add benchmarking for hnsw flat based on efSearch (#3858)

Summary:
Pull Request resolved: #3858

Stealing from Alexander's hnsw benchmark where he tuned the efSearch parameter and search_bounded_queue in https://fburl.com/code/keovfhxk

Reviewed By: asadoughi

Differential Revision: D62652021

fbshipit-source-id: c9324718781ab171f1be86e7310717c9bcf4c563

faiss/perf_tests/bench_hnsw.py

@@ -52,10 +52,12 @@ def accumulate_perf_counter(
 def run_on_dataset(
  ds: Dataset,
  M: int,
- num_threads:
- int,
+ num_threads: int,
+ num_add_iterations: int,
+ num_search_iterations: int,
  efSearch: int = 16,
- efConstruction: int = 40
+ efConstruction: int = 40,
+ search_bounded_queue: bool = True,
 ) -> Dict[str, int]:
  xq = ds.get_queries()
  xb = ds.get_database()
@@ -67,22 +69,27 @@ def run_on_dataset(
  # pyre-ignore[16]: Module `faiss` has no attribute `omp_set_num_threads`.
  faiss.omp_set_num_threads(num_threads)
  index = faiss.IndexHNSWFlat(d, M)
- index.hnsw.efConstruction = 40 # default
+ index.hnsw.efConstruction = efConstruction # default
  with timed_execution() as t:
- index.add(xb)
+ for _ in range(num_add_iterations):
+ index.add(xb)
  counters = {}
  accumulate_perf_counter("add", t, counters)
  counters["nb"] = nb
+ counters["num_add_iterations"] = num_add_iterations
 
  index.hnsw.efSearch = efSearch
+ index.hnsw.search_bounded_queue = search_bounded_queue
  with timed_execution() as t:
- D, I = index.search(xq, k)
+ for _ in range(num_search_iterations):
+ D, I = index.search(xq, k)
  accumulate_perf_counter("search", t, counters)
  counters["nq"] = nq
  counters["efSearch"] = efSearch
  counters["efConstruction"] = efConstruction
  counters["M"] = M
  counters["d"] = d
+ counters["num_search_iterations"] = num_search_iterations
 
  return counters
 
@@ -93,61 +100,25 @@ def run(
  nq: int,
  M: int,
  num_threads: int,
+ num_add_iterations: int = 1,
+ num_search_iterations: int = 1,
  efSearch: int = 16,
  efConstruction: int = 40,
+ search_bounded_queue: bool = True,
 ) -> Dict[str, int]:
  ds = SyntheticDataset(d=d, nb=nb, nt=0, nq=nq, metric="L2", seed=1338)
  return run_on_dataset(
  ds,
  M=M,
+ num_add_iterations=num_add_iterations,
+ num_search_iterations=num_search_iterations,
  num_threads=num_threads,
  efSearch=efSearch,
  efConstruction=efConstruction,
+ search_bounded_queue=search_bounded_queue,
  )
 
 
-def _merge_counters(
- element: Dict[str, int], accu: Optional[Dict[str, int]] = None
-) -> Dict[str, int]:
- if accu is None:
- return dict(element)
- else:
- assert accu.keys() <= element.keys(), (
- "Accu keys must be a subset of element keys: "
- f"{accu.keys()} not a subset of {element.keys()}"
- )
- for key in accu.keys():
- if is_perf_counter(key):
- accu[key] += element[key]
- return accu
-
-
-def run_with_iterations(
- iterations: int,
- d: int,
- nb: int,
- nq: int,
- M: int,
- num_threads: int,
- efSearch: int = 16,
- efConstruction: int = 40,
-) -> Dict[str, int]:
- result = None
- for _ in range(iterations):
- counters = run(
- d=d,
- nb=nb,
- nq=nq,
- M=M,
- num_threads=num_threads,
- efSearch=efSearch,
- efConstruction=efConstruction,
- )
- result = _merge_counters(counters, result)
- assert result is not None
- return result
-
-
 def _accumulate_counters(
  element: Dict[str, int], accu: Optional[Dict[str, List[int]]] = None
 ) -> Dict[str, List[int]]:
@@ -169,10 +140,13 @@ def main():
  parser.add_argument("-M", "--M", type=int, required=True)
  parser.add_argument("-t", "--num-threads", type=int, required=True)
  parser.add_argument("-w", "--warm-up-iterations", type=int, default=0)
- parser.add_argument("-i", "--num-iterations", type=int, default=20)
+ parser.add_argument("-i", "--num-search-iterations", type=int, default=20)
+ parser.add_argument("-i", "--num-add-iterations", type=int, default=20)
  parser.add_argument("-r", "--num-repetitions", type=int, default=20)
  parser.add_argument("-s", "--ef-search", type=int, default=16)
  parser.add_argument("-c", "--ef-construction", type=int, default=40)
+ parser.add_argument("-b", "--search-bounded-queue", action="store_true")
+
  parser.add_argument("-n", "--nb", type=int, default=5000)
  parser.add_argument("-q", "--nq", type=int, default=500)
  parser.add_argument("-d", "--d", type=int, default=128)
@@ -181,15 +155,17 @@ def main():
  if args.warm_up_iterations > 0:
  print(f"Warming up for {args.warm_up_iterations} iterations...")
  # warm-up
- run_with_iterations(
- iterations=args.warm_up_iterations,
+ run(
+ num_search_iterations=args.warm_up_iterations,
+ num_add_iterations=args.warm_up_iterations,
  d=args.d,
  nb=args.nb,
  nq=args.nq,
  M=args.M,
  num_threads=args.num_threads,
  efSearch=args.ef_search,
  efConstruction=args.ef_construction,
+ search_bounded_queue=args.search_bounded_queue,
  )
  print(
  f"Running benchmark with dataset(nb={args.nb}, nq={args.nq}, "
@@ -198,24 +174,23 @@ def main():
  )
  result = None
  for _ in range(args.num_repetitions):
- counters = run_with_iterations(
- iterations=args.num_iterations,
+ counters = run(
+ num_search_iterations=args.num_search_iterations,
+ num_add_iterations=args.num_add_iterations,
  d=args.d,
  nb=args.nb,
  nq=args.nq,
  M=args.M,
  num_threads=args.num_threads,
  efSearch=args.ef_search,
  efConstruction=args.ef_construction,
+ search_bounded_queue=args.search_bounded_queue,
  )
  result = _accumulate_counters(counters, result)
  assert result is not None
  for counter, values in result.items():
  if is_perf_counter(counter):
  print(
- "%s t=%.3f us (± %.4f)" % (
- counter,
- np.mean(values),
- np.std(values)
- )
+ "%s t=%.3f us (± %.4f)" %
+ (counter, np.mean(values), np.std(values))
  )