In the last blog post we had a look at quite superficial performance improvements for Python programs. This time we try to surpass those limits by creating our own modules from scratch – in C++.

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A program can be written in many different ways, (hopefully) always obtaining the same result. Still, the execution time may differ drastically. In higher languages like Python, one may not tell instantly, how a predefined function is implemented.

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”The Schrödinger equation explains everything but cannot explain anything “ – With this dilemma my solid-state physics professor addressed the limits of his course right in the beginning. The equation , so mighty yet so short, when applied on single …

Alexander J. Pfleger Read More »

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Project reference: 2007 Python is widely used in scientific research for tasks such as data processing, analysis and visualisation. However, it is not yet widely used for large-scale modelling and simulation on high performance computers due to its poor performance …

Performance of Parallel Python Programs on New HPC Architectures Read More »

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