Research project on Sustainable Computing #348
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Henry: good luck identifying a social cost of carbon Question for Asim? Python is ~60% less efficient than java, implies switching, but could fix Python Navveen: wrote application in nodejs and rust, keep stuff constant, rust was very efficient (~5-10%). RESOURCES: Core question: |
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WG: Gadhu: What will be really useful is just some detailed benchmarking of various aspects of the stack - language, pattern etc for achieving a particular function so that you can compare the carbon cost of using these aspects to design your software system. Pindy: comparing languages - could we do a longitudinal study compare the same solutions using different languages - can the professor create simulations |
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update in August |
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During today's discussion (5/25/2023), I shared an idea and an ultimate vision that someday, major github open source projects will have an SCI score or SSC (Social Cost of Carbon dollars sign) along side the number of forks and likes, or some type of carbon efficiency rating of the software, in absolute terms or relative terms, or some sort of carbon efficiency certification. To achieve that, one of the approaches is to define a standard/specification of a controlled environment (hardware, software, versions of SCI spec, locale etc) where such rating/evaluation of SCI/SCC is produced. This way, anyone can take such an environmental specification and produce an SCI/SSC dollars of their own software systems. The produced SCI/SCC scores will be compliant and certified by GSF. Of course, it will make sense for GSF as an organization to build an initial reference implementation of the controlled environment, and ideally the compliant environment built by 3rd parties should produce similar SCI/SCC scores results. This could also be an extension of the sustainable computing research project. This idea is a bit like UL Labs that measures product safety. In this cause, software product or systems are measured for its carbon footprint, in CO2's or in SSC dollars. The point of this idea is to translate SCI scores to real life meaning, real life value, in terms of dollar amount, or understandable certification or meaning of carbon efficiency of software systems. Again, the initial scope of the standard is to define the parameters of the controlled testing environment in order to create the SCI/SCC scores, so that anyone can take the standard specification to build their own testing lab environment to test their software to create their own SCI/SCC score, and GSF could issue the certificate that their score meets or complies with GSF's standard of certification. GSF still maintains the authority of the certificate and the evolution of the SCI/SCC spec, and still is responsible for the definition of the SCI, SCC spec, the testing environment spec, and the future iterations of these specifications. If this vision is achieved, SCI will have a really meaningful impact to the whole software industry. The value of SCI standard will be truly realized. Look forward to continued brainstorming of ideas of translating SCI to real life meanings and applications. |
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WG: recommends merging with SCER |
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Hey @chrisxie-fw , we have just submitted an article that describes an automated open source approach to measure the SCI. Is that something that fits what you are suggesting? Green-Software-Foundation/sci-guide#52 @Henry-WattTime See an example for a TPC Select benchmark here for:
![]() The repo to match it is here: https://github.com/green-coding-berlin/DBMS-bench Is that something that could be interesting for the SCER project? |
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Hi @ArneTR , you presented a great tool that could potentially be helpful in SCER project, thank you! I was thinking if some kind of labelling be possible for different software projects, similar to what France has done to food nutritional score labelling: Nutri-Score: https://en.wikipedia.org/wiki/Nutri-Score .
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From Chris Xie (Huawei)
We are intending to initiate a research project on Sustainable Computing topic, in particular, how programming languages (Rust, C, Java, Python etc.) affect the carbon efficiencies of the full computing stack, and translate the efficiencies into economic impacts in dollar terms, using the SCI methodology as a tool for such studies. Effectively this project could be a case study or an application of SCI and intends to apply the SCI methodology to the Social Cost of Carbon (SCC) study of programming languages and software systems. Apply meaning to SCI scores is not limited to dollar terms, but it could also be carbon efficiency rankings of comparable computing systems, ICT solutions, 5G base stations, etc. Please see the attached document for details. Please feel free to ping me for further discussions, ideas, collaborations. - SoftwareSCC_GSF.pdf
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