A Green approach to save energy consumed by software

International audienceThe availability of various services (i.e. eBank, eHospital) through the cloud has facilitated daily lives. It allows to make energy and money savings by preventing people from moving to accomplish a small task (for instance see his account at the bank). Furthermore, the availability of these services through mobile devices and their widely usage has a positive impact on energy saving. It is also worthwhile to consider technology addicts developing/using applications or software when estimating the growing impact of software on energy consumption

Beyond CPU: Considering Memory Power Consumption of Software

International audienceICTs (Information and Communication Technologies) are responsible around 2% of worldwide greenhouse gas emissions (Gartner, 2007). And according to the Intergovernmental Panel on Climate Change (IPPC) recent reports, CO2 emissions due to ICTs are increasing widely. For this reason, many works tried to propose various tools to estimate the energy consumption due to software in order to reduce carbon footprint. However, these studies, in the majority of cases, takes into account only the CPU and neglects all others components. Whereas, the trend towards high-density packaging and raised memory involve a great increased of power consumption caused by memory and maybe memory can become the largest power consumer in servers. In this paper, we model and then estimate the power consumed by CPU and memory due to the execution of a software. Thus, we perform several experiments in order to observe the behavior of each component

Towards a Green and Sustainable Software

International audienceInformation and Communication Technologies (ICTs) are responsible around 2% of worldwide greenhouse gas emissions [1]. On the other hand, the use of mobile devices (smartphone, tablet, etc.) is continually increasing. Due to the accessibility of the Internet and the cloud computing, users will use more and more software applications which will cause even an increasing effect on gas emission. Thus, an important research question is "how can we reduce or limit the energy consumption related to ICT and, in particular, related to software?" For a long time, proposed solutions focused only on the hardware design, however in recent years the software aspects have also become important. Our first objective is to compare the studies in the research area of energy efficient/green software. Relying on this survey, we will propose a methodology to measure the energy consumed by software at runtime

Does Reinfusion of Stem Cell Products on Multiple Days Affect Engraftment?

Objective: High-doses of melphalan treatment with autologous stem cell transplantation in multiple myeloma (MM) remains a major treatment modality in suitable patients. A minimal dose of 2x106/kg CD34+ cells is preferred to achieve engraftment. Some patients need multiple leukapheresis procedures to achieve the necessary number of CD34+ cells, but this can cause a high volume of stem cell product that cannot be given in a single day. Whether or not the number of infusion days affects engraftment has not been studied before. We aimed to evaluate the impact of reinfusion of stem cells on multiple days on engraftment results. Materials and Methods: Demographic features, CD34+ cell doses, neutrophil and platelet engraftment days, hospitalization days, and number of infusion days of 149 autologous transplantations of 143 MM patients were evaluated retrospectively. Results: The data of 143 MM patients who were transplanted were analyzed retrospectively. Median age was 55±8.5 (range: 26-70) years with a male/female ratio of 91/58. Hospitalization days for all patients were 24±6 (range: 14-50) days. Mean CD34+ cell number was (7.5±5.3) x106/kg (range: 1.5-31x106/kg). CD34+ cells were reinfused in 1 day in 80.5% (n=120) of the patients, 2 days in 18.2% of the patients (n=27), and 3 days in 1.3% of the patients (n=2). For 29 patients, reinfusion was applied in more than 1 day because of the high volume of stem cell product. We did not see any dimethyl sulfoxide toxicity, cardiac arrhythmia, or volume overload complications. Hypertensive attacks during infusion were easily controlled by furosemide treatment. In the group with multiple infusions, the infused CD34+ cell numbers had a mean of (4.8±2.8)x106/kg, and in the single infusion group the mean was (8.1±5.5)x106/kg. There were no statistical differences between the two groups regarding platelet and neutrophil engraftment days (p=0.850, r=0.820 and p=0.500, r=0.440). There was no statistical difference between the two groups for hospitalization days (p=0.060, r=0.050). Conclusion: In cases with a high volume of stem cell product to acquire adequate stem cells, reinfusion can be safely applied across multiple days without any delay in engraftment

Méthodologie de développement de logiciels dans un environnement informatiquement vert

The number of mobile devices (smartphone, tablet, laptop, etc.) and Internet users are continually increasing. Due to the accessibility provided by cloud computing, Internet and Internet of Things (IoT), users use more and more software applications which cause an increasing effect on gas emission. Thus, ICT (Information and Communication Technologies) is responsible of around 2% worldwide greenhouse gas emissions which is equivalent of that emitted by the airline industry. According to recent reports, the Intergovernmental Panel on Climate Change (IPCC), CO2 emissions due to ICT are increasing widely. Nevertheless, ICT, in allowing to solve complex problems in other sectors, can greatly and easily participate to reduce significant portion of the remaining 98% of global CO2 emissions. The use of software implies hardware operations which are physically responsible of energy consumption. Consequently, software is indirectly involved in the energy consumption. Thus, we need to reduce software energy consumption while maintaining the same functionalities for the software in order to build sustainable and green software. Firstly, in this thesis work, we define the terms sustainable and green in the area of software development. To build a software product, we need to follow a software engineering process. Hence, we define and describe sustainable and green criteria to be respected after each step of this process in order to establish a sustainable and green software engineering process. Then, we focus on the software energy consumption estimation. Many research works tried to propose various tools to estimate the energy consumption due to software in order to reduce carbon footprint. Unfortunately, these studies, in the majority of cases, consider only the CPU and neglects all others components. Existing power consumption methodologies need to be improved by taking into account more components susceptible to consume energy during runtime of an application. Writing sustainable, power efficient and green software necessitates to understand the power consumption behavior of a computer program. One of the benefits is the fact that developers, by improving their source code implementations, will optimize software power consumption. Moreover, there is a lack of analyzing tool to dynamically monitor source code energy consumption of several components. Thus, we propose GMTEEC (Generic Methodology of a Tool to Estimate Energy Consumption) which is composed of four layers assisting developers to build a tool estimating the software power consumption. Hence, in our work, respecting the layers of GMTEEC, we develop TEEC (Tool to Estimate Energy Consumption) which is based on mathematical formula established for each component (CPU, memory, hard disk, network) in order to estimate the total software energy consumption. Moreover, we add in TEEC the capacity to locate dynamically the hotpoints which are the parts of source code consuming the greater amount of energy in order to help and guide developers to optimize their source code and build efficient, sustainable and green software. We performed a variety of experiments to validate the accuracy and quality of the sustainable and green software engineering process and TEEC. The results demonstrate the possibility to save significant quantity of energy and time at limited costs with an important positive impact on environmentLe nombre de périphériques mobiles (smartphone, tablette, ordinateur portable, etc.) et les internautes augmentent continuellement. En raison de l'accessibilité du cloud computing, de l'Internet et de l'Internet des Objets (IdO), les utilisateurs utilisent de plus en plus d'applications logicielles qui provoquent un effet croissant sur les émissions de gaz à effet de serre. Ainsi, les TIC (Technologies de l'Information et de la Communication) sont responsables d'environ 2% des émissions mondiales de gaz à effet de serre qui sont équivalentes à celles émises par l'industrie aérienne. Selon des rapports récents, le Groupe d'experts Intergouvernemental sur l'Evolution du Climat (GIEC), les émissions de CO2 dus aux TIC augmentent rapidement. Néanmoins, les TIC, en permettant de résoudre des problèmes complexes dans d'autres secteurs, peuvent grandement et facilement participer pour réduire une partie importante des 98% restants des émissions mondiales de CO2. L'utilisation du logiciel implique des opérations matérielles qui sont physiquement responsables de la consommation d'énergie. Par conséquent, le logiciel est indirectement impliqué dans la consommation d'énergie. Ainsi, nous devons réduire la consommation d'énergie du logiciel tout en conservant les mêmes fonctionnalités pour le logiciel afin de créer des logiciels durables et verts. Premièrement, dans ce travail de thèse, nous définissons les termes «durable et vert» dans le domaine du logiciel afin de créer des logiciels respectant les critères de ces termes. Pour créer un produit logiciel, nous devons suivre un processus d'ingénierie logicielle. Par conséquent, nous décrivons des critères durables et verts à respecter après chaque étape de ce processus afin d'établir un processus d'ingénierie logicielle durable et écologique. En particulier, nous nous concentrons sur l'estimation de la consommation d'énergie du logiciel. De nombreux travaux ont essayé de proposer divers outils pour estimer la consommation d'énergie due aux logiciels afin de réduire l'empreinte carbone. Pendant longtemps, les solutions proposées se sont concentrées uniquement sur la conception du matériel, mais ces dernières années, les aspects logiciels sont également devenus importants. Malheureusement, ces études, dans la plupart des cas, ne considèrent que le CPU et négligent tous les autres composants. Les modèles de consommation d'énergie existants doivent être améliorés en tenant compte de plus de composants susceptibles de consommer de l'énergie pendant l'exécution d'une application. L'écriture d'un logiciel durable, performant et vert nécessite de comprendre le comportement de consommation d'énergie d'un programme informatique. L'un des avantages est que les développeurs, en améliorant leurs implémentations du code source, optimiseront la consommation d'énergie du logiciel. De plus, il existe un manque d'outil d'analyse pour surveiller dynamiquement la consommation d'énergie du code source de plusieurs composants. Ainsi, nous proposons GMTEEC (Méthodologie Générique d'Outil pour Estimer la Consommation Energétique) qui se compose de quatre couches aidant et guidant la construction d'un outil permettant d'estimer la consommation énergétique d'un logiciel. Ainsi, dans notre travail, en respectant les couches de GMTEEC, nous créons TEEC (Outil pour Estimer la Consommation Energétique) qui repose sur une formule mathématique établie pour chaque composant (CPU, mémoire, disque dur, réseau) susceptible de consommer de l'énergie afin d'estimer la consommation totale d'énergie du logiciel composée de la somme de chaque consommation d'énergie par composant. De plus, nous ajoutons à TEEC la capacité de localiser dynamiquement les points chauds qui sont les parties du code source consommant la plus grande quantité d'énergie afin d'aider et guider les développeurs à optimiser leur code source et à créer des logiciels efficaces, durables et verts... [etc

The Impact of Source Code in Software on Power Consumption

International audienceWriting sustainable, power efficient and green software necessitates understanding the power consumption behavior of a computer program. One of the benefits is the fact that developers, by improving their source code implementations, can optimize power consumption of a software. Existing power consumption models need to be improved by taking into account more components susceptible to consume energy during runtime of an application. In this paper, we first present a detailed classification of previous works on power consumption modelization. Then, we introduce TEEC (Tool to Estimate Energy Consumption) model in order to estimate the power consumed by CPU, memory and disk due to the execution of an application at runtime. The main goal is to guide developers to improve their source code for optimizing energy consumption. TEEC enables determining the part of the code consuming the highest power. This will help to obtain a less energy consuming software with the same functionalities

TEEC: Improving power consumption estimation of software

International audienceRecently, researchers have begun to give importance at the energy consumed by software. But, to solve this problem, they propose often a hardware study of different devices. For this, they used hardware devices like powermeter or printed circuit. The main advantage of this methodology is the fact that we can obtain accurate results because we measure the energy consumed by components. But, we are limited at the fact that we can’t measure the power consumed by VM (Virtual Machine) and the cost of this process itself can be expansive. Estimating power consumption of software has begun a popular research field. Several tools have been presented in academic literature, however, these tools have the capacity to estimate only specific component’s consumption.ICT (Information and Communications Technologies) constitutes 2% of such gas emissions, and it is projected an increase to 4% by 2020, if nothing is done [1]. In fact, recent trends such as cloud computing and internet of things even increase the number of devices, and consequently the software running on them. Hence, software became a fundamental actor of efficiency plans that aims at reducing greenhouse gas emission.In this paper, we propose a tool, called TEEC (Tool to Estimate Energy Consumption), in order to estimate the power consumption of a given software at runtime by taking into account CPU, memory and disk power consumptions. Using TEEC, we expect to be able to obtain software/applications having some functionality and consuming less power

A kinetic study of atom transfer radical polymerization of styrene with bis(2-pyridyl)ethylenedimethanimine derivative ligands

Menteş, Ayfer (Aksaray, Yazar)Atom transfer radical polymerization (ATRP) of styrene was carried out with multidentate nitrogenbased ligands, namely N,N’-bis[phenyl(pyrid-2-yl)methylene] ethane-1,2-diamine (BPDA) and N,N’-bis[methyl(pyrid2-yl)methylene] ethane-1,2-diamine (BMDA), and catalyst systems at catalyst/ligand molar ratios of 1/0.33, 1/0.5, 1/1, and 1/1.5 by using 2 different initiators, (1-bromoethyl)benzene (BEB) and ethyl-2-bromopropionate (EBP). Linear first-order kinetic plots were observed for ATRP of styrene upon using BPDA as a ligand with both initiators. Even though the linear slopes indicate that radical concentration remains constant during reactions, high molecular weights were obtained at low conversion and showed a linear relation thereafter. To investigate the molecular weight effect, reactions were also performed in the presence of (1-bromoethyl)benzene initiator in dimethylformamide (DMF) for BPDA and in toluene for BMDA using a catalyst/ligand ratio of 1/1...

The Impact of Source Code in Software on Power Consumption

International audienceWriting sustainable, power efficient and green software necessitates understanding the power consumption behavior of a computer program. One of the benefits is the fact that developers, by improving their source code implementations, can optimize power consumption of a software. Existing power consumption models need to be improved by taking into account more components susceptible to consume energy during runtime of an application. In this paper, we first present a detailed classification of previous works on power consumption modelization. Then, we introduce TEEC (Tool to Estimate Energy Consumption) model in order to estimate the power consumed by CPU, memory and disk due to the execution of an application at runtime. The main goal is to guide developers to improve their source code for optimizing energy consumption. TEEC enables determining the part of the code consuming the highest power. This will help to obtain a less energy consuming software with the same functionalities

Towards a Green and Sustainable Software

International audienceInformation and Communication Technologies (ICTs) are responsible around 2% of worldwide greenhouse gas emissions [1]. On the other hand, the use of mobile devices (smartphone, tablet, etc.) is continually increasing. Due to the accessibility of the Internet and the cloud computing, users will use more and more software applications which will cause even an increasing effect on gas emission. Thus, an important research question is "how can we reduce or limit the energy consumption related to ICT and, in particular, related to software?" For a long time, proposed solutions focused only on the hardware design, however in recent years the software aspects have also become important. Our first objective is to compare the studies in the research area of energy efficient/green software. Relying on this survey, we will propose a methodology to measure the energy consumed by software at runtime