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When a workflow is executed several times, Anduril caches results of components and only executes the components whose configuration has changed since the last run, which reduces execution time significantly.
The reduced grid allows an increased timestep while eliminating the need for filtering and reduces execution time per model step by roughly 20%.
In the past few years, cloud computing has gained much popularity as it reduces execution time of a program by distributing it on different machines over a network.
This step is not essential, but reduces execution time by keeping only those variables that have at least one single term or variant in their label.
For large sequences running on our particular hardware, the GPU implementation reduces execution time by a factor of close to 60 compared with an optimized serial implementation, and by a factor of 116 compared with the original code.
For large sequences, the GPU implementation reduces execution time by a factor of close to 60 compared with an optimized serial implementation, and by a factor of 116 compared with the original code.
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In [18], a parallel Hough transform for reducing execution time was proposed, but space complexity remains.
This concept can remarkably reduce execution time and computing complexity for multi-train simulation.
Chern et al. presented a parallel Hough transform to reduce execution time [18].
As a whole, our approach can help reduce execution time by 6 96% for computation-intensive applications.
To reduce execution time, a customized data structure is implemented and explained.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com