Added Build Infinity

.history/docs/benchmark_20231226133852.md

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+# 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

.history/docs/benchmark_20231226140016.md

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+# 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

.history/docs/benchmark_20231226140905.md

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+# 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

.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