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We introduce an open-source Python package for the analysis of large-scale electrophysiological data, named SyNCoPy, which stands for Systems Neuroscience Computing in Python.

PySpark: deployed as the engine for distributed computing, optimizes computational efficiency in ETL processes by distributing data across multiple nodes for parallel processing, scaling to match ...

Series of notebook on parallel computing. Contribute to yvesdubief/Python-parallel-computing development by creating an account on GitHub.

The chief impediment to widespread usage of parallel computing is the difficulty in programming high performance computers (HPCs). Furthermore, most users work from a Windows PC, so that learning UNIX ...

The premise of analysing static voltage stability of large power grids online is identifying Thevenin equivalent parameters rapidly and accurately. And based on the current reaearch in this field, ...

Multiprocessing in Python enables the computer to utilize multiple cores of a CPU to run tasks/processes in parallel.

Pierre Glaser from INRIA gave this talk at EuroPython 2019. "Modern hardware is multi-core. It is crucial for Python to provide high-performance parallelism. This talk will expose to both ...