Development

environment.yml

@@ -2,19 +2,21 @@ name: python_for_hpc
 channels:
   - defaults
 dependencies:
-  - bokeh
-  - click
+  - mpi4py
+  - python
   - cython
-  - dask
   - h5py
-  - jupyterlab
-  - mpi4py
-  - numba
   - numexpr
-  - numpy
-  - pandas
-  - python
   - scipy
-  - snakeviz
+  - pandas
   - swig
+  - dask
+  - numpy
+  - jupyterlab
+  - bokeh
+  - click
+  - numba
+  - snakeviz
+  - memory_profiler
+  - matplotlib
 prefix: /home/gjb/miniconda3/envs/python_for_hpc

source-code/gpu/cudac_linux64_conda_specs.txt

@@ -0,0 +1,181 @@
+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: linux-64
+@EXPLICIT
+https://repo.anaconda.com/pkgs/main/linux-64/nvcc_linux-64-10.1-hcaf9a05_10.conda
+https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
+https://repo.anaconda.com/pkgs/main/linux-64/blas-1.0-openblas.conda
+https://repo.anaconda.com/pkgs/main/linux-64/ca-certificates-2021.10.26-h06a4308_2.conda
+https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.36.1-hea4e1c9_2.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-11.2.0-h5c6108e_10.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-11.2.0-he4da1e4_10.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/mysql-common-8.0.25-ha770c72_2.tar.bz2
+https://conda.anaconda.org/conda-forge/linux-64/pandoc-2.14.2-h7f98852_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/tzdata-2021c-he74cb21_0.tar.bz2
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+https://conda.anaconda.org/conda-forge/noarch/jupyter_server-1.11.1-pyhd8ed1ab_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/notebook-6.4.4-pyha770c72_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/jupyterlab_server-2.8.2-pyhd8ed1ab_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/nbclassic-0.3.2-pyhd8ed1ab_0.tar.bz2
+https://conda.anaconda.org/conda-forge/noarch/jupyterlab-3.1.18-pyhd8ed1ab_0.tar.bz2

source-code/gpu/environment.yml

@@ -0,0 +1,12 @@
+name: cuda
+channels:
+  - defaults
+dependencies:
+  - pycuda
+  - jupyterlab
+  - matplotlib
+  - numpy
+  - nvcc_linux-64
+  - numba
+  - psutil
+prefix: /home/gjb/miniconda3/envs/cuda

source-code/multiprocessing/pi_futures.py

@@ -19,16 +19,14 @@ def partial_pi(args=(1000, )):
     return 4.0*nr_hits/nr_tries
 
 
-def compute_pi(nr_tries=10000, pool_size=None, constructor=None):
+def compute_pi(nr_tries=10000, pool_size=1, constructor=None):
     if not constructor:
         executor = ProcessPoolExecutor(max_workers=pool_size)
     else:
         executor = constructor(max_workers=pool_size)
     args = [(nr_tries//pool_size, )
             for _ in range(pool_size)]
     results = executor.map(partial_pi, args)
-    if not pool_size:
-        pool_size = multiprocessing.cpu_count()
     return sum(results)/pool_size
 
 
@@ -37,21 +35,29 @@ def main():
     arg_parser.add_argument('--p', dest='pool_size', type=int,
                             default=1, help='pool size')
     arg_parser.add_argument('--n', dest='nr_tries', type=int,
-                            default=1, help='number of tries')
+                            default=1000, help='number of tries')
     arg_parser.add_argument('--t', default='processes', dest='type',
                             choices=['processes', 'threads'],
                             help='Either use processes or treads')
+    arg_parser.add_argument('--verbose', action='store_true',
+                            help='generate verbose output')
     options = arg_parser.parse_args()
-    if options.type:
-        if options.type == 'processes':
-            constructor = ProcessPoolExecutor
-        else:
-            constructor = ThreadPoolExecutor
-        my_pi = compute_pi(options.nr_tries, options.pool_size, constructor)
+    if options.nr_tries//options.pool_size == 0:
+        print(f'#error: too little work, increase --n value to at least '
+              f'{options.pool_size}',
+              file=sys.stderr)
+        sys.exit(1)
+    if options.type == 'processes':
+        constructor = ProcessPoolExecutor
     else:
-        my_pi = compute_pi(options.nr_tries, options.pool_size)
-    print('computed pi = {0:.15f}'.format(my_pi))
-    print('exact pi    = {0:.15f}'.format(math.pi))
+        constructor = ThreadPoolExecutor
+    if options.verbose:
+        print(f'# running using {options.pool_size} {options.type} on '
+              f'{multiprocessing.cpu_count()} logical cores',
+              file=sys.stderr)
+    my_pi = compute_pi(options.nr_tries, options.pool_size, constructor)
+    print(f'computed pi = {my_pi:.15f}')
+    print(f'exact pi    = {math.pi:.15f}')
     return 0
 
 if __name__ == '__main__':