Accelerating Scientific Computing: A Comprehensive Analysis of Python Vectorization Paradigms and Performance Optimization Across CPU and GPU Architectures

Surya Rao Rayarao, Naga Donikena

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DOI: 10.22541/au.175829683.32274228/v1
Published: 2025-09-19
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Publisher: Wiley
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Cite this work

BibTeX

@article{allodium:10.22541/au.175829683.32274228/v1,
  title = {Accelerating Scientific Computing: A Comprehensive Analysis of Python Vectorization Paradigms and Performance Optimization Across CPU and GPU Architectures},
  author = {Surya Rao Rayarao and Naga Donikena},
  year = {2025},
  doi = {10.22541/au.175829683.32274228/v1},
  url = {https://doi.org/10.22541/au.175829683.32274228/v1}
}

RIS

TY  - JOUR
TI  - Accelerating Scientific Computing: A Comprehensive Analysis of Python Vectorization Paradigms and Performance Optimization Across CPU and GPU Architectures
AU  - Surya Rao Rayarao
AU  - Naga Donikena
PY  - 2025
DO  - 10.22541/au.175829683.32274228/v1
UR  - https://doi.org/10.22541/au.175829683.32274228/v1
ER  -

APA

Rayarao, S. R., & Donikena, N. (2025). Accelerating Scientific Computing: A Comprehensive Analysis of Python Vectorization Paradigms and Performance Optimization Across CPU and GPU Architectures. https://doi.org/10.22541/au.175829683.32274228/v1

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crossref · retrieved 2026-11-10T16:36:50.970Z