From 8731d137c54d5d7911583a6240b7ce44813867f1 Mon Sep 17 00:00:00 2001
From: Vissidarte-Herman <cai.keith@gmail.com>
Date: Tue, 26 Dec 2023 13:44:28 +0800
Subject: [PATCH 1/7] Added a benchmark report on sift

---
 docs/benchmark.md | 25 ++++++++++++++++---------
 1 file changed, 16 insertions(+), 9 deletions(-)

diff --git a/docs/benchmark.md b/docs/benchmark.md
index c8f50edf0a..a41223fcc3 100644
--- a/docs/benchmark.md
+++ b/docs/benchmark.md
@@ -1,6 +1,6 @@
 # Benchmark
 
-**Infinity** provides Python script for sift1m and gist1m dataset benchmark.
+Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
 
 ## Get the Infinity binary file
 
@@ -9,9 +9,9 @@ git clone https://github.com/infiniflow/infinity.git
 cd infinity
 ```
 
-## Download the benchmark file
+## Download the benchmark files
 
-Download via wget.
+To obtain the benchmark files, you have the option to download them using the wget command.
 
 ```sh
 #download sift benchmark
@@ -21,16 +21,16 @@ wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
 
 ```
 
-or visit [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/) to download manually.
+Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
 
 ```sh
-#uncompress and move benchmark file
+# Unzip and move the SIFT1M benchmark file.
 tar -zxvf sift.tar.gz
 mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
 mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
 mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
 
-
+# Unzip and move the GIST1M benchmark file.
 tar -zxvf gist.tar.gz
 mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
 mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
@@ -74,10 +74,17 @@ options:
   -r ROUNDS, --rounds ROUNDS
   -d DATA_SET, --data DATA_SET
 
-# ROUNDS refers to the number of times that Python runs the benchmark. The result is the average time for all runs.
+# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
 
-# The following command means run benchmark with one thread, for one time using the sift dataset.
+# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
 python remote_benchmark.py -t 1 -r 1 -d sift_1m
-
+# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
 python remote_benchmark.py -t 1 -r 1 -d gist_1m
 ```
+## A SIFT benchmark report
+
+- **Hardware**: Intel i5-12500H, 16C, 16GB
+- **Operating system**: Ubuntu 22.04
+- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
+- **QPS**: 10,305
+- **P99 Latency**: 0.3 ms
\ No newline at end of file

From 8e45122576a034a957936450cdfc665358e82b32 Mon Sep 17 00:00:00 2001
From: Vissidarte-Herman <cai.keith@gmail.com>
Date: Tue, 26 Dec 2023 14:10:21 +0800
Subject: [PATCH 2/7] Added Build Infinity

---
 .history/docs/benchmark_20231226133852.md | 90 ++++++++++++++++++++++
 .history/docs/benchmark_20231226140016.md | 92 +++++++++++++++++++++++
 .history/docs/benchmark_20231226140905.md | 86 +++++++++++++++++++++
 .history/docs/benchmark_20231226140937.md | 86 +++++++++++++++++++++
 .history/docs/benchmark_20231226141001.md | 86 +++++++++++++++++++++
 docs/benchmark.md                         | 36 ++++-----
 6 files changed, 456 insertions(+), 20 deletions(-)
 create mode 100644 .history/docs/benchmark_20231226133852.md
 create mode 100644 .history/docs/benchmark_20231226140016.md
 create mode 100644 .history/docs/benchmark_20231226140905.md
 create mode 100644 .history/docs/benchmark_20231226140937.md
 create mode 100644 .history/docs/benchmark_20231226141001.md

diff --git a/.history/docs/benchmark_20231226133852.md b/.history/docs/benchmark_20231226133852.md
new file mode 100644
index 0000000000..a41223fcc3
--- /dev/null
+++ b/.history/docs/benchmark_20231226133852.md
@@ -0,0 +1,90 @@
+# Benchmark
+
+Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
+
+## Get the Infinity binary file
+
+```sh
+git clone https://github.com/infiniflow/infinity.git
+cd infinity
+```
+
+## Download the benchmark files
+
+To obtain the benchmark files, you have the option to download them using the wget command.
+
+```sh
+#download sift benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
+#download gist benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
+
+```
+
+Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
+
+```sh
+# Unzip and move the SIFT1M benchmark file.
+tar -zxvf sift.tar.gz
+mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
+mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
+mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
+
+# Unzip and move the GIST1M benchmark file.
+tar -zxvf gist.tar.gz
+mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
+mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
+mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
+
+```
+
+## Benchmark dependencies
+
+```sh
+cd python
+
+pip install -r requirements.txt
+python setup.py bdist_wheel
+pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
+```
+
+## Start Infinity
+
+See the [README.md](https://github.com/infiniflow/infinity/blob/main/README.md) to start Infinity.
+
+## Import data
+
+```sh
+cd benchmark
+
+options:
+  -h, --help            show this help message and exit
+  -d DATA_SET, --data DATA_SET
+
+python remote_benchmark_import.py -d sift_1m
+python remote_benchmark_import.py -d gist_1m
+```
+
+## Run benchmark
+
+```sh
+options:
+  -h, --help            show this help message and exit
+  -t THREADS, --threads THREADS
+  -r ROUNDS, --rounds ROUNDS
+  -d DATA_SET, --data DATA_SET
+
+# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
+
+# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d sift_1m
+# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d gist_1m
+```
+## A SIFT benchmark report
+
+- **Hardware**: Intel i5-12500H, 16C, 16GB
+- **Operating system**: Ubuntu 22.04
+- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
+- **QPS**: 10,305
+- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226140016.md b/.history/docs/benchmark_20231226140016.md
new file mode 100644
index 0000000000..174dd1059b
--- /dev/null
+++ b/.history/docs/benchmark_20231226140016.md
@@ -0,0 +1,92 @@
+# Benchmark
+
+Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
+
+## Build Infinity
+
+You can either build Infinity 
+
+```sh
+git clone https://github.com/infiniflow/infinity.git
+cd infinity
+```
+
+## Download the Benchmark datasets
+
+To obtain the benchmark files, you have the option to download them using the wget command.
+
+```sh
+#download sift benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
+#download gist benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
+
+```
+
+Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
+
+```sh
+# Unzip and move the SIFT1M benchmark file.
+tar -zxvf sift.tar.gz
+mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
+mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
+mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
+
+# Unzip and move the GIST1M benchmark file.
+tar -zxvf gist.tar.gz
+mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
+mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
+mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
+
+```
+
+## Benchmark dependencies
+
+```sh
+cd python
+
+pip install -r requirements.txt
+python setup.py bdist_wheel
+pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
+```
+
+## Start Infinity
+
+See the [README.md](https://github.com/infiniflow/infinity/blob/main/README.md) to start Infinity.
+
+## Import the Benchmark datasets
+
+```sh
+cd benchmark
+
+options:
+  -h, --help            show this help message and exit
+  -d DATA_SET, --data DATA_SET
+
+python remote_benchmark_import.py -d sift_1m
+python remote_benchmark_import.py -d gist_1m
+```
+
+## Run Benchmark
+
+```sh
+options:
+  -h, --help            show this help message and exit
+  -t THREADS, --threads THREADS
+  -r ROUNDS, --rounds ROUNDS
+  -d DATA_SET, --data DATA_SET
+
+# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
+
+# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d sift_1m
+# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d gist_1m
+```
+## A SIFT benchmark report
+
+- **Hardware**: Intel i5-12500H, 16C, 16GB
+- **Operating system**: Ubuntu 22.04
+- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
+- **QPS**: 10,305
+- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226140905.md b/.history/docs/benchmark_20231226140905.md
new file mode 100644
index 0000000000..11805eeac9
--- /dev/null
+++ b/.history/docs/benchmark_20231226140905.md
@@ -0,0 +1,86 @@
+# Benchmark
+
+Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
+
+## Build Infinity
+
+You have two options for building Infinity. Choose the option that best fit your needs:
+
+- [Build Infinity using Docker](../README.md)
+- [Build from source](./build_from_source.md)
+
+## Download the Benchmark datasets
+
+To obtain the benchmark files, you have the option to download them using the wget command.
+
+```sh
+#download sift benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
+#download gist benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
+
+```
+
+Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
+
+```sh
+# Unzip and move the SIFT1M benchmark file.
+tar -zxvf sift.tar.gz
+mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
+mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
+mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
+
+# Unzip and move the GIST1M benchmark file.
+tar -zxvf gist.tar.gz
+mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
+mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
+mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
+
+```
+
+## Benchmark dependencies
+
+```sh
+cd python
+
+pip install -r requirements.txt
+python setup.py bdist_wheel
+pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
+```
+
+## Import the Benchmark datasets
+
+```sh
+cd benchmark
+
+options:
+  -h, --help            show this help message and exit
+  -d DATA_SET, --data DATA_SET
+
+python remote_benchmark_import.py -d sift_1m
+python remote_benchmark_import.py -d gist_1m
+```
+
+## Run Benchmark
+
+```sh
+options:
+  -h, --help            show this help message and exit
+  -t THREADS, --threads THREADS
+  -r ROUNDS, --rounds ROUNDS
+  -d DATA_SET, --data DATA_SET
+
+# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
+
+# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d sift_1m
+# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d gist_1m
+```
+## A SIFT benchmark report
+
+- **Hardware**: Intel i5-12500H, 16C, 16GB
+- **Operating system**: Ubuntu 22.04
+- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
+- **QPS**: 10,305
+- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226140937.md b/.history/docs/benchmark_20231226140937.md
new file mode 100644
index 0000000000..b6d8b2f98e
--- /dev/null
+++ b/.history/docs/benchmark_20231226140937.md
@@ -0,0 +1,86 @@
+# Benchmark
+
+Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
+
+## Build Infinity
+
+You have two options for building Infinity. Choose the option that best fit your needs:
+
+- [Build Infinity using Docker](../README.md)
+- [Build from source](./build_from_source.md)
+
+## Download the Benchmark datasets
+
+To obtain the benchmark files, you have the option to download them using the wget command.
+
+```sh
+#download sift benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
+#download gist benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
+
+```
+
+Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
+
+```sh
+# Unzip and move the SIFT1M benchmark file.
+tar -zxvf sift.tar.gz
+mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
+mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
+mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
+
+# Unzip and move the GIST1M benchmark file.
+tar -zxvf gist.tar.gz
+mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
+mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
+mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
+
+```
+
+## Benchmark dependencies
+
+```sh
+cd python
+
+pip install -r requirements.txt
+python setup.py bdist_wheel
+pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
+```
+
+## Import the Benchmark datasets
+
+```sh
+cd benchmark
+
+# options:
+#   -h, --help            show this help message and exit
+#   -d DATA_SET, --data DATA_SET
+
+python remote_benchmark_import.py -d sift_1m
+python remote_benchmark_import.py -d gist_1m
+```
+
+## Run Benchmark
+
+```sh
+# options:
+#   -h, --help            show this help message and exit
+#   -t THREADS, --threads THREADS
+#   -r ROUNDS, --rounds ROUNDS
+#   -d DATA_SET, --data DATA_SET
+
+# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
+
+# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d sift_1m
+# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d gist_1m
+```
+## A SIFT benchmark report
+
+- **Hardware**: Intel i5-12500H, 16C, 16GB
+- **Operating system**: Ubuntu 22.04
+- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
+- **QPS**: 10,305
+- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226141001.md b/.history/docs/benchmark_20231226141001.md
new file mode 100644
index 0000000000..0e223fbbdd
--- /dev/null
+++ b/.history/docs/benchmark_20231226141001.md
@@ -0,0 +1,86 @@
+# Benchmark
+
+Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
+
+## Build Infinity
+
+You have two options for building Infinity. Choose the option that best fits your needs:
+
+- [Build Infinity using Docker](../README.md)
+- [Build from source](./build_from_source.md)
+
+## Download the Benchmark datasets
+
+To obtain the benchmark files, you have the option to download them using the wget command.
+
+```sh
+#download sift benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
+#download gist benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
+
+```
+
+Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
+
+```sh
+# Unzip and move the SIFT1M benchmark file.
+tar -zxvf sift.tar.gz
+mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
+mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
+mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
+
+# Unzip and move the GIST1M benchmark file.
+tar -zxvf gist.tar.gz
+mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
+mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
+mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
+
+```
+
+## Benchmark dependencies
+
+```sh
+cd python
+
+pip install -r requirements.txt
+python setup.py bdist_wheel
+pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
+```
+
+## Import the Benchmark datasets
+
+```sh
+cd benchmark
+
+# options:
+#   -h, --help            show this help message and exit
+#   -d DATA_SET, --data DATA_SET
+
+python remote_benchmark_import.py -d sift_1m
+python remote_benchmark_import.py -d gist_1m
+```
+
+## Run Benchmark
+
+```sh
+# options:
+#   -h, --help            show this help message and exit
+#   -t THREADS, --threads THREADS
+#   -r ROUNDS, --rounds ROUNDS
+#   -d DATA_SET, --data DATA_SET
+
+# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
+
+# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d sift_1m
+# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d gist_1m
+```
+## A SIFT benchmark report
+
+- **Hardware**: Intel i5-12500H, 16C, 16GB
+- **Operating system**: Ubuntu 22.04
+- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
+- **QPS**: 10,305
+- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/docs/benchmark.md b/docs/benchmark.md
index a41223fcc3..0e223fbbdd 100644
--- a/docs/benchmark.md
+++ b/docs/benchmark.md
@@ -2,14 +2,14 @@
 
 Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
 
-## Get the Infinity binary file
+## Build Infinity
 
-```sh
-git clone https://github.com/infiniflow/infinity.git
-cd infinity
-```
+You have two options for building Infinity. Choose the option that best fits your needs:
+
+- [Build Infinity using Docker](../README.md)
+- [Build from source](./build_from_source.md)
 
-## Download the benchmark files
+## Download the Benchmark datasets
 
 To obtain the benchmark files, you have the option to download them using the wget command.
 
@@ -48,31 +48,27 @@ python setup.py bdist_wheel
 pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
 ```
 
-## Start Infinity
-
-See the [README.md](https://github.com/infiniflow/infinity/blob/main/README.md) to start Infinity.
-
-## Import data
+## Import the Benchmark datasets
 
 ```sh
 cd benchmark
 
-options:
-  -h, --help            show this help message and exit
-  -d DATA_SET, --data DATA_SET
+# options:
+#   -h, --help            show this help message and exit
+#   -d DATA_SET, --data DATA_SET
 
 python remote_benchmark_import.py -d sift_1m
 python remote_benchmark_import.py -d gist_1m
 ```
 
-## Run benchmark
+## Run Benchmark
 
 ```sh
-options:
-  -h, --help            show this help message and exit
-  -t THREADS, --threads THREADS
-  -r ROUNDS, --rounds ROUNDS
-  -d DATA_SET, --data DATA_SET
+# options:
+#   -h, --help            show this help message and exit
+#   -t THREADS, --threads THREADS
+#   -r ROUNDS, --rounds ROUNDS
+#   -d DATA_SET, --data DATA_SET
 
 # ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
 

From e91abdd44e25a5aef651e8add4ee69e56b60f26f Mon Sep 17 00:00:00 2001
From: Vissidarte-Herman <cai.keith@gmail.com>
Date: Tue, 26 Dec 2023 14:13:10 +0800
Subject: [PATCH 3/7] Removed history

---
 .history/docs/benchmark_20231226133852.md | 90 ----------------------
 .history/docs/benchmark_20231226140016.md | 92 -----------------------
 .history/docs/benchmark_20231226140905.md | 86 ---------------------
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 .history/docs/benchmark_20231226141001.md | 86 ---------------------
 5 files changed, 440 deletions(-)
 delete mode 100644 .history/docs/benchmark_20231226133852.md
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diff --git a/.history/docs/benchmark_20231226133852.md b/.history/docs/benchmark_20231226133852.md
deleted file mode 100644
index a41223fcc3..0000000000
--- a/.history/docs/benchmark_20231226133852.md
+++ /dev/null
@@ -1,90 +0,0 @@
-# Benchmark
-
-Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
-
-## Get the Infinity binary file
-
-```sh
-git clone https://github.com/infiniflow/infinity.git
-cd infinity
-```
-
-## Download the benchmark files
-
-To obtain the benchmark files, you have the option to download them using the wget command.
-
-```sh
-#download sift benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
-#download gist benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
-
-```
-
-Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
-
-```sh
-# Unzip and move the SIFT1M benchmark file.
-tar -zxvf sift.tar.gz
-mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
-mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
-mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
-
-# Unzip and move the GIST1M benchmark file.
-tar -zxvf gist.tar.gz
-mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
-mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
-mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
-
-```
-
-## Benchmark dependencies
-
-```sh
-cd python
-
-pip install -r requirements.txt
-python setup.py bdist_wheel
-pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
-```
-
-## Start Infinity
-
-See the [README.md](https://github.com/infiniflow/infinity/blob/main/README.md) to start Infinity.
-
-## Import data
-
-```sh
-cd benchmark
-
-options:
-  -h, --help            show this help message and exit
-  -d DATA_SET, --data DATA_SET
-
-python remote_benchmark_import.py -d sift_1m
-python remote_benchmark_import.py -d gist_1m
-```
-
-## Run benchmark
-
-```sh
-options:
-  -h, --help            show this help message and exit
-  -t THREADS, --threads THREADS
-  -r ROUNDS, --rounds ROUNDS
-  -d DATA_SET, --data DATA_SET
-
-# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
-
-# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d sift_1m
-# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d gist_1m
-```
-## A SIFT benchmark report
-
-- **Hardware**: Intel i5-12500H, 16C, 16GB
-- **Operating system**: Ubuntu 22.04
-- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
-- **QPS**: 10,305
-- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226140016.md b/.history/docs/benchmark_20231226140016.md
deleted file mode 100644
index 174dd1059b..0000000000
--- a/.history/docs/benchmark_20231226140016.md
+++ /dev/null
@@ -1,92 +0,0 @@
-# Benchmark
-
-Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
-
-## Build Infinity
-
-You can either build Infinity 
-
-```sh
-git clone https://github.com/infiniflow/infinity.git
-cd infinity
-```
-
-## Download the Benchmark datasets
-
-To obtain the benchmark files, you have the option to download them using the wget command.
-
-```sh
-#download sift benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
-#download gist benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
-
-```
-
-Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
-
-```sh
-# Unzip and move the SIFT1M benchmark file.
-tar -zxvf sift.tar.gz
-mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
-mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
-mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
-
-# Unzip and move the GIST1M benchmark file.
-tar -zxvf gist.tar.gz
-mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
-mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
-mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
-
-```
-
-## Benchmark dependencies
-
-```sh
-cd python
-
-pip install -r requirements.txt
-python setup.py bdist_wheel
-pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
-```
-
-## Start Infinity
-
-See the [README.md](https://github.com/infiniflow/infinity/blob/main/README.md) to start Infinity.
-
-## Import the Benchmark datasets
-
-```sh
-cd benchmark
-
-options:
-  -h, --help            show this help message and exit
-  -d DATA_SET, --data DATA_SET
-
-python remote_benchmark_import.py -d sift_1m
-python remote_benchmark_import.py -d gist_1m
-```
-
-## Run Benchmark
-
-```sh
-options:
-  -h, --help            show this help message and exit
-  -t THREADS, --threads THREADS
-  -r ROUNDS, --rounds ROUNDS
-  -d DATA_SET, --data DATA_SET
-
-# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
-
-# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d sift_1m
-# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d gist_1m
-```
-## A SIFT benchmark report
-
-- **Hardware**: Intel i5-12500H, 16C, 16GB
-- **Operating system**: Ubuntu 22.04
-- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
-- **QPS**: 10,305
-- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226140905.md b/.history/docs/benchmark_20231226140905.md
deleted file mode 100644
index 11805eeac9..0000000000
--- a/.history/docs/benchmark_20231226140905.md
+++ /dev/null
@@ -1,86 +0,0 @@
-# Benchmark
-
-Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
-
-## Build Infinity
-
-You have two options for building Infinity. Choose the option that best fit your needs:
-
-- [Build Infinity using Docker](../README.md)
-- [Build from source](./build_from_source.md)
-
-## Download the Benchmark datasets
-
-To obtain the benchmark files, you have the option to download them using the wget command.
-
-```sh
-#download sift benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
-#download gist benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
-
-```
-
-Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
-
-```sh
-# Unzip and move the SIFT1M benchmark file.
-tar -zxvf sift.tar.gz
-mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
-mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
-mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
-
-# Unzip and move the GIST1M benchmark file.
-tar -zxvf gist.tar.gz
-mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
-mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
-mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
-
-```
-
-## Benchmark dependencies
-
-```sh
-cd python
-
-pip install -r requirements.txt
-python setup.py bdist_wheel
-pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
-```
-
-## Import the Benchmark datasets
-
-```sh
-cd benchmark
-
-options:
-  -h, --help            show this help message and exit
-  -d DATA_SET, --data DATA_SET
-
-python remote_benchmark_import.py -d sift_1m
-python remote_benchmark_import.py -d gist_1m
-```
-
-## Run Benchmark
-
-```sh
-options:
-  -h, --help            show this help message and exit
-  -t THREADS, --threads THREADS
-  -r ROUNDS, --rounds ROUNDS
-  -d DATA_SET, --data DATA_SET
-
-# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
-
-# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d sift_1m
-# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d gist_1m
-```
-## A SIFT benchmark report
-
-- **Hardware**: Intel i5-12500H, 16C, 16GB
-- **Operating system**: Ubuntu 22.04
-- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
-- **QPS**: 10,305
-- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226140937.md b/.history/docs/benchmark_20231226140937.md
deleted file mode 100644
index b6d8b2f98e..0000000000
--- a/.history/docs/benchmark_20231226140937.md
+++ /dev/null
@@ -1,86 +0,0 @@
-# Benchmark
-
-Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
-
-## Build Infinity
-
-You have two options for building Infinity. Choose the option that best fit your needs:
-
-- [Build Infinity using Docker](../README.md)
-- [Build from source](./build_from_source.md)
-
-## Download the Benchmark datasets
-
-To obtain the benchmark files, you have the option to download them using the wget command.
-
-```sh
-#download sift benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
-#download gist benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
-
-```
-
-Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
-
-```sh
-# Unzip and move the SIFT1M benchmark file.
-tar -zxvf sift.tar.gz
-mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
-mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
-mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
-
-# Unzip and move the GIST1M benchmark file.
-tar -zxvf gist.tar.gz
-mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
-mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
-mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
-
-```
-
-## Benchmark dependencies
-
-```sh
-cd python
-
-pip install -r requirements.txt
-python setup.py bdist_wheel
-pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
-```
-
-## Import the Benchmark datasets
-
-```sh
-cd benchmark
-
-# options:
-#   -h, --help            show this help message and exit
-#   -d DATA_SET, --data DATA_SET
-
-python remote_benchmark_import.py -d sift_1m
-python remote_benchmark_import.py -d gist_1m
-```
-
-## Run Benchmark
-
-```sh
-# options:
-#   -h, --help            show this help message and exit
-#   -t THREADS, --threads THREADS
-#   -r ROUNDS, --rounds ROUNDS
-#   -d DATA_SET, --data DATA_SET
-
-# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
-
-# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d sift_1m
-# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d gist_1m
-```
-## A SIFT benchmark report
-
-- **Hardware**: Intel i5-12500H, 16C, 16GB
-- **Operating system**: Ubuntu 22.04
-- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
-- **QPS**: 10,305
-- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226141001.md b/.history/docs/benchmark_20231226141001.md
deleted file mode 100644
index 0e223fbbdd..0000000000
--- a/.history/docs/benchmark_20231226141001.md
+++ /dev/null
@@ -1,86 +0,0 @@
-# Benchmark
-
-Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
-
-## Build Infinity
-
-You have two options for building Infinity. Choose the option that best fits your needs:
-
-- [Build Infinity using Docker](../README.md)
-- [Build from source](./build_from_source.md)
-
-## Download the Benchmark datasets
-
-To obtain the benchmark files, you have the option to download them using the wget command.
-
-```sh
-#download sift benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
-#download gist benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
-
-```
-
-Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
-
-```sh
-# Unzip and move the SIFT1M benchmark file.
-tar -zxvf sift.tar.gz
-mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
-mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
-mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
-
-# Unzip and move the GIST1M benchmark file.
-tar -zxvf gist.tar.gz
-mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
-mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
-mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
-
-```
-
-## Benchmark dependencies
-
-```sh
-cd python
-
-pip install -r requirements.txt
-python setup.py bdist_wheel
-pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
-```
-
-## Import the Benchmark datasets
-
-```sh
-cd benchmark
-
-# options:
-#   -h, --help            show this help message and exit
-#   -d DATA_SET, --data DATA_SET
-
-python remote_benchmark_import.py -d sift_1m
-python remote_benchmark_import.py -d gist_1m
-```
-
-## Run Benchmark
-
-```sh
-# options:
-#   -h, --help            show this help message and exit
-#   -t THREADS, --threads THREADS
-#   -r ROUNDS, --rounds ROUNDS
-#   -d DATA_SET, --data DATA_SET
-
-# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
-
-# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d sift_1m
-# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d gist_1m
-```
-## A SIFT benchmark report
-
-- **Hardware**: Intel i5-12500H, 16C, 16GB
-- **Operating system**: Ubuntu 22.04
-- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
-- **QPS**: 10,305
-- **P99 Latency**: 0.3 ms
\ No newline at end of file

From 30ede4dbb470e8f2ec6d29f1804e5823434901d8 Mon Sep 17 00:00:00 2001
From: Vissidarte-Herman <cai.keith@gmail.com>
Date: Tue, 26 Dec 2023 14:22:26 +0800
Subject: [PATCH 4/7] minor updates

---
 .history/docs/benchmark_20231226141000.md | 86 +++++++++++++++++++++++
 .history/docs/benchmark_20231226141737.md | 86 +++++++++++++++++++++++
 .history/docs/benchmark_20231226142212.md | 86 +++++++++++++++++++++++
 docs/benchmark.md                         |  4 +-
 4 files changed, 260 insertions(+), 2 deletions(-)
 create mode 100644 .history/docs/benchmark_20231226141000.md
 create mode 100644 .history/docs/benchmark_20231226141737.md
 create mode 100644 .history/docs/benchmark_20231226142212.md

diff --git a/.history/docs/benchmark_20231226141000.md b/.history/docs/benchmark_20231226141000.md
new file mode 100644
index 0000000000..0e223fbbdd
--- /dev/null
+++ b/.history/docs/benchmark_20231226141000.md
@@ -0,0 +1,86 @@
+# Benchmark
+
+Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
+
+## Build Infinity
+
+You have two options for building Infinity. Choose the option that best fits your needs:
+
+- [Build Infinity using Docker](../README.md)
+- [Build from source](./build_from_source.md)
+
+## Download the Benchmark datasets
+
+To obtain the benchmark files, you have the option to download them using the wget command.
+
+```sh
+#download sift benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
+#download gist benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
+
+```
+
+Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
+
+```sh
+# Unzip and move the SIFT1M benchmark file.
+tar -zxvf sift.tar.gz
+mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
+mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
+mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
+
+# Unzip and move the GIST1M benchmark file.
+tar -zxvf gist.tar.gz
+mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
+mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
+mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
+
+```
+
+## Benchmark dependencies
+
+```sh
+cd python
+
+pip install -r requirements.txt
+python setup.py bdist_wheel
+pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
+```
+
+## Import the Benchmark datasets
+
+```sh
+cd benchmark
+
+# options:
+#   -h, --help            show this help message and exit
+#   -d DATA_SET, --data DATA_SET
+
+python remote_benchmark_import.py -d sift_1m
+python remote_benchmark_import.py -d gist_1m
+```
+
+## Run Benchmark
+
+```sh
+# options:
+#   -h, --help            show this help message and exit
+#   -t THREADS, --threads THREADS
+#   -r ROUNDS, --rounds ROUNDS
+#   -d DATA_SET, --data DATA_SET
+
+# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
+
+# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d sift_1m
+# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d gist_1m
+```
+## A SIFT benchmark report
+
+- **Hardware**: Intel i5-12500H, 16C, 16GB
+- **Operating system**: Ubuntu 22.04
+- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
+- **QPS**: 10,305
+- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226141737.md b/.history/docs/benchmark_20231226141737.md
new file mode 100644
index 0000000000..5ec5178e0e
--- /dev/null
+++ b/.history/docs/benchmark_20231226141737.md
@@ -0,0 +1,86 @@
+# Benchmark
+
+Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
+
+## Build and start Infinity
+
+You have two options for building Infinity. Choose the option that best fits your needs:
+
+- [Build Infinity using Docker](../README.md)
+- [Build from source](./build_from_source.md)
+
+## Download the Benchmark datasets
+
+To obtain the benchmark files, you have the option to download them using the wget command.
+
+```sh
+#download sift benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
+#download gist benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
+
+```
+
+Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
+
+```sh
+# Unzip and move the SIFT1M benchmark file.
+tar -zxvf sift.tar.gz
+mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
+mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
+mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
+
+# Unzip and move the GIST1M benchmark file.
+tar -zxvf gist.tar.gz
+mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
+mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
+mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
+
+```
+
+## Benchmark dependencies
+
+```sh
+cd python
+
+pip install -r requirements.txt
+python setup.py bdist_wheel
+pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
+```
+
+## Import the Benchmark datasets
+
+```sh
+cd benchmark
+
+# options:
+#   -h, --help            show this help message and exit
+#   -d DATA_SET, --data DATA_SET
+
+python remote_benchmark_import.py -d sift_1m
+python remote_benchmark_import.py -d gist_1m
+```
+
+## Run Benchmark
+
+```sh
+# options:
+#   -h, --help            show this help message and exit
+#   -t THREADS, --threads THREADS
+#   -r ROUNDS, --rounds ROUNDS
+#   -d DATA_SET, --data DATA_SET
+
+# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
+
+# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d sift_1m
+# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d gist_1m
+```
+## A SIFT benchmark report
+
+- **Hardware**: Intel i5-12500H, 16C, 16GB
+- **Operating system**: Ubuntu 22.04
+- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
+- **QPS**: 10,305
+- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226142212.md b/.history/docs/benchmark_20231226142212.md
new file mode 100644
index 0000000000..8e20691e8b
--- /dev/null
+++ b/.history/docs/benchmark_20231226142212.md
@@ -0,0 +1,86 @@
+# Benchmark
+
+Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
+
+## Build and start Infinity
+
+You have two options for building Infinity. Choose the option that best fits your needs:
+
+- [Build Infinity using Docker](../README.md)
+- [Build from source](./build_from_source.md)
+
+## Download the Benchmark datasets
+
+To obtain the benchmark files, you have the option to download them using the wget command.
+
+```sh
+#download sift benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
+#download gist benchmark
+wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
+
+```
+
+Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
+
+```sh
+# Unzip and move the SIFT1M benchmark file.
+tar -zxvf sift.tar.gz
+mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
+mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
+mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
+
+# Unzip and move the GIST1M benchmark file.
+tar -zxvf gist.tar.gz
+mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
+mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
+mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
+
+```
+
+## Benchmark dependencies
+
+```sh
+cd python
+
+pip install -r requirements.txt
+python setup.py bdist_wheel
+pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
+```
+
+## Import the Benchmark datasets
+
+```sh
+cd benchmark
+
+# options:
+#   -h, --help            show this help message and exit
+#   -d DATA_SET, --data DATA_SET
+
+python remote_benchmark_import.py -d sift_1m
+python remote_benchmark_import.py -d gist_1m
+```
+
+## Run Benchmark
+
+```sh
+# options:
+#   -h, --help            show this help message and exit
+#   -t THREADS, --threads THREADS
+#   -r ROUNDS, --rounds ROUNDS
+#   -d DATA_SET, --data DATA_SET
+
+# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
+
+# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d sift_1m
+# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
+python remote_benchmark.py -t 1 -r 1 -d gist_1m
+```
+## A SIFT1M Benchmark report
+
+- **Hardware**: Intel i5-12500H, 16C, 16GB
+- **Operating system**: Ubuntu 22.04
+- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
+- **QPS**: 10,305
+- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/docs/benchmark.md b/docs/benchmark.md
index 0e223fbbdd..8e20691e8b 100644
--- a/docs/benchmark.md
+++ b/docs/benchmark.md
@@ -2,7 +2,7 @@
 
 Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
 
-## Build Infinity
+## Build and start Infinity
 
 You have two options for building Infinity. Choose the option that best fits your needs:
 
@@ -77,7 +77,7 @@ python remote_benchmark.py -t 1 -r 1 -d sift_1m
 # Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
 python remote_benchmark.py -t 1 -r 1 -d gist_1m
 ```
-## A SIFT benchmark report
+## A SIFT1M Benchmark report
 
 - **Hardware**: Intel i5-12500H, 16C, 16GB
 - **Operating system**: Ubuntu 22.04

From 30938a38d7655e3d4699992a7be9c562c56899ab Mon Sep 17 00:00:00 2001
From: Vissidarte-Herman <cai.keith@gmail.com>
Date: Tue, 26 Dec 2023 14:23:35 +0800
Subject: [PATCH 5/7] minor updates

---
 .history/docs/benchmark_20231226141000.md | 86 -----------------------
 .history/docs/benchmark_20231226141737.md | 86 -----------------------
 .history/docs/benchmark_20231226142212.md | 86 -----------------------
 3 files changed, 258 deletions(-)
 delete mode 100644 .history/docs/benchmark_20231226141000.md
 delete mode 100644 .history/docs/benchmark_20231226141737.md
 delete mode 100644 .history/docs/benchmark_20231226142212.md

diff --git a/.history/docs/benchmark_20231226141000.md b/.history/docs/benchmark_20231226141000.md
deleted file mode 100644
index 0e223fbbdd..0000000000
--- a/.history/docs/benchmark_20231226141000.md
+++ /dev/null
@@ -1,86 +0,0 @@
-# Benchmark
-
-Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
-
-## Build Infinity
-
-You have two options for building Infinity. Choose the option that best fits your needs:
-
-- [Build Infinity using Docker](../README.md)
-- [Build from source](./build_from_source.md)
-
-## Download the Benchmark datasets
-
-To obtain the benchmark files, you have the option to download them using the wget command.
-
-```sh
-#download sift benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
-#download gist benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
-
-```
-
-Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
-
-```sh
-# Unzip and move the SIFT1M benchmark file.
-tar -zxvf sift.tar.gz
-mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
-mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
-mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
-
-# Unzip and move the GIST1M benchmark file.
-tar -zxvf gist.tar.gz
-mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
-mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
-mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
-
-```
-
-## Benchmark dependencies
-
-```sh
-cd python
-
-pip install -r requirements.txt
-python setup.py bdist_wheel
-pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
-```
-
-## Import the Benchmark datasets
-
-```sh
-cd benchmark
-
-# options:
-#   -h, --help            show this help message and exit
-#   -d DATA_SET, --data DATA_SET
-
-python remote_benchmark_import.py -d sift_1m
-python remote_benchmark_import.py -d gist_1m
-```
-
-## Run Benchmark
-
-```sh
-# options:
-#   -h, --help            show this help message and exit
-#   -t THREADS, --threads THREADS
-#   -r ROUNDS, --rounds ROUNDS
-#   -d DATA_SET, --data DATA_SET
-
-# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
-
-# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d sift_1m
-# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d gist_1m
-```
-## A SIFT benchmark report
-
-- **Hardware**: Intel i5-12500H, 16C, 16GB
-- **Operating system**: Ubuntu 22.04
-- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
-- **QPS**: 10,305
-- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226141737.md b/.history/docs/benchmark_20231226141737.md
deleted file mode 100644
index 5ec5178e0e..0000000000
--- a/.history/docs/benchmark_20231226141737.md
+++ /dev/null
@@ -1,86 +0,0 @@
-# Benchmark
-
-Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
-
-## Build and start Infinity
-
-You have two options for building Infinity. Choose the option that best fits your needs:
-
-- [Build Infinity using Docker](../README.md)
-- [Build from source](./build_from_source.md)
-
-## Download the Benchmark datasets
-
-To obtain the benchmark files, you have the option to download them using the wget command.
-
-```sh
-#download sift benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
-#download gist benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
-
-```
-
-Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
-
-```sh
-# Unzip and move the SIFT1M benchmark file.
-tar -zxvf sift.tar.gz
-mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
-mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
-mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
-
-# Unzip and move the GIST1M benchmark file.
-tar -zxvf gist.tar.gz
-mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
-mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
-mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
-
-```
-
-## Benchmark dependencies
-
-```sh
-cd python
-
-pip install -r requirements.txt
-python setup.py bdist_wheel
-pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
-```
-
-## Import the Benchmark datasets
-
-```sh
-cd benchmark
-
-# options:
-#   -h, --help            show this help message and exit
-#   -d DATA_SET, --data DATA_SET
-
-python remote_benchmark_import.py -d sift_1m
-python remote_benchmark_import.py -d gist_1m
-```
-
-## Run Benchmark
-
-```sh
-# options:
-#   -h, --help            show this help message and exit
-#   -t THREADS, --threads THREADS
-#   -r ROUNDS, --rounds ROUNDS
-#   -d DATA_SET, --data DATA_SET
-
-# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
-
-# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d sift_1m
-# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d gist_1m
-```
-## A SIFT benchmark report
-
-- **Hardware**: Intel i5-12500H, 16C, 16GB
-- **Operating system**: Ubuntu 22.04
-- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
-- **QPS**: 10,305
-- **P99 Latency**: 0.3 ms
\ No newline at end of file
diff --git a/.history/docs/benchmark_20231226142212.md b/.history/docs/benchmark_20231226142212.md
deleted file mode 100644
index 8e20691e8b..0000000000
--- a/.history/docs/benchmark_20231226142212.md
+++ /dev/null
@@ -1,86 +0,0 @@
-# Benchmark
-
-Infinity provides a Python script for benchmarking the SIFT1M and GIST1M datasets.
-
-## Build and start Infinity
-
-You have two options for building Infinity. Choose the option that best fits your needs:
-
-- [Build Infinity using Docker](../README.md)
-- [Build from source](./build_from_source.md)
-
-## Download the Benchmark datasets
-
-To obtain the benchmark files, you have the option to download them using the wget command.
-
-```sh
-#download sift benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/sift.tar.gz
-#download gist benchmark
-wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
-
-```
-
-Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
-
-```sh
-# Unzip and move the SIFT1M benchmark file.
-tar -zxvf sift.tar.gz
-mv sift/sift_base.fvecs test/data/benchmark/sift_1m/sift_base.fvecs
-mv sift/sift_query.fvecs test/data/benchmark/sift_1m/sift_query.fvecs
-mv sift/sift_groundtruth.ivecs test/data/benchmark/sift_1m/sift_groundtruth.ivecs
-
-# Unzip and move the GIST1M benchmark file.
-tar -zxvf gist.tar.gz
-mv gist/gist_base.fvecs test/data/benchmark/gist_1m/gist_base.fvecs
-mv gist/gist_query.fvecs test/data/benchmark/gist_1m/gist_query.fvecs
-mv gist/gist_groundtruth.ivecs test/data/benchmark/gist_1m/gist_groundtruth.ivecs
-
-```
-
-## Benchmark dependencies
-
-```sh
-cd python
-
-pip install -r requirements.txt
-python setup.py bdist_wheel
-pip install dist/infinity_sdk-0.1.0.dev1-py3-none-any.whl
-```
-
-## Import the Benchmark datasets
-
-```sh
-cd benchmark
-
-# options:
-#   -h, --help            show this help message and exit
-#   -d DATA_SET, --data DATA_SET
-
-python remote_benchmark_import.py -d sift_1m
-python remote_benchmark_import.py -d gist_1m
-```
-
-## Run Benchmark
-
-```sh
-# options:
-#   -h, --help            show this help message and exit
-#   -t THREADS, --threads THREADS
-#   -r ROUNDS, --rounds ROUNDS
-#   -d DATA_SET, --data DATA_SET
-
-# ROUNDS indicates the number of times Python executes the benchmark, and the result represents the average duration for each run.
-
-# Perform a benchmark on the SIFT1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d sift_1m
-# Perform a benchmark on the GIST1M dataset using a single thread, running it only once.
-python remote_benchmark.py -t 1 -r 1 -d gist_1m
-```
-## A SIFT1M Benchmark report
-
-- **Hardware**: Intel i5-12500H, 16C, 16GB
-- **Operating system**: Ubuntu 22.04
-- **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
-- **QPS**: 10,305
-- **P99 Latency**: 0.3 ms
\ No newline at end of file

From e1905b8e2f53d94af699107d8c332b1fde31c5ca Mon Sep 17 00:00:00 2001
From: Vissidarte-Herman <cai.keith@gmail.com>
Date: Tue, 26 Dec 2023 14:29:10 +0800
Subject: [PATCH 6/7] Editorial updates.

---
 docs/benchmark.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/benchmark.md b/docs/benchmark.md
index 8e20691e8b..2ee2bab767 100644
--- a/docs/benchmark.md
+++ b/docs/benchmark.md
@@ -11,7 +11,7 @@ You have two options for building Infinity. Choose the option that best fits you
 
 ## Download the Benchmark datasets
 
-To obtain the benchmark files, you have the option to download them using the wget command.
+To obtain the benchmark datasets, you have the option to download them using the wget command.
 
 ```sh
 #download sift benchmark
@@ -21,7 +21,7 @@ wget ftp://ftp.irisa.fr/local/texmex/corpus/gist.tar.gz
 
 ```
 
-Alternatively, you can manually download the benchmark files by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
+Alternatively, you can manually download the benchmark datasets by visiting [http://corpus-texmex.irisa.fr/](http://corpus-texmex.irisa.fr/).
 
 ```sh
 # Unzip and move the SIFT1M benchmark file.

From d4b81a11a22dec03b2a44bb64e85bc9e25caa441 Mon Sep 17 00:00:00 2001
From: Vissidarte-Herman <cai.keith@gmail.com>
Date: Tue, 26 Dec 2023 19:29:26 +0800
Subject: [PATCH 7/7] Updated benchmark report

---
 docs/benchmark.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/benchmark.md b/docs/benchmark.md
index 2ee2bab767..42aa1e180e 100644
--- a/docs/benchmark.md
+++ b/docs/benchmark.md
@@ -83,4 +83,4 @@ python remote_benchmark.py -t 1 -r 1 -d gist_1m
 - **Operating system**: Ubuntu 22.04
 - **Dataset**: SIFT1M; **topk**: 100; **recall**: 97%+
 - **QPS**: 10,305
-- **P99 Latency**: 0.3 ms
\ No newline at end of file
+- **P99 Latency**: < 0.4 ms
\ No newline at end of file