diff --git a/integrations/dense/test_ance.py b/integrations/dense/test_ance.py
index a8c010255..1ff11aac2 100644
--- a/integrations/dense/test_ance.py
+++ b/integrations/dense/test_ance.py
@@ -16,8 +16,8 @@
 
 """Integration tests for ANCE and ANCE PRF using on-the-fly query encoding."""
 
+import multiprocessing
 import os
-import socket
 import unittest
 
 from integrations.utils import clean_files, run_command, parse_score, parse_score_qa, parse_score_msmarco
@@ -29,30 +29,16 @@ class TestAnce(unittest.TestCase):
     def setUp(self):
         self.temp_files = []
         self.threads = 16
-        self.batch_size = 256
+        self.batch_size = self.threads * 32
         self.rocchio_alpha = 0.4
         self.rocchio_beta = 0.6
 
-        # Hard-code larger values for internal servers
-        if socket.gethostname().startswith('damiano') or socket.gethostname().startswith('orca'):
-            self.threads = 36
-            self.batch_size = 144
-
-    def test_ance_encoded_queries(self):
-        encoded = QueryEncoder.load_encoded_queries('ance-msmarco-passage-dev-subset')
-        topics = get_topics('msmarco-passage-dev-subset')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-        encoded = QueryEncoder.load_encoded_queries('ance-dl19-passage')
-        topics = get_topics('dl19-passage')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-        encoded = QueryEncoder.load_encoded_queries('ance-dl20')
-        topics = get_topics('dl20')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
+        half_cores = int(multiprocessing.cpu_count() / 2)
+        # If server supports more threads, then use more threads.
+        # As a heuristic, use up half up available CPU cores.
+        if half_cores > self.threads:
+            self.threads = half_cores
+            self.batch_size = half_cores * 32
 
     def test_msmarco_passage_ance_avg_prf_otf(self):
         output_file = 'test_run.dl2019.ance.avg-prf.otf.trec'
diff --git a/integrations/dense/test_distilbert_kd.py b/integrations/dense/test_distilbert_kd.py
deleted file mode 100644
index c476017df..000000000
--- a/integrations/dense/test_distilbert_kd.py
+++ /dev/null
@@ -1,45 +0,0 @@
-#
-# Pyserini: Reproducible IR research with sparse and dense representations
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-#
-
-"""Integration tests for DistilBERT KD."""
-
-import unittest
-
-from pyserini.search import QueryEncoder
-from pyserini.search import get_topics
-
-
-class TestDistilBertKd(unittest.TestCase):
-    # Note that we test actual retrieval in 2CR, so no need to test here.
-    def test_distilbert_kd_encoded_queries(self):
-        encoded = QueryEncoder.load_encoded_queries('distilbert_kd-msmarco-passage-dev-subset')
-        topics = get_topics('msmarco-passage-dev-subset')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-        encoded = QueryEncoder.load_encoded_queries('distilbert_kd-dl19-passage')
-        topics = get_topics('dl19-passage')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-        encoded = QueryEncoder.load_encoded_queries('distilbert_kd-dl20')
-        topics = get_topics('dl20')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-
-if __name__ == '__main__':
-    unittest.main()
diff --git a/integrations/dense/test_distilbert_tasb.py b/integrations/dense/test_distilbert_tasb.py
deleted file mode 100644
index 997ac601b..000000000
--- a/integrations/dense/test_distilbert_tasb.py
+++ /dev/null
@@ -1,44 +0,0 @@
-#
-# Pyserini: Reproducible IR research with sparse and dense representations
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-#
-
-"""Integration tests for DistilBERT TAS-B."""
-
-import unittest
-
-from pyserini.search import QueryEncoder
-from pyserini.search import get_topics
-
-
-class TestDistilBertTasB(unittest.TestCase):
-    def test_distilbert_kd_tas_b_encoded_queries(self):
-        encoded = QueryEncoder.load_encoded_queries('distilbert_tas_b-msmarco-passage-dev-subset')
-        topics = get_topics('msmarco-passage-dev-subset')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-        encoded = QueryEncoder.load_encoded_queries('distilbert_tas_b-dl19-passage')
-        topics = get_topics('dl19-passage')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-        encoded = QueryEncoder.load_encoded_queries('distilbert_tas_b-dl20')
-        topics = get_topics('dl20')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-
-if __name__ == '__main__':
-    unittest.main()
diff --git a/integrations/dense/test_dpr.py b/integrations/dense/test_dpr.py
index a05d94546..ec57c6e88 100644
--- a/integrations/dense/test_dpr.py
+++ b/integrations/dense/test_dpr.py
@@ -17,8 +17,8 @@
 """Integration tests for DPR model using pre-encoded queries."""
 
 import json
+import multiprocessing
 import os
-import socket
 import unittest
 
 from integrations.utils import clean_files, run_command, parse_score_qa
@@ -30,12 +30,14 @@ class TestDpr(unittest.TestCase):
     def setUp(self):
         self.temp_files = []
         self.threads = 16
-        self.batch_size = 256
+        self.batch_size = self.threads * 32
 
-        # Hard-code larger values for internal servers
-        if socket.gethostname().startswith('damiano') or socket.gethostname().startswith('orca'):
-            self.threads = 36
-            self.batch_size = 144
+        half_cores = int(multiprocessing.cpu_count() / 2)
+        # If server supports more threads, then use more threads.
+        # As a heuristic, use up half up available CPU cores.
+        if half_cores > self.threads:
+            self.threads = half_cores
+            self.batch_size = half_cores * 32
 
     def test_dpr_nq_test_bf_otf(self):
         output_file = 'test_run.dpr.nq-test.multi.bf.otf.trec'
diff --git a/integrations/dense/test_sbert.py b/integrations/dense/test_sbert.py
index 4ebab1668..884238282 100644
--- a/integrations/dense/test_sbert.py
+++ b/integrations/dense/test_sbert.py
@@ -16,25 +16,25 @@
 
 """Integration tests for ANCE model using on-the-fly query encoding."""
 
+import multiprocessing
 import os
-import socket
 import unittest
 
 from integrations.utils import clean_files, run_command, parse_score
-from pyserini.search import QueryEncoder
-from pyserini.search import get_topics
 
 
 class TestSBert(unittest.TestCase):
     def setUp(self):
         self.temp_files = []
         self.threads = 16
-        self.batch_size = 256
+        self.batch_size = self.threads * 32
 
-        # Hard-code larger values for internal servers
-        if socket.gethostname().startswith('damiano') or socket.gethostname().startswith('orca'):
-            self.threads = 36
-            self.batch_size = 144
+        half_cores = int(multiprocessing.cpu_count() / 2)
+        # If server supports more threads, then use more threads.
+        # As a heuristic, use up half up available CPU cores.
+        if half_cores > self.threads:
+            self.threads = half_cores
+            self.batch_size = half_cores * 32
 
     def test_msmarco_passage_sbert_bf_otf(self):
         output_file = 'test_run.msmarco-passage.sbert.bf.otf.tsv'
@@ -53,12 +53,6 @@ def test_msmarco_passage_sbert_bf_otf(self):
         self.assertEqual(status, 0)
         self.assertAlmostEqual(score, 0.3314, delta=0.0001)
 
-    def test_msmarco_passage_sbert_encoded_queries(self):
-        encoded = QueryEncoder.load_encoded_queries('sbert-msmarco-passage-dev-subset')
-        topics = get_topics('msmarco-passage-dev-subset')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
     def tearDown(self):
         clean_files(self.temp_files)
 
diff --git a/integrations/dense/test_tct_colbert-v2.py b/integrations/dense/test_tct_colbert-v2.py
index 37d6fd404..4a0c0c0f9 100644
--- a/integrations/dense/test_tct_colbert-v2.py
+++ b/integrations/dense/test_tct_colbert-v2.py
@@ -16,25 +16,25 @@
 
 """Integration tests for TCT-ColBERTv2 models using on-the-fly query encoding."""
 
+import multiprocessing
 import os
-import socket
 import unittest
 
 from integrations.utils import clean_files, run_command, parse_score
-from pyserini.search import QueryEncoder
-from pyserini.search import get_topics
 
 
 class TestTctColBertV2(unittest.TestCase):
     def setUp(self):
         self.temp_files = []
         self.threads = 16
-        self.batch_size = 256
+        self.batch_size = self.threads * 32
 
-        # Hard-code larger values for internal servers
-        if socket.gethostname().startswith('damiano') or socket.gethostname().startswith('orca'):
-            self.threads = 36
-            self.batch_size = 144
+        half_cores = int(multiprocessing.cpu_count() / 2)
+        # If server supports more threads, then use more threads.
+        # As a heuristic, use up half up available CPU cores.
+        if half_cores > self.threads:
+            self.threads = half_cores
+            self.batch_size = half_cores * 32
 
     def test_msmarco_passage_tct_colbert_v2_bf_otf(self):
         output_file = 'test_run.msmarco-passage.tct_colbert-v2.bf-otf.tsv'
@@ -106,24 +106,6 @@ def test_msmarco_passage_tct_colbert_v2_hnp_bf_d2q_hybrid_otf(self):
         self.assertEqual(status, 0)
         self.assertAlmostEqual(score, 0.3731, delta=0.0001)
 
-    def test_msmarco_passage_tct_colbert_v2_encoded_queries(self):
-        encoded = QueryEncoder.load_encoded_queries('tct_colbert-v2-msmarco-passage-dev-subset')
-        topics = get_topics('msmarco-passage-dev-subset')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-    def test_msmarco_passage_tct_colbert_v2_hn_encoded_queries(self):
-        encoded = QueryEncoder.load_encoded_queries('tct_colbert-v2-hn-msmarco-passage-dev-subset')
-        topics = get_topics('msmarco-passage-dev-subset')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
-    def test_msmarco_passage_tct_colbert_v2_hnp_encoded_queries(self):
-        encoded = QueryEncoder.load_encoded_queries('tct_colbert-v2-hnp-msmarco-passage-dev-subset')
-        topics = get_topics('msmarco-passage-dev-subset')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
     def tearDown(self):
         clean_files(self.temp_files)
 
diff --git a/integrations/dense/test_tct_colbert.py b/integrations/dense/test_tct_colbert.py
index 18c9fc391..67b94d2c2 100644
--- a/integrations/dense/test_tct_colbert.py
+++ b/integrations/dense/test_tct_colbert.py
@@ -16,8 +16,8 @@
 
 """Integration tests for TCT-ColBERTv1 models using on-the-fly query encoding."""
 
+import multiprocessing
 import os
-import socket
 import unittest
 
 from integrations.utils import clean_files, run_command, parse_score
@@ -29,12 +29,14 @@ class TestTctColBert(unittest.TestCase):
     def setUp(self):
         self.temp_files = []
         self.threads = 16
-        self.batch_size = 256
+        self.batch_size = self.threads * 32
 
-        # Hard-code larger values for internal servers
-        if socket.gethostname().startswith('damiano') or socket.gethostname().startswith('orca'):
-            self.threads = 36
-            self.batch_size = 144
+        half_cores = int(multiprocessing.cpu_count() / 2)
+        # If server supports more threads, then use more threads.
+        # As a heuristic, use up half up available CPU cores.
+        if half_cores > self.threads:
+            self.threads = half_cores
+            self.batch_size = half_cores * 32
 
     def test_msmarco_passage_tct_colbert_bf_otf(self):
         output_file = 'test_run.msmarco-passage.tct_colbert.bf-otf.tsv'
@@ -169,12 +171,6 @@ def test_msmarco_doc_tct_colbert_bf_d2q_hybrid_otf(self):
         self.assertEqual(status, 0)
         self.assertAlmostEqual(score, 0.3784, places=4)
 
-    def test_msmarco_doc_tct_colbert_encoded_queries(self):
-        encoded = QueryEncoder.load_encoded_queries('tct_colbert-msmarco-doc-dev')
-        topics = get_topics('msmarco-doc-dev')
-        for t in topics:
-            self.assertTrue(topics[t]['title'] in encoded.embedding)
-
     def tearDown(self):
         clean_files(self.temp_files)
 
diff --git a/integrations/papers/test_ecir2023.py b/integrations/papers/test_ecir2023.py
index f894483ed..e029c5f08 100644
--- a/integrations/papers/test_ecir2023.py
+++ b/integrations/papers/test_ecir2023.py
@@ -16,6 +16,7 @@
 
 """Integration tests for commands in Pradeep et al. resource paper at ECIR 2023."""
 
+import multiprocessing
 import os
 import unittest
 
@@ -25,6 +26,15 @@
 class TestECIR2023(unittest.TestCase):
     def setUp(self):
         self.temp_files = []
+        self.threads = 16
+        self.batch_size = self.threads * 32
+
+        half_cores = int(multiprocessing.cpu_count() / 2)
+        # If server supports more threads, then use more threads.
+        # As a heuristic, use up half up available CPU cores.
+        if half_cores > self.threads:
+            self.threads = half_cores
+            self.batch_size = half_cores * 32
 
     def test_section5_sub2_first(self):
         """Sample code of the first command in Section 5.2."""
@@ -42,7 +52,7 @@ def test_section5_sub2_first(self):
                       --topics nq-test \
                       --encoder castorini/dkrr-dpr-nq-retriever \
                       --output {output_file} --query-prefix question: \
-                      --threads 72 --batch-size 72 \
+                      --threads {self.threads} --batch-size {self.batch_size} \
                       --hits 100'
         status = os.system(run_cmd)
         self.assertEqual(status, 0)
diff --git a/integrations/papers/test_sigir2022.py b/integrations/papers/test_sigir2022.py
index ff7ae0215..6665bb5f1 100644
--- a/integrations/papers/test_sigir2022.py
+++ b/integrations/papers/test_sigir2022.py
@@ -16,6 +16,7 @@
 
 """Integration tests for commands in Ma et al. resource paper and Trotman et al. demo paper at SIGIR 2022."""
 
+import multiprocessing
 import os
 import unittest
 
@@ -25,6 +26,15 @@
 class TestSIGIR2022(unittest.TestCase):
     def setUp(self):
         self.temp_files = []
+        self.threads = 16
+        self.batch_size = self.threads * 8
+
+        half_cores = int(multiprocessing.cpu_count() / 2)
+        # If server supports more threads, then use more threads.
+        # As a heuristic, use up half up available CPU cores.
+        if half_cores > self.threads:
+            self.threads = half_cores
+            self.batch_size = half_cores * 8
 
     def test_Ma_etal_section4_1a(self):
         """Sample code in Section 4.1. in Ma et al. resource paper."""
@@ -57,7 +67,7 @@ def test_Ma_etal_section4_1b(self):
                       --topics msmarco-v2-passage-dev \
                       --encoder castorini/unicoil-msmarco-passage \
                       --output {output_file} \
-                      --batch 144 --threads 36 \
+                      --batch {self.batch_size} --threads {self.threads} \
                       --hits 1000 \
                       --impact'
         status = os.system(run_cmd)
@@ -78,7 +88,7 @@ def test_Trotman_etal(self):
                       --topics msmarco-passage-dev-subset-unicoil \
                       --output {output_file} \
                       --output-format msmarco \
-                      --batch 36 --threads 12 \
+                      --batch {self.batch_size} --threads {self.threads} \
                       --hits 1000 \
                       --impact'
         status = os.system(run_cmd)
diff --git a/integrations/dense/test_kilt.py b/integrations/sparse/test_kilt.py
similarity index 85%
rename from integrations/dense/test_kilt.py
rename to integrations/sparse/test_kilt.py
index b337cd8ac..4b27ab1df 100644
--- a/integrations/dense/test_kilt.py
+++ b/integrations/sparse/test_kilt.py
@@ -16,9 +16,9 @@
 
 """Integration tests for KILT integration."""
 
+import multiprocessing
 import os
 import re
-import socket
 import unittest
 
 from integrations.utils import clean_files, run_command
@@ -37,12 +37,14 @@ class TestKilt(unittest.TestCase):
     def setUp(self):
         self.temp_files = []
         self.threads = 16
-        self.batch_size = 256
+        self.batch_size = self.threads * 8
 
-        # Hard-code larger values for internal servers
-        if socket.gethostname().startswith('damiano') or socket.gethostname().startswith('orca'):
-            self.threads = 36
-            self.batch_size = 144
+        half_cores = int(multiprocessing.cpu_count() / 2)
+        # If server supports more threads, then use more threads.
+        # As a heuristic, use up half up available CPU cores.
+        if half_cores > self.threads:
+            self.threads = half_cores
+            self.batch_size = half_cores * 8
 
     def test_kilt_search(self):
         run_file = 'test_run.fever-dev-kilt.jsonl'
diff --git a/pyserini/resources/naturalquestion.yaml b/pyserini/resources/naturalquestion.yaml
index e8050af03..7a6cecc0a 100644
--- a/pyserini/resources/naturalquestion.yaml
+++ b/pyserini/resources/naturalquestion.yaml
@@ -1,7 +1,7 @@
 conditions:
   - model_name: BM25-k1_0.9_b_0.4
     command: 
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics nq-test --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics nq-test --output $output --bm25 --k1 0.9 --b 0.4
     scores:
       - Top5: 44.82
         Top20: 64.02
@@ -10,7 +10,7 @@ conditions:
         Top1000: 88.95
   - model_name: BM25-k1_0.9_b_0.4_dpr-topics
     command: 
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics dpr-nq-test --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics dpr-nq-test --output $output --bm25 --k1 0.9 --b 0.4
     scores:
       - Top5: 43.77
         Top20: 62.99
@@ -19,9 +19,9 @@ conditions:
         Top1000: 88.01
   - model_name: GarT5-RRF
     command: 
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics nq-test-gar-t5-answers --output $output --bm25 --k1 0.9 --b 0.4
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics nq-test-gar-t5-titles --output $output --bm25 --k1 0.9 --b 0.4
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics nq-test-gar-t5-sentences --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics nq-test-gar-t5-answers --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics nq-test-gar-t5-titles --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics nq-test-gar-t5-sentences --output $output --bm25 --k1 0.9 --b 0.4
     scores:
       - Top5: 64.62
         Top20: 77.17
@@ -30,7 +30,7 @@ conditions:
         Top1000: 92.91
   - model_name: DPR
     command: 
-      - python -m pyserini.search.faiss --threads 72 --batch-size 128 --index wikipedia-dpr-100w.dpr-single-nq --encoder facebook/dpr-question_encoder-single-nq-base --topics nq-test --output $output
+      - python -m pyserini.search.faiss --threads 16 --batch-size 512 --index wikipedia-dpr-100w.dpr-single-nq --encoder facebook/dpr-question_encoder-single-nq-base --topics nq-test --output $output
     scores:
       - Top5: 68.61
         Top20: 80.58 
@@ -39,7 +39,7 @@ conditions:
         Top1000: 91.83
   - model_name: DPR-DKRR
     command: 
-      - 'python -m pyserini.search.faiss --threads 72 --batch-size 128 --index wikipedia-dpr-100w.dkrr-nq --encoder castorini/dkrr-dpr-nq-retriever --topics nq-test --output $output --query-prefix question: '
+      - 'python -m pyserini.search.faiss --threads 16 --batch-size 512 --index wikipedia-dpr-100w.dkrr-nq --encoder castorini/dkrr-dpr-nq-retriever --topics nq-test --output $output --query-prefix question: '
     scores:
       - Top5: 73.80
         Top20: 84.27
@@ -48,7 +48,7 @@ conditions:
         Top1000: 93.43
   - model_name: DPR-Hybrid
     command: 
-      - python -m pyserini.search.hybrid dense --index wikipedia-dpr-100w.dpr-single-nq --encoder facebook/dpr-question_encoder-single-nq-base sparse --index wikipedia-dpr-100w fusion --alpha 1.2 run --topics nq-test --output $output --threads 72 --batch-size 128
+      - python -m pyserini.search.hybrid dense --index wikipedia-dpr-100w.dpr-single-nq --encoder facebook/dpr-question_encoder-single-nq-base sparse --index wikipedia-dpr-100w fusion --alpha 1.2 run --topics nq-test --output $output --threads 16 --batch-size 512
     scores:
       - Top5: 72.52
         Top20: 83.43
diff --git a/pyserini/resources/triviaqa.yaml b/pyserini/resources/triviaqa.yaml
index a6d466a30..ea1dae6a0 100644
--- a/pyserini/resources/triviaqa.yaml
+++ b/pyserini/resources/triviaqa.yaml
@@ -1,7 +1,7 @@
 conditions:
   - model_name: BM25-k1_0.9_b_0.4
     command: 
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics dpr-trivia-test --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics dpr-trivia-test --output $output --bm25 --k1 0.9 --b 0.4
     scores:
       - Top5: 66.29
         Top20: 76.41
@@ -10,7 +10,7 @@ conditions:
         Top1000: 88.50
   - model_name: BM25-k1_0.9_b_0.4_dpr-topics
     command: 
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics dpr-trivia-test --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics dpr-trivia-test --output $output --bm25 --k1 0.9 --b 0.4
     scores:
       - Top5: 66.29
         Top20: 76.41
@@ -19,9 +19,9 @@ conditions:
         Top1000: 88.50
   - model_name: GarT5-RRF
     command: 
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics dpr-trivia-test-gar-t5-answers --output $output --bm25 --k1 0.9 --b 0.4
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics dpr-trivia-test-gar-t5-titles --output $output --bm25 --k1 0.9 --b 0.4
-      - python -m pyserini.search.lucene --threads 72 --batch-size 128 --index wikipedia-dpr-100w --topics dpr-trivia-test-gar-t5-sentences --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics dpr-trivia-test-gar-t5-answers --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics dpr-trivia-test-gar-t5-titles --output $output --bm25 --k1 0.9 --b 0.4
+      - python -m pyserini.search.lucene --threads 16 --batch-size 512 --index wikipedia-dpr-100w --topics dpr-trivia-test-gar-t5-sentences --output $output --bm25 --k1 0.9 --b 0.4
     scores:
       - Top5: 72.82
         Top20: 80.66
@@ -30,7 +30,7 @@ conditions:
         Top1000: 90.06
   - model_name: DPR
     command: 
-      - python -m pyserini.search.faiss --threads 72 --batch-size 128 --index wikipedia-dpr-100w.dpr-multi --encoder facebook/dpr-question_encoder-multiset-base --topics dpr-trivia-test --output $output
+      - python -m pyserini.search.faiss --threads 16 --batch-size 512 --index wikipedia-dpr-100w.dpr-multi --encoder facebook/dpr-question_encoder-multiset-base --topics dpr-trivia-test --output $output
     scores:
       - Top5: 69.80
         Top20: 78.87 
@@ -39,7 +39,7 @@ conditions:
         Top1000: 89.30
   - model_name: DPR-DKRR
     command: 
-      - 'python -m pyserini.search.faiss --threads 72 --batch-size 128 --index wikipedia-dpr-100w.dkrr-tqa --encoder castorini/dkrr-dpr-tqa-retriever --topics dpr-trivia-test --output $output --query-prefix question: '
+      - 'python -m pyserini.search.faiss --threads 16 --batch-size 512 --index wikipedia-dpr-100w.dkrr-tqa --encoder castorini/dkrr-dpr-tqa-retriever --topics dpr-trivia-test --output $output --query-prefix question: '
     scores:
       - Top5: 77.23
         Top20: 83.74
@@ -48,7 +48,7 @@ conditions:
         Top1000: 90.63
   - model_name: DPR-Hybrid
     command: 
-      - python -m pyserini.search.hybrid dense --index wikipedia-dpr-100w.dpr-multi --encoder facebook/dpr-question_encoder-multiset-base sparse --index wikipedia-dpr-100w fusion --alpha 0.95 run --topics dpr-trivia-test --output $output --threads 72 --batch-size 128
+      - python -m pyserini.search.hybrid dense --index wikipedia-dpr-100w.dpr-multi --encoder facebook/dpr-question_encoder-multiset-base sparse --index wikipedia-dpr-100w fusion --alpha 0.95 run --topics dpr-trivia-test --output $output --threads 16 --batch-size 512
     scores:
       - Top5: 76.01
         Top20: 82.64
diff --git a/pyserini/search/lucene/ltr/_search_msmarco.py b/pyserini/search/lucene/ltr/_search_msmarco.py
index bc6ced6ae..7b1bb9504 100644
--- a/pyserini/search/lucene/ltr/_search_msmarco.py
+++ b/pyserini/search/lucene/ltr/_search_msmarco.py
@@ -205,7 +205,6 @@ def batch_extract(self, df, queries, fe):
                 group = pd.DataFrame(group_lst, columns=['qid', 'count'])
                 print(features.shape)
                 print(task_infos.qid.drop_duplicates().shape)
-                print(group.mean())
                 print(features.head(10))
                 print(features.info())
                 yield task_infos, features, group
@@ -219,7 +218,6 @@ def batch_extract(self, df, queries, fe):
             group = pd.DataFrame(group_lst, columns=['qid', 'count'])
             print(features.shape)
             print(task_infos.qid.drop_duplicates().shape)
-            print(group.mean())
             print(features.head(10))
             print(features.info())
             yield task_infos, features, group
diff --git a/scripts/classifier_prf/rank_trec_covid.py b/scripts/classifier_prf/rank_trec_covid.py
index 73b5ae950..e879dd7c1 100644
--- a/scripts/classifier_prf/rank_trec_covid.py
+++ b/scripts/classifier_prf/rank_trec_covid.py
@@ -195,10 +195,10 @@ class VectorizerType(Enum):
 def evaluate(qrels_path: str, run_path: str, options: str = ''):        
     curdir = os.getcwd()
     if curdir.endswith('clprf'):
-       anserini_root = '../../../anserini'
+       root = '..'
     else:
-       anserini_root = '../anserini'
-    prefix = f"{anserini_root}/tools/eval/trec_eval.9.0.4/trec_eval -c -M1000 -m all_trec {qrels_path}"
+       root = '.'
+    prefix = f"{root}/tools/eval/trec_eval.9.0.4/trec_eval -c -M1000 -m all_trec {qrels_path}"
     cmd1 = f"{prefix} {run_path} {options} | grep 'ndcg_cut_20 '"
     cmd2 = f"{prefix} {run_path} {options} | grep 'map                   	'"
     ndcg_score = str(subprocess.check_output(cmd1, shell=True)).split('\\t')[-1].split('\\n')[0]
diff --git a/scripts/jobs.integrations-all.txt b/scripts/jobs.integrations-all.txt
new file mode 100644
index 000000000..0c8210a58
--- /dev/null
+++ b/scripts/jobs.integrations-all.txt
@@ -0,0 +1,4 @@
+python -m unittest discover -s integrations/dense > logs/log.dense 2>&1
+python -m unittest discover -s integrations/sparse > logs/log.sparse 2>&1
+python -m unittest discover -s integrations/clprf > logs/log.clprf 2>&1
+python -m unittest discover -s integrations/papers > logs/log.papers 2>&1
diff --git a/scripts/run_jobs_with_load.py b/scripts/run_jobs_with_load.py
new file mode 100644
index 000000000..4a759d05e
--- /dev/null
+++ b/scripts/run_jobs_with_load.py
@@ -0,0 +1,58 @@
+#
+# Pyserini: Reproducible IR research with sparse and dense representations
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import argparse
+import logging
+import os
+import time
+
+logger = logging.getLogger('run_jobs_with_load')
+logger.setLevel(logging.INFO)
+ch = logging.StreamHandler()
+ch.setLevel(logging.INFO)
+formatter = logging.Formatter('%(asctime)s %(levelname)s  [python] %(message)s')
+ch.setFormatter(formatter)
+logger.addHandler(ch)
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(
+        description='Run jobs in parallel while maintaining a target load threshold.')
+    parser.add_argument('--file', type=str, default=None, help="File with commands.")
+    parser.add_argument('--sleep', type=int, default=30, help="Sleep between.")
+    parser.add_argument('--load', type=int, default=10, help="Target load.")
+    args = parser.parse_args()
+
+    logger.info(f'Running commands in {args.file}')
+    logger.info(f'Sleep interval: {args.sleep}')
+    logger.info(f'Threshold load: {args.load}')
+
+    with open(args.file) as f:
+        lines = f.read().splitlines()
+
+    for r in lines:
+        if not r or r.startswith('#'):
+            continue
+
+        logger.info(f'Launching: {r}')
+        os.system(r + ' &')
+
+        while True:
+            time.sleep(args.sleep)
+            load = os.getloadavg()[0]
+            logger.info(f'Current load: {load:.1f} (threshold = {args.load})')
+            if load < args.load:
+                break
diff --git a/tests/test_load_encoded_queries.py b/tests/test_load_encoded_queries.py
new file mode 100644
index 000000000..721891e16
--- /dev/null
+++ b/tests/test_load_encoded_queries.py
@@ -0,0 +1,106 @@
+#
+# Pyserini: Reproducible IR research with sparse and dense representations
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+"""Integration tests for DistilBERT KD."""
+
+import unittest
+
+from pyserini.search import QueryEncoder
+from pyserini.search import get_topics
+
+
+class TestLoadEncodedQueries(unittest.TestCase):
+    def test_ance_encoded_queries(self):
+        encoded = QueryEncoder.load_encoded_queries('ance-msmarco-passage-dev-subset')
+        topics = get_topics('msmarco-passage-dev-subset')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+        encoded = QueryEncoder.load_encoded_queries('ance-dl19-passage')
+        topics = get_topics('dl19-passage')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+        encoded = QueryEncoder.load_encoded_queries('ance-dl20')
+        topics = get_topics('dl20')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+    def test_distilbert_kd_encoded_queries(self):
+        encoded = QueryEncoder.load_encoded_queries('distilbert_kd-msmarco-passage-dev-subset')
+        topics = get_topics('msmarco-passage-dev-subset')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+        encoded = QueryEncoder.load_encoded_queries('distilbert_kd-dl19-passage')
+        topics = get_topics('dl19-passage')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+        encoded = QueryEncoder.load_encoded_queries('distilbert_kd-dl20')
+        topics = get_topics('dl20')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+    def test_distilbert_kd_tas_b_encoded_queries(self):
+        encoded = QueryEncoder.load_encoded_queries('distilbert_tas_b-msmarco-passage-dev-subset')
+        topics = get_topics('msmarco-passage-dev-subset')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+        encoded = QueryEncoder.load_encoded_queries('distilbert_tas_b-dl19-passage')
+        topics = get_topics('dl19-passage')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+        encoded = QueryEncoder.load_encoded_queries('distilbert_tas_b-dl20')
+        topics = get_topics('dl20')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+    def test_msmarco_doc_tct_colbert_encoded_queries(self):
+        encoded = QueryEncoder.load_encoded_queries('tct_colbert-msmarco-doc-dev')
+        topics = get_topics('msmarco-doc-dev')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+    def test_msmarco_passage_tct_colbert_v2_encoded_queries(self):
+        encoded = QueryEncoder.load_encoded_queries('tct_colbert-v2-msmarco-passage-dev-subset')
+        topics = get_topics('msmarco-passage-dev-subset')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+    def test_msmarco_passage_tct_colbert_v2_hn_encoded_queries(self):
+        encoded = QueryEncoder.load_encoded_queries('tct_colbert-v2-hn-msmarco-passage-dev-subset')
+        topics = get_topics('msmarco-passage-dev-subset')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+    def test_msmarco_passage_tct_colbert_v2_hnp_encoded_queries(self):
+        encoded = QueryEncoder.load_encoded_queries('tct_colbert-v2-hnp-msmarco-passage-dev-subset')
+        topics = get_topics('msmarco-passage-dev-subset')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+    def test_msmarco_passage_sbert_encoded_queries(self):
+        encoded = QueryEncoder.load_encoded_queries('sbert-msmarco-passage-dev-subset')
+        topics = get_topics('msmarco-passage-dev-subset')
+        for t in topics:
+            self.assertTrue(topics[t]['title'] in encoded.embedding)
+
+
+if __name__ == '__main__':
+    unittest.main()
diff --git a/tests/test_load_topics.py b/tests/test_load_queries.py
similarity index 100%
rename from tests/test_load_topics.py
rename to tests/test_load_queries.py