# Known issues¶

In addition to the issues noted below, you can refer to our bug tracker on GitHub.

## Cannot find msvcr90d.dll¶

If you see this message coming up, find the file PythonDir\Lib\site-packages\numpy\distutils\mingw32ccompiler.py and modify the line msvcr_dbg_success = build_msvcr_library(debug=True) to read msvcr_dbg_success = False (you can comment out the existing line and add the new line immediately after).

## “Missing compiler_cxx fix for MSVCCompiler”¶

If you keep seeing this message, do not worry. It’s not possible for us to hide it, but doesn’t indicate any problems.

## Problems with numerical integration¶

In some cases, the automatic choice of numerical integration method will not be appropriate, because of a choice of parameters that couldn’t be determined in advance. In this case, typically you will get nan (not a number) values in the results, or large oscillations. In this case, Brian will generate a warning to let you know, but will not raise an error.

## Jupyter notebooks and C++ standalone mode progress reporting¶

When you run simulations in C++ standalone mode and enable progress reporting (e.g. by using report='text' as a keyword argument), the progress will not be displayed in the jupyter notebook. If you started the notebook from a terminal, you will find the output there. Unfortunately, this is a tricky problem to solve at the moment, due to the details of how the jupyter notebook handles output.

## Parallel Brian simulations with the weave code generation target¶

When using the weave code generation target (the default runtime target on Python 2.x, see Runtime code generation for details), you should avoid running multiple Brian simulations in parallel. The weave package caches compiled files, but this cache is not prepared for multiple concurrent updates. If two Python scripts (or two processes started from the same Python script, e.g. via the multiprocessing package) try to store compilation results at the same time, weave will crash with an error message. The numpy and cython targets are not affected by this problem.

## Slow standalone simulations¶

Some versions of the GNU standard library (in particular those used by recent Ubuntu versions) have a bug that can dramatically slow down simulations in C++ standalone mode on modern hardware (see #803). As a workaround, Brian will set an environment variable LD_BIND_NOW during the execution of standalone stimulations which changes the way the library is linked so that it does not suffer from this problem. If this environment variable leads to unwanted behaviour on your machine, change the prefs.devices.cpp_standalone.run_environment_variables preference.