Python gotcha fixes + python tools submodule

.appveyor.yml

@@ -42,45 +42,23 @@ environment:
       USE_ARCH: "OFF"
       USE_PYTHON: "ON"
       BUILD_C: "ON"
+      BUILD_SHARED: "ON"
       BUILD_STATIC: "OFF"
       BUILD_TESTING: "ON"
       LINE_PROFILER: "ON"
-    - CONDA: 37
-      CPP: 14
-      CONFIG: RelWithDebInfo
-      EXAMPLES: "OFF"
-      TOOLS: "OFF"
-      WINSOCK: "OFF"
-      USE_ARCH: "OFF"
-      USE_PYTHON: "ON"
-      BUILD_C: "OFF"
-      BUILD_STATIC: "ON"
-      BUILD_TESTING: "OFF"
-      LINE_PROFILER: "ON"
-    - PYTHON: 36
+    - PYTHON: 37
       CPP: 14
       CONFIG: Debug
       EXAMPLES: "ON"
-      TOOLS: "OFF"
-      WINSOCK: "OFF"
-      USE_ARCH: "OFF"
-      USE_PYTHON: "ON"
-      BUILD_C: "ON"
-      BUILD_STATIC: "OFF"
-      BUILD_TESTING: "OFF"
-      LINE_PROFILER: "OFF"
-    - PYTHON: 37
-      CPP: 17
-      CONFIG: MinSizeRel
-      EXAMPLES: "OFF"
       TOOLS: "ON"
       WINSOCK: "OFF"
       USE_ARCH: "OFF"
       USE_PYTHON: "ON"
       BUILD_C: "OFF"
+      BUILD_SHARED: "OFF"
       BUILD_STATIC: "ON"
       BUILD_TESTING: "OFF"
-      LINE_PROFILER: "ON"
+      LINE_PROFILER: "OFF"
 
 install:
   # Configure environment
@@ -109,7 +87,7 @@ install:
           $env:PYTHON_EXE = "C:\Python$env:PYTHON\python.exe"
         }
         python -m pip install --disable-pip-version-check --user --upgrade pip wheel
-        python -m pip install --user cython numpy matplotlib pillow pandas pydot
+        python -m pip install --user matplotlib numpy pillow cython six pandas pydot multiprocess
       } elseif ($env:CONDA) {
         if ($env:PLATFORM -eq "x64") {
           $env:PATH = "C:\Miniconda$env:CONDA-x64;C:\Miniconda$env:CONDA-x64\Scripts;$env:PATH"
@@ -122,8 +100,8 @@ install:
           $env:PYTHONHOME = "C:\Miniconda$env:CONDA"
           $env:PYTHON_EXE = "C:\Miniconda$env:CONDA\python.exe"
         }
-        conda update -y -q -n base conda
-        conda install -y -c defaults -c conda-forge -q pip setuptools scikit-build numpy matplotlib pillow cython pandas pydot
+        conda update -y -n base conda
+        conda install -y -c conda-forge -c defaults matplotlib numpy pillow cython six pandas pydot multiprocess
       }
       $env:TIMEMORY_FILE_OUTPUT = "OFF"
       $env:TIMEMORY_AUTO_OUTPUT = "ON"
@@ -134,8 +112,9 @@ build_script:
   - mkdir build-timemory
   - cd build-timemory
   - cmake .. -G "%CMAKE_GENERATOR%" -A "%CMAKE_ARCH%"
-    -DBUILD_SHARED_LIBS=ON
+    -DBUILD_SHARED_LIBS="%BUILD_SHARED%"
     -DBUILD_STATIC_LIBS="%BUILD_STATIC%"
+    -DCMAKE_POSITION_INDEPENDENT_CODE=ON
     -DCMAKE_BUILD_TYPE="%CONFIG%"
     -DCMAKE_CXX_STANDARD="%CPP%"
     -DCMAKE_INSTALL_PREFIX=..\install-timemory

.readthedocs.yml

@@ -6,7 +6,7 @@ conda:
 
 python:
   setup_py_install: False
-  version: 3.6
+  version: 3.7
 
 build:
   image: latest

VERSION

@@ -1 +1 @@
-3.2.1
+3.2.2.dev0

docs/conf.py

@@ -81,6 +81,9 @@ def build_doxy_docs():
             "-DENABLE_DOXYGEN_LATEX_DOCS=OFF",
             "-DENABLE_DOXYGEN_MAN_DOCS=OFF",
             "-DTIMEMORY_BUILD_KOKKOS_TOOLS=ON",
+            "-DTIMEMORY_BUILD_C=OFF",
+            "-DTIMEMORY_BUILD_CUDA=OFF",
+            "-DTIMEMORY_BUILD_FORTRAN=OFF",
             _srcdir,
         ]
     )

docs/environment.yml

@@ -3,7 +3,7 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python=3.6
+  - python=3.7
   - cmake
   - curl
   - doxygen
@@ -18,4 +18,5 @@ dependencies:
   - setuptools
   - breathe
   - sphinx-markdown-tables
+  - docutils
 

docs/getting_started/integrating.md

@@ -42,6 +42,7 @@ were not available when timemory was installed.
 | `timemory::timemory-compile-extra` | Extra optimization flags |
 | `timemory::timemory-compile-options` | Adds the standard set of compiler flags used by timemory |
 | `timemory::timemory-compile-timing` | Adds compiler flags which report compilation timing metrics |
+| `timemory::timemory-compiler-instrument-compile-options` | INTERFACE |
 | `timemory::timemory-compiler-instrument` | Provides library for compiler instrumentation |
 | `timemory::timemory-coverage` | Enables code-coverage flags |
 | `timemory::timemory-cpu-roofline` | Enables flags and libraries for proper CPU roofline generation |
@@ -69,6 +70,7 @@ were not available when timemory was installed.
 | `timemory::timemory-hidden-visibility` | Adds -fvisibility=hidden compiler flag |
 | `timemory::timemory-instrument-functions` | Adds compiler flags to enable compile-time instrumentation |
 | `timemory::timemory-leak-sanitizer` | Adds compiler flags to enable leak sanitizer (-fsanitize=leak) |
+| `timemory::timemory-libunwind` | Enables libunwind support |
 | `timemory::timemory-likwid` | Enables LIKWID support |
 | `timemory::timemory-lto` | Adds link-time-optimization flags |
 | `timemory::timemory-mallocp-library` | Provides MALLOCP library for tracking memory allocations |
@@ -79,6 +81,7 @@ were not available when timemory was installed.
 | `timemory::timemory-ncclp-library` | Provides NCCLP library for NCCL performance analysis |
 | `timemory::timemory-no-mpi-init` | Disables the generation of MPI_Init and MPI_Init_thread symbols |
 | `timemory::timemory-null-sanitizer` | Adds compiler flags to enable null sanitizer (-fsanitize=null) |
+| `timemory::timemory-nvml` | Enables NVML support (NVIDIA) |
 | `timemory::timemory-ompt-library` | Provides OMPT library for OpenMP performance analysis |
 | `timemory::timemory-ompt` | Enables OpenMP-tools support |
 | `timemory::timemory-papi-static` | Enables PAPI support + links to static library |

docs/tools/timemory-compiler-instrument/README.md

@@ -39,6 +39,10 @@ In other words, `"TIMEMORY_FLAT_PROFILE=ON"` will not be applied to the compiler
 to enable flat profiling for the compiler instrumentation, set `"TIMEMORY_COMPILER_FLAT_PROFILE=ON"`,
 and so on for `"TIMEMORY_COMPILER_OUTPUT_PATH=..."`, etc.
 
+> **NOTE:** Environment variables `TIMEMORY_COMPILER_MAX_DEPTH`, `TIMEMORY_COMPILER_THROTTLE_COUNT`, and `TIMEMORY_COMPILER_THROTTLE_VALUE`
+> can be very useful for reducing the overhead of the instrumentation. For more information, see the descriptions provided via
+> `timemory-avail -Sd -r 'THROTTLE|MAX_DEPTH'`.
+
 ## Build
 
 Timemory provides a `timemory::timemory-compiler-instrument` target in CMake which provides the necessary

examples/ex-custom-dynamic-instr/ex_custom_dynamic_instr.cpp

@@ -23,6 +23,7 @@
 // SOFTWARE.
 //
 
+#include "timemory/components/papi/papi_tuple.hpp"
 #include "timemory/library.h"
 #include "timemory/timemory.hpp"
 

examples/ex-optional/ex_optional.cpp

@@ -123,6 +123,9 @@ int main(int argc, char** argv)
         ret_sum += ret * ret;
     }
 
+    // avoid set but unused warning
+    if(ret_sum < 0) printf("sum: %li\n", ret_sum);
+
     std::vector<long> ret_reduce;
     std::vector<long> ret_send;
     for(size_t i = 0; i < fibvalues.size(); ++i)

examples/ex-python/ex_bindings.py

@@ -1,19 +1,22 @@
 #!@PYTHON_EXECUTABLE@
 
-
+import sys
 import numpy
 import argparse
 
 use_mpi = True
 try:
     import mpi4py  # noqa: F401
     from mpi4py import MPI  # noqa: F401
+    from mpi4py.MPI import Exception as MPIException  # noqa: F401
 except ImportError:
     use_mpi = False
+    MPIException = RuntimeError
     pass
 
 import timemory  # noqa: E402
 from timemory.profiler import profile  # noqa: E402
+from timemory.tools import function_wrappers  # noqa: E402
 import libex_python_bindings as ex_bindings  # noqa: E402
 
 if use_mpi:
@@ -35,37 +38,48 @@ def run_profile(nitr=100, nsize=1000000):
 
 def run_mpi(nitr=100, nsize=1000000):
 
-    if size != 2:
-        return
+    if use_mpi is False:
+        _sum = 0.0
+        for i in range(nitr):
+            data = numpy.arange(nsize, dtype="i")
+            _val = numpy.sum(data)
+            _sum += 1.0 / _val
+            data = numpy.arange(nsize, dtype=numpy.float64)
+            _val = numpy.sum(data)
+            _sum += 1.0 / _val
 
+    msgs = set()
     for i in range(nitr):
         # passing MPI datatypes explicitly
-        if rank == 0:
-            data = numpy.arange(nsize, dtype="i")
-            comm.Send([data, MPI.INT], dest=1, tag=77)
-        elif rank == 1:
-            data = numpy.empty(nsize, dtype="i")
-            comm.Recv([data, MPI.INT], source=0, tag=77)
+        try:
+            if rank == 0:
+                data = numpy.arange(nsize, dtype="i")
+                comm.Send([data, MPI.INT], dest=1, tag=77)
+            elif rank == 1:
+                data = numpy.empty(nsize, dtype="i")
+                comm.Recv([data, MPI.INT], source=0, tag=77)
+        except MPIException as e:
+            msgs.add(f"{e}")
 
         # automatic MPI datatype discovery
-        if rank == 0:
-            data = numpy.empty(nsize, dtype=numpy.float64)
-            comm.Recv(data, source=1, tag=13)
-        elif rank == 1:
-            data = numpy.arange(nsize, dtype=numpy.float64)
-            comm.Send(data, dest=0, tag=13)
-
+        try:
+            if rank == 0 and size == 2:
+                data = numpy.empty(nsize, dtype=numpy.float64)
+                comm.Recv(data, source=1, tag=13)
+            elif rank == 1:
+                data = numpy.arange(nsize, dtype=numpy.float64)
+                comm.Send(data, dest=0, tag=13)
+        except MPIException as e:
+            msgs.add(f"{e}")
 
-def main(args):
-    # start MPI wrappers
-    id = timemory.start_mpip()
+    for i, itr in enumerate(msgs):
+        sys.stderr.write("{}: {}\n".format(i, itr))
 
-    run_mpi(args.iterations)
-    ans = run_profile(args.iterations, args.size)
 
-    # stop MPI wrappers
-    timemory.stop_mpip(id)
-    return ans
+def main(args):
+    # start function wrappers (MPI, OpenMP, etc. if available)
+    with function_wrappers(*args.profile, nccl=False):
+        return run_profile(args.iterations, args.size)
 
 
 if __name__ == "__main__":
@@ -74,40 +88,60 @@ def main(args):
     parser.add_argument(
         "-i",
         "--iterations",
-        required=False,
         default=100,
         type=int,
         help="Iterations",
     )
     parser.add_argument(
         "-n",
         "--size",
-        required=False,
         default=1000000,
         type=int,
         help="Array size",
     )
+    parser.add_argument(
+        "-c",
+        "--components",
+        default=[
+            "wall_clock",
+            "peak_rss",
+            "cpu_clock",
+            "cpu_util",
+            "thread_cpu_clock",
+            "thread_cpu_util",
+        ],
+        type=str,
+        help="Additional components",
+        nargs="*",
+    )
+    parser.add_argument(
+        "-p",
+        "--profile",
+        default=["mpi", "openmp", "malloc"],
+        choices=("mpi", "openmp", "malloc", "nccl"),
+        type=str,
+        help="Profiling library wrappers to activate",
+        nargs="*",
+    )
 
     args = parser.parse_args()
     timemory.enable_signal_detection()
-    timemory.settings.width = 12
-    timemory.settings.precision = 6
+    timemory.settings.width = 8
+    timemory.settings.precision = 2
+    timemory.settings.scientific = True
     timemory.settings.plot_output = True
-    timemory.settings.dart_output = True
+    timemory.settings.dart_output = False
+    timemory.timemory_init([__file__])
 
-    with profile(
-        [
-            "wall_clock",
-            "user_clock",
-            "system_clock",
-            "cpu_util",
-            "peak_rss",
-            "thread_cpu_clock",
-            "thread_cpu_util",
-        ]
-    ):
+    @function_wrappers(*args.profile, nccl=False)
+    def runner(nitr, nsize):
+        run_mpi(nitr, nsize)
+
+    runner(args.iterations, args.size)
+
+    with profile(args.components):
         ans = main(args)
-        print("Answer = {}".format(ans))
 
+    print("Success! Answer = {}. Finalizing...".format(ans))
     timemory.finalize()
     print("Python Finished")