Spyder IDE is a complex but usually stable Python program.
When something goes wrong with Spyder, often the symptom is it simply won’t appear, maybe you’ll just get the splash logo.
To totally reset Spyder (erasing all user preferences for Spyder), type in Terminal / Command Prompt:
Normally, that fixes Spyder.
To diagnose further, start Spyder from Terminal instead of OS Start menu, it might give some hints.
In 2017, Anaconda
Accelerate was discontinued.
The GPU CUDA, cuDNN and NCCL functionality are accessed in a Numpy-like way from
CuPy also allows use of the GPU is a more
fashion as well.
Before starting GPU work in any programming language realize these general caveats:
I/O heavy workloads may make realizing GPU benefits more difficult
Consumer GPUs (GeForce) can be > 10x slower than workstation class (Tesla, Quadro)
You must have a discrete Nvidia GPU in your laptop or desktop.
Check for existence of an Nvidia GPU in your computer by:
lspci | grep -i nvidia
a blank response means an Nvidia GPU is not detected.
Look under the “render” tab to see if an Nvidia GPU exists.
cupy.cuda.runtime.CUDARuntimeError: cudaErrorInsufficientDriver: CUDA driver version is insufficient for CUDA runtime version
This means the CUDA Toolkit version is expecting a newer Nvidia driver.
The Nvidia driver can be updated via your standard Nvidia update program that was installed from the factory.
“Table 1” of the CUDA Toolkit release notes gives the
CUDA Toolkit required Driver Versions.
A code cell in popular Python IDEs including
is created by line starting with # %%.
This “code cell” is analogous to IPython code cells and
Matlab code sections.
You will see like
# %% user data
y =4# %% main loopfor i in range(5):
x += y
The code cells allow running sections of code in an IDE without the need to constantly set/unset breakpoints in the IDE.
They also catch the eye of developers to delineate logical blocks of code in the algorithm.
We encourage the use of code cell syntax, even if you don’t use them in the IDE directly, as the IDE will highlight sections of code to visibly delineate these separate parts of the algorithm.
Sadly, PGI 19.7
deprecated PGI debugger.
PGI Java-based pgdbg graphical debugger was for Fortran, C and C++ and was in the no-cost Community Edition as well.
The program to be debugged needs compile options -g -O0 to provide maximum debugging information.
Example with hello.f90:
pgfortran -g hello.f90
pgdbg a.out opened the graphical Fortran debugger.
If you don’t see code in the upper left of the graphical PGI debugger for your program, be sure you compiled the executable with -g -O0 options.
gained the ability to
open HDF5 files in 0.12.0.
However, this can cause Python to quietly crash without error message, which can be quite confusing.
This is true even with the minimum required versions of xarray, h5py and h5netcdf installed.
We don’t have a specific workaround for this other than to use
We have used h5py for several years in high-stakes operations, including data analysis and data collection.
Both h5py and netcdf4 Python modules work with
to avoid excess I/O resource consumption.
Since GitLab Community Edition is
large projects like CMake may host their own self-managed GitLab instance.
To make merge requests to such projects, one can configure Git SSH.
For this example, we use Kitware’s CMake GitLab instance https://gitlab.kitware.com/cmake.
This procedure works for any operating system, including Windows.
First, create an account on the self-managed GitLab instance and fork the desired repo.
This will be available like