Ponto de Partida 79 – As Baterias do Futuro (Audio in Portuguese)
GSL member João Paulo Fernandes has a few things to say about the batteries of the future in the 79th Ponto de Partida!
Ponto de Partida 79 – As Baterias do Futuro (Audio in Portuguese)
GSL member João Paulo Fernandes has a few things to say about the batteries of the future in the 79th Ponto de Partida!
The article “Towards a Green Ranking for Programming Languages”, authored by HASLab/INESC TEC & UMinho researchers Marco Couto, Rui Pereira, Francisco Ribeiro, Rui Rua and João Saraiva, was awarded the Best Paper Award at SBLP 2017.
In this work, the researchers analysed and compared the energy efficiency of various programming languages. More specifically, this award-winning research used a set of benchmarking programs and problems in 10 different programming languages in order to compare the energy efficiency of each. In a second phase, the execution time data of the programs was collected, in order to try to understand the relation between energy consumption and execution time.
Finally, while the obtained results showed that the C language is, unsurprisingly, the most efficient language in terms of both energy consumption and performance, the study also showed languages which are slower than others yet consume less energy. It should be noted that execution time and energy consumption vary in different and not directly related ways, since some languages are more efficient in some cases and less in others. Therefore, this study will allow not only the optimisation of energy consumption, but also the optimisation of the execution time of each program.
The 21st Brazilian Symposium on Programming Languages (SBLP 2017) took place on the 21st and 22nd of September, in Fortaleza, Brazil, and is one of the conferences that compose the Brazilian Conference on Software (CBSOFT).
Energy Efficiency across Programming Languages: How does energy, time, and memory relate? – Rui Pereira, Marco Couto, Francisco Ribeiro, Rui Rua, Jácome Cunha, João Paulo Fernandes, João Saraiva
This paper presents a study of the runtime, memory usage and energy consumption of twenty seven well-known software languages. We monitor the performance of such languages using ten different programming problems, expressed in each of the languages. Our results show interesting findings, such as, slower/faster languages consuming less/more energy, and how memory usage influences energy consumption. We show how to use our results to provide software engineers support to decide which language to use when
energy efficiency is a concern.
Towards a Green Ranking for Programming Languages – Marco Couto, Rui Pereira, Francisco Ribeiro, Rui Rua, João Saraiva
While in the past the primary goal to optimize software was the run time optimization, nowadays there is a growing awareness of the need to reduce energy consumption. Additionally, a growing number of developers wish to become more energy-aware when programming and feel a lack of tools and the knowledge to do so.
In this paper we define a ranking of energy efficiency in programming languages. We consider a set of computing problems implemented in ten well-known programming languages, and monitored the energy consumed when executing each langauge. Our preliminary results show that although the fastest languages tend to be the lowest consuming ones, there are other interesting cases where slower languages are more energy efficient than faster ones.
Rui Pereira, a doctoral student of HASLab, reached the second place in the ACM Student Research Competition at ICSE 2017, with the article “Locating energy hotspots in source code”.
The article entitled “Locating energy hotspots in source code”, which was initially submitted in the form of a long abstract paper, was presented in a second evaluation phase in poster form at the 39th International Conference on Software Engineering, one of the most important conferences in the field of Software Engineering, and it was carried out under the project GSL – Green Software Laboratory, a national project financed by FCT.
In this evaluation phase, along with nine other candidates, Rui Pereira made a small public presentation and exhibition of the poster during a special session of the same conference, before a jury composed of five ICSE and ACM members. Only four researchers advanced to the final phase of the competition.
In the third and final phase, with a research talk at ICSE, Rui Pereira achieved the second place in the competition, losing the first place to a researcher from Carnegie Mellon University, and prior Apple researcher. In this phase, three were awarded a medal.
The next round will be in the Grand Final of the ACM Research Competition, where all medalists participate in the ACM Student Research Competition. This round will be during the ACM Awards Banquet an event where, as a general rule, the Turing Award is presented, that is, a prize awarded by ACM to a person who contributed significantly to the area of Computing.
It is important to mention that this competition, sponsored by Microsoft, offers a unique forum for undergraduate and graduate students to present their original research before a panel of judges and attendees at well-known ACM-sponsored and co-sponsored conferences.
This edition of ICSE was held in Buenos Aires, Argentina, from May 20 to 28 and has an annual membership of approximately 1600 participants.
Products go Green: Worst-Case Energy Consumption in Software Product Lines -Marco Couto, Rui Pereira, Paulo Borba, Jácome Cunha, João Paulo Fernandes and João Saraiva
The optimization of software to be (more) energy efficient is becoming a major concern for the software industry. Although several techniques have been presented to measure energy consumption for software, none has addressed software product lines (SPLs). Thus, to measure energy consumption of a SPL, the products must be generated and measured individually, which is too costly.
In this paper, we present a technique and a prototype tool to statically estimate the worst case energy consumption for SPL. The goal is to provide software developers with techniques and tools to reason about the energy consumption of all products in a line, without having to produce, run and measure the energy in every combination.
Our technique combines classic static program analysis techniques and worst case execution time prediction with energy consumption analysis. This technique analyses all products in a feature-sensitive manner, that is, a feature used in several products is analyzed only once, while the energy consumption is estimated once per product.
We implemented our technique in a tool called Serapis. We did a preliminary evaluation using a realistic product line for image processing implemented in C. Our experiments considered 7 products from such line and our initial results show that the tool was able to estimate the worst-case energy consumption with a mean error percentage of 9.4% and standard deviation of 6.2% when compared with the energy measured when running the products.
Rui Pereira has been selected to join the second phase of the ACM ICSE’17 Student Research Competition for the paper titled: Locating Energy Hotspots in Source Code to be presented in a Poster session on May 25th at the 39th International Conference on Software Engineering at Buenos Aires.
An Economic Energy Approach For Queries On Data Centers – João Saraiva, Miguel Guimarães, Orlando Belo
Energy consumption is an issue that involves all of us, both as individuals and as members of a society, and covers all our areas of activity. It is something so broad that its impact has important reflections on our social, cultural and financial structures. The domain of software, and in particular database systems, is not an exception. Although it seems to be a little bit strange to study the energy consumption of just one query, when we consider the execution of a a few thousand queries per second, quickly we see the importance of the querying consumption in the monthly account of any company that has a conventional data center.
To demonstrate the energy consumption of queries in data centers, we idealized a small dashboard for monitoring and analyzing the sales of a company, and implemented all the queries needed for populating it and ensuring its operation. The queries were organized into two groups, oriented especially to two distinct database management systems: one relational (MySQL) and one non relational (Neo4J).
The goal is to evaluate the energy consumption of different types of queries, and at the same time compare it in terms of relational and non-relational database approaches. This paper relates the process we implemented to set up the energy consumption application scenario, measure the energy consumption of each query, and present our first preliminary results.