diff --git a/benchmark/datasets.py b/benchmark/datasets.py
index 9d79f8a8..7e4e95fb 100644
--- a/benchmark/datasets.py
+++ b/benchmark/datasets.py
@@ -294,6 +294,7 @@ def get_dataset_iterator(self, bs=512, split=(1,0)):
         i0, i1 = self.nb * rank // nsplit, self.nb * (rank + 1) // nsplit
         filename = self.get_dataset_fn()
         x = xbin_mmap(filename, dtype=self.dtype, maxn=self.nb)
+        print(f"x.shape={x.shape} self.nb={self.nb} self.d={self.d}")
         assert x.shape == (self.nb, self.d)
         for j0 in range(i0, i1, bs):
             j1 = min(j0 + bs, i1)
@@ -385,6 +386,33 @@ def __init__(self, nb_M=1000):
     def distance(self):
         return "euclidean"
 
+
+class BigANNDimReducedDataset(DatasetCompetitionFormat):
+    def __init__(self, nb_M=1000):
+        self.nb_M = nb_M
+        self.nb = 10**6 * nb_M
+        self.d = 32
+        self.nq = 10000
+        # use for indexing of the dimensionality reduced dataset
+        self.dtype = "float32"
+        # use for search over the index built from the dimensionality reduced dataset
+        # self.dtype = "uint8"
+        self.ds_fn = "base.1B.u8bin"
+        self.qs_fn = "query.public.10K.u8bin"
+        self.gt_fn = (
+            "GT.public.1B.ibin" if self.nb_M == 1000 else
+            subset_url + "GT_100M/bigann-100M" if self.nb_M == 100 else
+            subset_url + "GT_10M/bigann-10M" if self.nb_M == 10 else
+            None
+        )
+        # self.gt_fn = "https://comp21storage.blob.core.windows.net/publiccontainer/comp21/bigann/public_query_gt100.bin" if self.nb == 10**9 else None
+        self.base_url = "https://dl.fbaipublicfiles.com/billion-scale-ann-benchmarks/bigann/"
+        self.basedir = os.path.join(BASEDIR, "bigann")
+
+    def distance(self):
+        return "euclidean"
+
+
 class Deep1BDataset(DatasetCompetitionFormat):
     def __init__(self, nb_M=1000):
         self.nb_M = nb_M
@@ -616,6 +644,7 @@ def default_count(self):
     'bigann-1B': lambda : BigANNDataset(1000),
     'bigann-100M': lambda : BigANNDataset(100),
     'bigann-10M': lambda : BigANNDataset(10),
+    'bigann-dim-reduced-100M': lambda: BigANNDimReducedDataset(100),
 
     'deep-1B': lambda : Deep1BDataset(),
     'deep-100M': lambda : Deep1BDataset(100),
diff --git a/run_t1_faiss_baseline_eval.sh b/run_t1_faiss_baseline_eval.sh
new file mode 100755
index 00000000..257a20de
--- /dev/null
+++ b/run_t1_faiss_baseline_eval.sh
@@ -0,0 +1,37 @@
+params="
+nprobe=1,quantizer_efSearch=4
+nprobe=2,quantizer_efSearch=4
+nprobe=4,quantizer_efSearch=4
+nprobe=4,quantizer_efSearch=8
+nprobe=8,quantizer_efSearch=4
+nprobe=8,quantizer_efSearch=8
+nprobe=8,quantizer_efSearch=16
+nprobe=8,quantizer_efSearch=32
+nprobe=16,quantizer_efSearch=16
+nprobe=16,quantizer_efSearch=32
+nprobe=16,quantizer_efSearch=64
+nprobe=32,quantizer_efSearch=8
+nprobe=32,quantizer_efSearch=32
+nprobe=32,quantizer_efSearch=64
+nprobe=32,quantizer_efSearch=128
+nprobe=64,quantizer_efSearch=16
+nprobe=64,quantizer_efSearch=32
+nprobe=64,quantizer_efSearch=64
+nprobe=64,quantizer_efSearch=128
+nprobe=64,quantizer_efSearch=256
+nprobe=128,quantizer_efSearch=32
+nprobe=128,quantizer_efSearch=64
+nprobe=128,quantizer_efSearch=128
+nprobe=128,quantizer_efSearch=256
+nprobe=128,quantizer_efSearch=512
+nprobe=256,quantizer_efSearch=64
+nprobe=256,quantizer_efSearch=128
+nprobe=256,quantizer_efSearch=512
+nprobe=512,quantizer_efSearch=256
+nprobe=512,quantizer_efSearch=512
+nprobe=1024,quantizer_efSearch=256
+"
+
+python  track1_baseline_faiss/baseline_faiss.py \
+   --dataset bigann-dim-reduced-100M --indexfile data/track1_baseline_faiss/bigann-100M.IVF1M_2level_PQ64x4fsr.faissindex \
+   --search --searchparams $params
diff --git a/run_t1_faiss_baseline_index.sh b/run_t1_faiss_baseline_index.sh
new file mode 100755
index 00000000..dd1912fe
--- /dev/null
+++ b/run_t1_faiss_baseline_index.sh
@@ -0,0 +1,11 @@
+python -u track1_baseline_faiss/baseline_faiss.py --dataset bigann-dim-reduced-100M \
+    --indexkey OPQ64_128,IVF1048576_HNSW32,PQ64x4fsr \
+    --maxtrain 10000000 \
+    --two_level_clustering \
+    --build \
+    --add_splits 30 \
+    --indexfile data/track1_baseline_faiss_dim_reduction/bigann-100M.IVF1M_2level_PQ64x4fsr.faissindex \
+    --quantizer_efConstruction 200 \
+    --quantizer_add_efSearch 80
+
+