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![Green Computing
Caught the attention of many companies allowing them to save:
greenlab.di.uminho.pt
4
“close to 50% of the energy costs of an organization can be
attributed to the IT departments”
- [PICMET, 2009]
“up to 90% of energy used by ICT hardware can be attributed to
software”
- [The Greenhouse Gas Protocol Report, 2013]](https://image.slidesharecdn.com/greens-160519183926/85/The-Influence-of-the-Java-Collection-Framework-on-Overall-Energy-Consumption-4-320.jpg)
![Green Software
Problems (extend to programmers):
How to analyze
How to interpret
How to improve
greenlab.di.uminho.pt
6
Mining questions about software energy consumption
- [MSR’14]
Integrated energy-directed test suite optimization
- [ISTA’14]](https://image.slidesharecdn.com/greens-160519183926/85/The-Influence-of-the-Java-Collection-Framework-on-Overall-Energy-Consumption-6-320.jpg)
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The Influence of the Java Collection Framework on Overall Energy Consumption
The document discusses quantifying the energy consumption of Java data structures and methods to optimize energy usage. It presents a study ranking common data structures by energy efficiency. The study found refactoring Java programs to use more efficient data structure implementations based on the rankings can decrease energy consumption by 4-11%. A methodology is introduced to automatically analyze Java programs, identify data structure usage, and suggest refactors to lower energy usage.
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The Influence of the Java Collection Framework on Overall Energy Consumption
- 1. The Influence ofthe Java Collection Framework on Overall Energy Consumption Rui Pereira*, Marco Couto*, Jácome Cunha§, João Paulo Fernandes‡, and João Saraiva* greenlab.di.uminho.pt * HASLab/INESC Tec, Universidade do Minho § NOVA LINCS, Universidade Nova de Lisboa ‡ RELEASE, Universidade da Beira Interior {ruipereira, mcouto, jas}@di.uminho.pt, jacome@fct.unl.pt, jpf@di.ubi.pt
- 2.
- 3. Global energy systemis unsustainable greenlab.di.uminho.pt 3
- 4. Green Computing Caughtthe attention of many companies allowing them to save: greenlab.di.uminho.pt 4 “close to 50% of the energy costs of an organization can be attributed to the IT departments” - [PICMET, 2009] “up to 90% of energy used by ICT hardware can be attributed to software” - [The Greenhouse Gas Protocol Report, 2013]
- 5. Green Software Reducingenergy consumption through software analysis and optimization Problem: How to analyze How to interpret How to improve greenlab.di.uminho.pt 5
- 6. Green Software Problems(extend to programmers): How to analyze How to interpret How to improve greenlab.di.uminho.pt 6 Mining questions about software energy consumption - [MSR’14] Integrated energy-directed test suite optimization - [ISTA’14]
- 7. Can we saveenergy by refactoring Java programs to use different data structure implementations? greenlab.di.uminho.pt 7
- 8. Research Questions greenlab.di.uminho.pt 8 (RQ1)Can we define an energy consumption quantification of Java data structures and their methods? (RQ2) Can we use such quantification to decrease the energy consumption of software systems?
- 9. Towards a Rankingof Java data structures greenlab.di.uminho.pt 9 Design Simple scenario of: Storing Retrieving Deleting String values
- 10. greenlab.di.uminho.pt 10 Java CollectionsFramework (JCF) library ConcurrentSkipListSet ArrayList ConcurrentHashMap CopyOnWriteArraySet AttributeList ConcurrentSkipListMap HashSet CopyOnWriteArrayList HashMap LinkedHashSet LinkedList Hashtable TreeSet RoleList IdentityHashMap RoleUnresolvedList LinkedHashMap Stack Properties Vector SimpleBindings TreeMap UIDefaults WeakHashMap Sets Lists Maps Towards a Ranking of Java data structures Design – Data Structures
- 11. greenlab.di.uminho.pt 11 add add clear addAlladdAll containsKey clear add(index) containsValue contains addAll(index) entrySet containsAll clear get iterateAll contains iterateAll iterator containsAll keySet remove get put removeAll indexOf putAll retainAll iterator remove toArray lastIndexOf values listIterator listIterator(index) remove removeAll Continues… Sets Lists Maps Towards a Ranking of Java data structures Design - Methods
- 12. greenlab.di.uminho.pt 12 Defined populationsizes (popsize) of 25,000 250,000 1,000,000 When a second data structure is needed (i.e. addAll) SecondaryCol = 10% of popsize Half existing & half new (shuffled) Towards a Ranking of Java data structures Design - Benchmark
- 13. greenlab.di.uminho.pt 13 Linux 3.13.0-74-genericOS 8GB Ram Intel(R) Core(TM) i3-3240 CPU @ 3.40GHz Java Interpreter/Compiler versions 1.8.0_66 RAPL/jRAPL Towards a Ranking of Java data structures Execution - Specifications
- 14. greenlab.di.uminho.pt 14 Warm-up Instantiated Populated w/ popsize Performed simple actions on the data structure Each test x20 Extracted time/Joules consumed Removed lowest/highest 20% 336 different test (Collection.method) configurations 6720 executions for each popsize 20,000+ different executions Towards a Ranking of Java data structures Execution – For every test
- 15. greenlab.di.uminho.pt 15 Towards a Rankingof Java data structures Results (25k pop)
- 16. greenlab.di.uminho.pt 16 Towards a Rankingof Java data structures
- 17. greenlab.di.uminho.pt 17 Towards a Rankingof Java data structures
- 18. greenlab.di.uminho.pt 18 Towards a Rankingof Java data structures
- 19. Is faster, Greener?! greenlab.di.uminho.pt 19 Isslower, Greener?! Faster Slower
- 20. Research Questions greenlab.di.uminho.pt 20 (RQ1)Can we define an energy consumption quantification of Java data structures and their methods? (RQ2) Can we use such quantification to decrease the energy consumption of software systems?
- 21. Optimizing Energy Consumptionof Java Programs greenlab.di.uminho.pt 21 Methodology 1. Compute which implementations/methods are used in the programs 2. Look up the appropriate energy tables for the used implementations/methods 3. Choose the most energy efficient alternative
- 22. Optimizing Energy Consumptionof Java Programs greenlab.di.uminho.pt 22 Applying the methodology – Data acquisition Obtained Java projects of a Journalism support platform First year OO course Collaborators, Journalists, Readers, Editors Write chronicles and reports Give likes and comments Etc. Average of 36 classes 104 methods 2000 lines of code
- 23. Optimizing Energy Consumptionof Java Programs greenlab.di.uminho.pt 23 Applying the methodology – Data acquisition Obtained 7 test cases to simulate usage Size varied vetween 2000-10000 for each test case/each entity Chosen popsize – 25,000 (smallest) Applied methodology on 5 projects Detected usage of any JCF implementation Detected which methods were used for each implementation Chose the most efficient implementation for each project Measured the changes before and after
- 24. Optimizing Energy Consumptionof Java Programs greenlab.di.uminho.pt 24 Applying the methodology – Example
- 25. Optimizing Energy Consumptionof Java Programs greenlab.di.uminho.pt 25 Applying the methodology – Results Between 4.37% - 11.05% Average of 6.2%
- 26. FW + Conclusion greenlab.di.uminho.pt 26 Presented detailed study of the energy consumption of Sets, Lists, and Maps Quantification of the energy spent by each method (RQ1 Answer) Introduced a very simple methodology to optimize Java programs (RQ2 Answer) Consider other object types (int, objects, etc.) Implement an automatic refactoring plugin Found @ our page: http://greenlab.di.uminho.pt/
- 27. greenlab.di.uminho.pt 27 Portuguese NationalScience Foundation (FCT) Starts July 2016 Grants available for young researchers MSc PhD Postdoc Universities: University of Minho (Braga) University of Beira Interior (Covilhã) University of Porto (Porto) New University of Lisbon (Lisbon)
- 28. The Influence ofthe Java Collection Framework on Overall Energy Consumption Rui Pereira*, Marco Couto*, Jácome Cunha§, João Paulo Fernandes‡, and João Saraiva* greenlab.di.uminho.pt * HASLab/INESC Tec, Universidade do Minho § NOVA LINCS, Universidade Nova de Lisboa ‡ RELEASE, Universidade da Beira Interior {ruipereira, mcouto, jas}@di.uminho.pt, jacome@fct.unl.pt, jpf@di.ubi.pt
Editor's Notes
- #7 Aware of the energy consumption problem, many times seeking help in resolving this, misconceptions within the programming community as to what causes highenergy consumption, how to solve them a heavy lack of support and knowledge for energy-aware development Even in software testing Image from [http://thevunderkind.com/new-to-coding-dont-know-how-to-pick-your-first-language-let-udacitys-infographic-help-you/]
- #11 The most classical way is to separate Implement the interfaces Separation makes sense as each interface is used for distinct properties Elimiated: Job State Reasons (SET) IdentityHashMap (MAP)
- #13 Provides analysis with multiple orders of magnituted. Learn how it scales also
- #16 CopyOnWriteArraySet was discarded. Did not finish in reasonable amount of time.
- #17 LinkedHashSet includes most of the efficient methods But we can also note it has the two most inefficient methods (addAll and containsAll)
- #18 RoleUnresolved and AttributeList are the best. Interesting they both extend ArrayList which has less efficient methods, and quite different consumption values. LinkedList is by far the worse
- #19 HashTable, LinkedHashMap, Properties contain the most efficient methods, with no red. Once again concurrent fails. Properties is generally used to store project configuration data/settings, yet produced very good results for this simple string value scenario