Backend
Spectral deferred corrections parallelized across the method for differential-algebraic equations
arXiv cs.NA0 views
arXiv:2606.25908v2 Announce Type: replace Abstract: In this work, the performance of different spectral deferred corrections (SDC) methods applied to initial value problems for differential-algebraic equations (DAEs) of index one is analyzed. The SDC method solves a series of correction equations, and after each iteration, the numerical solution is corrected by adding the obtained approximation of the error. The formulation of the SDC method allows for a parallelization across the method to obtain small-scale parallelism, for which a number of processes equal to the number of collocation nodes can be used. Recently, an analytical approach to finding optimal diagonal coefficients for parallel SDC was proposed. So far, no analysis with the new coefficients for parallel SDC applied to DAEs was done. We demonstrate that parallel SDC methods solve DAE problems with high accuracy faster than the associated sequential SDC schemes, obtaining speedup in a small-scale parallel regime.
Source:https://arxiv.org/abs/2606.25908PreviousHigher Accuracy Modular Data Assimilation for the Navier-Stokes EquationsNextWeighted Laplace Spaces for Spectral Measures and Rational Approximation
Related posts
Turn Today’s Messy Notes Into Tomorrow’s Checklist With AI
0dev.to AI
A 763B MoE at "2 Bits": Where the Bytes Really Go in the GSQ-RCO GGUFs, and Why 100% Recovery Sits Inside the Noise
0dev.to AI
How I ship fixes to open-source projects maintainers actually merge (with AI in the loop)
0dev.to AI
Prompt Injection Through Documents: How to Harden an LLM Extraction Pipeline
0dev.to AI
Keeping noindex, the sitemap and the image sitemap in agreement for programmatic pages
0dev.to AI
3 Things in AI You Should Know: Character.AI Files for Bankruptcy
0dev.to AI