_span.start == new_start:
|
|
return False # This server is on its best place already
|
|
|
|
throughputs[local_span.start : local_span.end] += local_span.throughput * eps
|
|
local_span.move_to(new_start)
|
|
throughputs[local_span.start : local_span.end] += local_span.throughput
|
|
|
|
moved = True
|
|
while moved:
|
|
servers = list(spans.keys())
|
|
np.random.shuffle(servers)
|
|
|
|
moved = False
|
|
for peer_id in servers:
|
|
span = spans[peer_id]
|
|
throughputs[span.start : span.end] -= span.throughput * (1 + eps)
|
|
|
|
new_start = _choose_best_start(throughputs, span.length)
|
|
|
|
throughputs[span.start : span.end] += span.throughput * eps
|
|
if span.start != new_start:
|
|
span.move_to(new_start)
|
|
moved = True
|
|
throughputs[span.start : span.end] += span.throughput
|
|
|
|
new_throughput = throughputs.min()
|
|
if new_throughput < initial_throughput or new_throughput < eps:
|
|
return False
|
|
|
|
actual_quality = initial_throughput / new_throughput
|
|
logger.info(f"Swarm balance quality: {actual_quality * 100:.1f}%")
|
|
|
|
return actual_quality < balance_quality - eps
|