Green Software Lab
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Presentation @ IT4Energy 2015
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Green Software Lab
- 1. Green Software Lab Orlando Belo23, Marco Couto13, Jácome Cunha15, João Paulo Fernandes4, Miguel Guimarães13, Rui Pereira13, and João Saraiva13 1 HASLab/INESC TEC 2 Algoritmi R&D Centre 3 Universidade do Minho, Portugal 4 RELEASE, Universidade da Beira Interior, Portugal 5 Universidade Nova de Lisboa, Portugal {obelo, mcouto, mguimaraes, ruipereira, jas}@di.uminho.pt, jacome@fct.unl.pt, jpf@di.ubi.pt greenlab@di.uminho.pt greenlab.di.uminho.pt
- 3. Green Software Lab – Our focus 2greenlab.di.uminho.pt
- 4. Our focus – Analysis 3greenlab.di.uminho.pt
- 5. Our focus – Visualization 4greenlab.di.uminho.pt
- 6. Our focus – Optimization 5greenlab.di.uminho.pt
- 7. Green Software Lab – Research areas 6greenlab.di.uminho.pt
- 8. Research areas – Mobile apps (GreenDroid) 7greenlab.di.uminho.pt
- 9. Research areas – Data bases/warehouses (gSQL) 8greenlab.di.uminho.pt
- 10. Research areas – Source Code (SPELL) 9 Tests 1 t1 t2 t3 t4 t5 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0.3 0.7 0.3 0.3 0.3 0.7 1 0 1 0 1 greenlab.di.uminho.pt
- 11. Green Software Lab – Industrial Partners 10greenlab.di.uminho.pt
- 12. Green Software Lab Orlando Belo23, Marco Couto13, Jácome Cunha15, João Paulo Fernandes4, Miguel Guimarães13, Rui Pereira13, and João Saraiva13 1 HASLab/INESC TEC 2 Algoritmi R&D Centre 3 Universidade do Minho, Portugal 4 RELEASE, Universidade da Beira Interior, Portugal 5 Universidade Nova de Lisboa, Portugal {obelo, mcouto, mguimaraes, ruipereira, jas}@di.uminho.pt, jacome@fct.unl.pt, jpf@di.ubi.pt greenlab@di.uminho.pt greenlab.di.uminho.pt
Editor's Notes
- which will focus on improving the energy consumption of computers by a software approach
- The GSL is a team of researchers from across the country, consisting of members currently from the Uminho, UBI, and the UNL and several research and development centers. motivated on the need to look at the software side to tackle the energy consumption problem. While the focus on software, the solution will obviously expand to mobile applications, data-centers, and other computing applications.
- working on reducing energy consumption across various computing systems (mobile, programs, databases, etc.). The global idea is to apply SE techniques to -(source code) using analysis and transformation techniques to detect anomalies in energy consumption, -visualize this information into tools and frameworks, -to define optimizations to reduce such consumption.
- Here we will begun to find the indicators and bad smells to high energy costs, allowing us to construct a red smell catalog.
- In our second task, we will concern ourselves on how to display the information we have gathered, and from using our techniques. This would allow programmers to begin becoming energy aware when coding, and allow us to distribute our prototypes to other researchers and continue gathering more patterns and smells that cause high energy consumption. We have been looking at how to display this information, some of our ideas are: sunburst, code flagging, and even a combination of both. we will validate our chosen approach with an empirical study using programmers.
- So whats a red smell catalog without its green refactorings? This final task will focus on constructing the refactorings for the smells we detected causing high energy consumption. Here we will define the theories, methodologies, and approaches to optimize software to become green. We plan on also building a prototype wizard, which will display information from the analysis, where in ones code are the high consumption spots, and show how to correct them or automatically refactor the code according to our catalog. And once again, the theories, methodologies, and tools will run through a series of validations.
- Is a tool where With an instrumented android application, which has calls to an energy measuring API And our testing framework where we run various Junit tests We can identify, using our defined methods and techniques, and with various graphical representations of this information which are the more energy efficient and inefficient methods in that given application, and information Such as how often is a certain method called in a Green, Yellow, Orange, or Red test run, allowing us to further analyze the source code to optimize the code and application
- We have defined energy consumption plans for data querying processes. By using the information from the querying execution plan, especially the information related to the used operators, we designed and developed a method to define energy consumption plans for database queries. This tool, adapted into the Postgres kernel, allows us to estimate the energy consumption of each query and database operator at compile time. We have also started looking into measuring ETL (Extract, Transform and Load) and surrogate key pipeline energy consumption. The general idea is to assign each ETL component a specific energy consumption value, so it may be possible to substitue a high energy consuming component, or refactor, for a lower consumping component, essentially allowing optimization. have an idea of how much the pipeline would consume, and be able to
- The third way is to analyze source code directly. We have adapted a Spectrum-based fault localization technique, which is normally used to detect bugs in SW code, we can detect where energy leaks occur, from various levels such as packages to functions.
- As industrial partners, we will work with: primavera, SIG, National Instruments, and VisionSpace whom we already have a QREN green research project (Green software for space control mission)
- Good afternoon everyone. Today ill be presenting my phd pre-thesis, which will focus on improving the energy consumption of computers by a software approach