good hyper parameters for the task2 spot dataset

Author: Neiko2002

python/benchmark_task2_spot.py

@@ -34,74 +34,17 @@ class ModeConfig:
 
 
 MODES: list[ModeConfig] = [
-    ModeConfig(
-        name="mode3_no_flas",
-        mode="mode3",
-        label="Mode 3: FP32 Build & FP16 Explore (no FLAS)",
-        settings="k_ext=64, k_graph=32, runs=1",
-        max_dist="4000,8000",
-        eps_search="0.25",
-        num_runs=1,
-        use_flas=False,
-    ),
-    ModeConfig(
-        name="mode3_flas",
-        mode="mode3",
-        label="Mode 3: FP32 Build & FP16 Explore (+ FLAS)",
-        settings="k_ext=64, k_graph=32, runs=1",
-        max_dist="4000,8000",
-        eps_search="0.28",
-        num_runs=1,
-        use_flas=True,
-    ),
-    ModeConfig(
-        name="mode5_no_flas",
-        mode="mode5",
-        label="Mode 5: L2 Build (d+1) & FP16 IP Explore (no FLAS)",
-        settings="k_ext=64, k_graph=32, runs=1",
-        max_dist="2000,4000,8000",
-        eps_search="0.18",
-        num_runs=1,
-        use_flas=False,
-    ),
     ModeConfig(
         name="mode5_flas",
         mode="mode5",
         label="Mode 5: L2 Build (d+1) & FP16 IP Explore (+ FLAS)",
-        settings="k_ext=64, k_graph=32, runs=1",
-        max_dist="2000,4000,8000",
-        eps_search="0.18",
-        num_runs=1,
-        use_flas=True,
-    ),
-    ModeConfig(
-        name="mode4_flas",
-        mode="mode4",
-        label="Mode 4: L2 Build (d+1) & FP32 L2 Explore (+ FLAS)",
-        settings="k_ext=64, k_graph=32, runs=1",
-        max_dist="2000,4000,8000",
-        eps_search="0.008",
-        num_runs=1,
-        use_flas=True,
-    ),
-    ModeConfig(
-        name="mode6_flas",
-        mode="mode6",
-        label="Mode 6: L2 Build (d+1) & FP16 L2 Explore (+ FLAS)",
-        settings="k_ext=64, k_graph=32, runs=1",
-        max_dist="2000,4000,8000",
-        eps_search="0.007",
-        num_runs=1,
-        use_flas=True,
-    ),
-    ModeConfig(
-        name="mode7_flas",
-        mode="mode7",
-        label="Mode 7: L2 Build (d+2) & FP16 L2 Explore (+ FLAS)",
-        settings="k_ext=64, k_graph=32, runs=1",
-        max_dist="2000,4000,8000",
-        eps_search="0.007",
-        num_runs=1,
+        settings="k_ext=48, k_graph=24, runs=100",
+        max_dist="1400,1500,1600",
+        k_graph="32",
+        k_ext="64",
+        eps_ext="0.1",
+        eps_search="0.05,0.06,0.07,0.08,0.09",
+        num_runs=100,
         use_flas=True,
     ),
 ]

submission/search.py

@@ -34,7 +34,8 @@
 
 DEGLIB_BIN = os.environ.get("DEGLIB_BIN", "/usr/local/bin/deglib_sisap")
 ALGO = "deglib"
-THREADS = os.environ.get("DEGLIB_THREADS", "8")
+THREADS = str(os.environ.get("DEGLIB_THREADS") or os.cpu_count() or 1)
+print(f"[search.py] Using {THREADS} threads")
 
 # --- per-dataset parameter profiles ------------------------------------------
 # Each dataset maps to a LIST of configs; every config is one binary invocation
@@ -96,8 +97,8 @@
     ],
     # spot-check (14k vectors); smoke test only
     "llama-small": [
-        dict(mode="mode5", k_graph=32, k_ext=64, eps_ext=0.001, build_threads=1, use_flas=True,
-             num_runs=1, max_dist=[2000, 4000, 8000], eps_search=[0.2, 0.3]),
+        dict(mode="mode5", k_graph=32, k_ext=64, eps_ext=0.1, build_threads=1, use_flas=True,
+             num_runs=1, max_dist=[1400,1500,1600], eps_search=[0.05,0.06,0.07,0.08,0.09]),
     ],
 }