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NUMA Benchmarks for the Lecture "Trends and Concepts in the Software Industry I" at HPI

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WGierke/tuk1_numa_a

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TuK NUMA Benchmarks

Setup

Requires libnuma, so it will only compile on Linux; for macOS you can use a Docker container (see below).

  1. Requirements: gcc, cmake, libnuma-dev
  2. Clone this repository and cd into it
  3. mkdir build && cd build
  4. cmake -G 'Unix Makefiles' -DCMAKE_BUILD_TYPE=Release .. (or set build type to Debug if needed)
  5. make -j8
  6. Run ./src/tuk_numa_benchmark

Develop with a Docker container (e.g. on macOS)

  1. Assuming docker is installed https://store.docker.com/editions/community/docker-ce-desktop-mac
  2. Build a docker image using the included Dockerfile: cd <repo> && docker build -t tuk-numa ./docker
  3. After creating the build directory, you can run CMake and make inside a container, e.g.:
docker run --rm \
    -v `pwd`:`pwd` \
    -w `pwd`/build \
    tuk-numa /bin/bash -c "cmake -G 'Unix Makefiles' -DCMAKE_BUILD_TYPE=Debug .."
  1. Because all this seems pretty tedious to type, I've set up a task and debug configuration for Visual Studio Code:
    1. Once you've opened the repo folder in VS Code
    2. Press Cmd-Shift-P and select "Tasks: Run Task" to build the docker image and initialize the CMake build directory
    3. Compile the project with Cmd-Shift-B
    4. Set a breakpoint and start debugging in VS Code, or select "Run Test Task" from the Cmd-Shift-P menu to run without a debugger

Results

Based on 7 computations (took 9 hours)

Task 1

columnscan_20m columnscan_100m rowscan_20m rowscan_100m

Task 2

join_20m_2000 join_20m_20000 join_20m_200000 join_20m_2000000 join_100m_2000 join_100m_20000 join_100m_200000 join_100m_2000000 join_local_20m join_local_100m join_local_remote_20m join_local_remote_100m join_same_remote_20m join_same_remote_100m join_different_remote_20m join_different_remote_100m

Task 3

query_plots

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NUMA Benchmarks for the Lecture "Trends and Concepts in the Software Industry I" at HPI

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