in powershell

$manifest = (Get-AppxPackage Microsoft.WindowsStore).InstallLocation + '\AppxManifest.xml' ; Add-AppxPackage -DisableDevelopmentMode -Register $manifest

url: https://github.com/tensorflow/tensorflow/issues/30227

https://github.com/tensorflow/tensorflow/issues/30227#issuecomment-506783788

Searching deeply, I found that the first timestep is also used to determine the cell output shape and its dtype.

(py3-tf2-gpu) sephiroce@bike:/usr/local/cuda/samples/5_Simulations/nbody$ ./nbody -benchmark -numbodies=2560000 -device=0

Run "nbody -benchmark [-numbodies=]" to measure performance.

-fullscreen (run n-body simulation in fullscreen mode)

-fp64 (use double precision floating point values for simulation)

-hostmem (stores simulation data in host memory)

-benchmark (run benchmark to measure performance)

-numbodies= (number of bodies (>= 1) to run in simulation)

-device= (where d=0,1,2.... for the CUDA device to use)

-numdevices= (where i=(number of CUDA devices > 0) to use for simulation)

-compare (compares simulation results running once on the default GPU and once on the CPU)

-cpu (run n-body simulation on the CPU)

-tipsy= (load a tipsy model file for simulation)

NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.

> Windowed mode

> Simulation data stored in video memory

> Single precision floating point simulation

> 1 Devices used for simulation

gpuDeviceInit() CUDA Device [0]: "Ampere

> Compute 8.6 CUDA device: [GeForce RTX 3090]

number of bodies = 2560000

2560000 bodies, total time for 10 iterations: 69005.547 ms

= 949.721 billion interactions per second

= 18994.415 single-precision GFLOP/s at 20 flops per interaction

1. install boost using python3

ref: https://github.com/pupil-labs/pupil/issues/874, huangjiancong1

tar -xzvf boost_1_65_1.tar.gz

cd boost_1_65_1

echo "using mpi ;

using gcc : : g++ ;

using python : 3.6 : /usr/bin/python3 : /usr/include/python3.6m : /usr/local/lib ;" > ~/user-config.jam

./bootstrap.sh --with-python=/usr/bin/python3 --with-python-version=3.6 --with-python-root=/usr/local/lib/python3.6 --prefix=/usr/local

sudo ./b2 install -a --with=all

2. install rdkit

modifying CMakeList boost version 1.5.1 to the installed version of boost.

change all the path below!

cmake version needs to be ~= 3.1

cmake -DPYTHON_LIBRARY=/usr/lib/python3.6/config/libpython3.6.a \

-DPYTHON_INCLUDE_DIR=/usr/include/python3.6/ \

-DPYTHON_EXECUTABLE=/usr/bin/python3 \

-DBOOST_LIBRARIES=libboost_python3.so.1.65.1 \

-DBoost_INCLUDE_DIR=include_foldr ..

3. Add rdkitpath to PYTHONPATH, libpath to LD_LIBRARY_PATH