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Efexor Zolpidem :v_com: (capeta@ursal.zone)'s status on Saturday, 19-Oct-2024 19:45:30 JST Efexor Zolpidem :v_com:

sextou lendo artigo científico que a pesquisadorah vingativah publicou pra esculachar outro artigo científico publicado por outra pesquisadorah.
barraco acadêmico
me apetece

In conversation about a month ago from ursal.zone permalink
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  Chaotic Princess :Ryyca: (bruiserzinha@ursal.zone)'s status on Saturday, 19-Oct-2024 19:45:45 JST Chaotic Princess :Ryyca:
  in reply to
  
  @capeta resumo da fofoca? 🤔
  
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  Efexor Zolpidem :v_com: (capeta@ursal.zone)'s status on Saturday, 19-Oct-2024 22:10:21 JST Efexor Zolpidem :v_com:
  in reply to
  - Chaotic Princess :Ryyca:
  @Bruiserzinha o artigo original faz várias afirmações sobre quais linguagens de programação são mais amigáveis ao meio ambiente, por usarem menos energia.
  aí o artigo vem retrucando que a metodologia do primeiro não era confiável, e apontando vários furos nos experimentos que eles fizeram.
  o nome é "It's Not Easy Being Green: On the Energy Efficiency of Programming Languages"
  https://arxiv.org/abs/2410.05460
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    It's Not Easy Being Green: On the Energy Efficiency of Programming Languages
    
    Does the choice of programming language affect energy consumption? Previous highly visible studies have established associations between certain programming languages and energy consumption. A causal misinterpretation of this work has led academics and industry leaders to use or support certain languages based on their claimed impact on energy consumption. This paper tackles this causal question directly. It first corrects and improves the measurement methodology used by prior work. It then develops a detailed causal model capturing the complex relationship between programming language choice and energy consumption. This model identifies and incorporates several critical but previously overlooked factors that affect energy usage. These factors, such as distinguishing programming languages from their implementations, the impact of the application implementations themselves, the number of active cores, and memory activity, can significantly skew energy consumption measurements if not accounted for. We show -- via empirical experiments, improved methodology, and careful examination of anomalies -- that when these factors are controlled for, notable discrepancies in prior work vanish. Our analysis suggests that the choice of programming language implementation has no significant impact on energy consumption beyond execution time.

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