J H Cadena

Ignacio A Figueroa

M A Suarez

O Novelo-Peralta

G González

G A Lara-Rodríguez

Ismeli Alfonso

Production of al foams using the SDP method: Processing parameters and introduction of a new sintering device

Keywords: Aluminum foams, Cellular metals, Powder metallurgy, Sintering dissolution process

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In recent years, the interest in metallic foams has widen for several industrial applications, as the properties obtained as a result of the combination of their cellular structure and metallic properties are found to be rather attractive [1]. The most common application, in particular for Al-foams, includes crash impact absorbers, noise reduction systems and lightweight panels for automotive industry; heaters and heat exchangers, fluid filters, catalysis supporters among others for functional industry and some application in aerospace and biomedical industries [1][2][3]. This range of applications of, in particular, Alfoams is obtained for its good mechanical properties combined with low weight [START_REF] Gibson | Cellular solids: Structure and Properties[END_REF].

There are a number of processing-routes developed to produce metallic foams, however, they can be grouped mainly in the following categories: 1) according to the nature of metal (liquid and solid), 2) melt-foaming agents, 3) powder-space holders, 4) investment casting and 5) melt infiltration [START_REF] Michailidis | [END_REF][6]. In order to produce open-cell structures is necessary the employ of internal removable patterns or space holders [START_REF] Michailidis | [END_REF][6][7][8][9][10][START_REF] Ashby | Metal foams: a designguide[END_REF]. The application of materials with sacrificial functions in other areas, such as surface engineering has been reported, here sacrificial coatings and its effect on the Al-Al3Ni ultrafine eutectic formation was investigated [START_REF] Čelko | [END_REF]. However, the present author have reported the formations of highly porous metallic foams without the use of such removable patterns or foaming agents, for alloys with specific characteristics [13].

In the powder method, called Sintering and Dissolution Process (SDP), metallic powder and a water-soluble phase are mixed and mechanically compacted to produce a double-connected structure of both phases (metal and space holder, SH). Then the compact is sintered at temperature close or above the melting point of the metallic phase to produce a netshape structure with bonded particles. Finally, the water-soluble phase is removed by leaching the compact to produce open-cell metallic foams. The advantages of this process are that the porosity of final foam is closely fixed and can be modified by adjusting the water soluble/metallic particles volume ratio in the powder compact [1,14]. In this process, there are a number of parameters that affect the final structure of the foam produced, which can be associated to: 1) materials (morphology, composition, etc.), 2) compaction process (pressure and time), and 3) sinterization conditions (time, temperature and atmosphere). From the above, an adequate control of such parameters is essential in order to obtain foams with the advantages that this process offers. From this, the aim of this work is to analyze the effect of SH diameter, SH concentration and the sintering temperature on the formation of Al foams, and their respective effect on the mechanical properties. The introduction of a sintering device for producing metallic foams at temperatures below 900 °C will be also presented.

Experimental

The materials employed for the processing of metallic foams were gas atomized Al powder with irregular shape, particle size in the range of 75-200 µm (Figure 1a) and a purity of 99.5 %. For the space holder, spherical carbamide granulates provided by Sigma-Aldrich with 99 % of purity and particle sizes ranging from 1 to 2 mm were used (Figure 1b). To obtain the Al/carbamide green compact, these materials were mixed using a double cone mixer during 15 minutes. With the aim of ensuring good adhesion among Al powders and carbamide granulates, 2 vol.% of ethanol was sprayed onto the carbamide granulates before the mixing stage in order to obtain a sticky surface. Then, the mixture was poured into the steel mold and then, it was uniaxially compacted to produce cylindrical samples of around 13 mm in diameter and around 15 mm in length. The pressure used for the compaction stage of the Al/carbamide mixture was 300 MPa, for all samples. The carbamide content of the green compact was dissolved by immersion in a gently stirred water bath at 25 °C during two hours. It is worth mentioning that dissolution process was carried out before the sintering process.

For the sintering process, in this work we are proposing a new device that could be used for producing aluminum foams and other metals with sintering temperatures below 900 °C. With the use of this device, it is intended to get the maxima advantages that DSP provides. Figure 2 shows the home-manufactured device used for this research. This consists on the following parts: (a) stainless steel (ss) chamber rounded by an ss tube spiral, (b) a valve system for controlling the vacuum and gas injection, (c) a graphite flexible seal and (d) a heating system, which could be an electrical resistance furnace or a heating device with vertical chamber. The latter component could be part of the device or could be external.

The sample is located inside of the ss chamber, as shown in Figure 2. The bottom part of this chamber is attached to the top part, and sealed with the flexible graphite seal. Once this process has been completed, the vacuum valve is opened until a pressure of 6 x 10 -2 torr is reached. After this, five purges with high purity Ar are carried out. Then, a constantly controlled Ar flow is introduced through the ss spiral, being heated during its trajectory from the top of the device to the inlet, which is located at the bottom of the equipment. The combination of the Ar flow and the spiral setup not only minimizes the amount of oxygen inside the chamber, but also it keeps the sample at the desired temperature, and takes away all the fumes produced during the sintering process, leaving a clean and inert atmosphere surrounding the sample. Finally, the green compacts were sintered at temperatures from 600 °C to 660 °C (with increments of 20 °C in each experiment) in order to determine the optimum sinterization temperature, Ts. The process treatment at 660 ºC was only taken for temperature control purposes.

The foam relative density, ρ, and its, porosity, P f , were determined through the equations ( 1) and ( 2) [14,15], respectively.

Where, ρ is the theoretical relative density of the foam, ρ Al is the Al density, V Al is the Al volume fraction in the mixture, ρ SH is the carbamide density and ρ f is the foam density. The densities of green compact and foams were determined using the conventional equation ρ=m/V (m=mass, V=volume). The pore size and distribution of the Alfoams was analyzed using stereomicroscope Olympus SZX16. Field Emission Scanning Electron microscope Jeol JSM-7600F was used to observe the neck formation between Al particles and the pores interconnection. Finally, the mechanical properties of the specimens were measured by means of standard compression tests using an Instron 1125-5500R testing machine with a crosshead speed of 0.1 mm/min.

Results and discusion

Analysis of the sintering temperature effect

As expected, at a sintered temperature of 660 ºC the individual Al-particles melted down during the process, the structure of the foam completely collapsed, forming a solid ingot. When the sintering temperature was reduced down to 640 °C, the Al foam sample partially collapsed, as this temperature is rather close to the Al melting temperature. Here, the Al particles were mostly consolidated, forming much larger particles or clusters and few necks between the initial Al particles were observed. This can be attributed to the sintering temperature, which softens the Al powders, given place to the formation of such clusters. It is worthy of note that the number of interparticles pores also dropped drastically (Figure 3a). The partly collapsed Al foam shown in Figure 3a corresponds to the sample with 60 wt.% of carbamide.

At 620 ºC a number of necks between Al particles surfaces were observed, indicating a good cohesion between Al powders (Figure 3b). At this sintering temperature, the porous structure resembles that of the green compact. This fact can be observed in the resulting foam shown in Figure 3b. From these results, it can be suggested that 620 ºC can be considered as the optimum sinterization temperature, for at least, the experimental conditions reported in this work. Finally when the sintering temperature was dropped down to 600 ºC the cohesion between the Al powders was poor, as observed in Figure 3c, and the foam structure tended to crumble apart at low stresses (i.e. when handling the Al foam sample).

Analysis of the space holder concentration

Figure 4a shows the structure of the Al foam with 40 wt.% of carbamide obtained using the optimum sintering temperature (620 ºC). From this figure, the foam presented a deficient open interconnection between pores and the existence of blocking walls between pores, reducing the possibility to produce an open-cell foam structure. With the increment of the carbamide concentration, up to 50 wt.% (Figure 4b), the interconnection of the foam also increases (with four pores interconnected). Finally, the foam with 60 wt.% of carbamide (Figure 4c) presented the highest increment of the interconnection, practically, with all pores interconnected. For 50 wt.% and 60 wt.% an open-cell foam structure was obtained.

In terms of the microstructure, these results indicate that the optimal concentration of carbamide (for the present size) to produce open-cell metallic foams is 60 wt.%. Green compact samples with contents of 40 and 50 wt.% of carbamide are not suggested for the production of Al-foams with good interconnected pores, under the conditions proposed in this work. At lower carbamide contents than the reported here, the pores interconnections are totally blocked, and at higher carbamide contents, the network of metallic foams collapses during the dissolution process. On the other hand, the metallic particle sizes used in the manufacturing of Al-foams promotes the formation of micropores, which increased, slightly, the foam porosity (Figure 3b). The analysis of relative density (Absolute Density: expresses the magnitude of mass and volume of a

                V V V P Al SH Al SH Al Al f f A l 1 1 1 0 0 ( ( )) /
substance and Relative Density: is the ratio between the density and density of the other reference substance is a dimensionless number) is important in order to understand the lightweight properties. The values of relative density also give an idea of the foam porosity and the interconnection type between the Al particles. Figure 5a shows the behavior of relative density as function of Al concentration for two sizes of carbamide granulates and two different sintering temperatures. As it can be observed, the relative density decreases, as does the Al concentration, ensuring the formation of foams with an open pore structure. On the other hand, the observed decrement of the relative density could be associated to the large carbamide particles size, with respect to the size of Al powder, which promotes this level of porosity. The experimental relative density values are lower than theoretical ones; this is attributed to the size and shapes of Al particles, in addition to the bonding/union between them, during that sinterization step. Figure 5b shows that the experimental values of porosity, for all compositions, are higher when compared to the theoretical one. It is though, that this behavior is due to the sum of the porosity left by the space holder and the small amount of porosity caused by the Al spheres/particles packing (space produced between Al particles during the compaction). Although the vast majority of the porosity produced was attributed to the carbamide particles.

From the above, it can be concluded that the foams manufactured with carbamide contents of 60 %, exhibited porosity about 70 % and the high P f value is essentially caused by two contributions: a) The

Mechanical behavior

Figure 6 shows the stress () strain () curves for the foams containing 40, 50 and 60 wt.% of carbamide. For the foam of 60 wt.% the typical mechanical behavior of foamy metallic materials is observed, here three zones are clearly identified: Elastic deformation (Zone I); plateau (Zone II), where the cell edges are yielding plastically in bending; and densification (Zone III), where the structure compacts and stress rises. The behavior of the -curves did change, depending on the carbamide content. In the case of the sample with the minimum amount of carbamide, the behavior of the -curve is more closely related to that of solid aluminum, since the porous concentration is not as high as the samples with carbamide content above 50 %. From this, the blocking walls are very large and the mechanical behavior in compression of aluminum predominates. As the concentration of carbamide increases, the slope of plateau decreases as a result of the plastic deformation of such blocking walls. Besides, the instability of serrated edges observed in zone II for all foams is also attributed to the continuous or progressing collapsed of the blocking walls.

From the same Figure 6, the compression stress for densification ( r in Zone III) increased slightly from  r = 22 MPa to  r = 24 MPa, for the samples with 40 and 50 wt.% of carbamide, respectively. The inverse behavior is shown when the carbamide content is increased up to 60 wt.%, where it drops down to 12 MPa. It is though that the maximum  r , obtained for the sample with 50 % of carbamide, could be attributed to the combination of the blocking walls size and the good sinterization between Al particles. The strain values significantly increased when the carbamide content increased from 40 to 60 wt.%. Similar behavior was also observed in Zone II, where, if the stress is kept at certain value, the strain is drastically increased as the carbamide content increases. At 60 % of carbamide, the number of blocking walls increases leading an increment in the plastic behavior of the sample, but the blocking walls are too thin and easily break up. In contrast, in the sample with 40 % of carbamide, the blocking walls are much thicker, reducing the plastic deformation. As expected, the sample with 60 wt.% of carbamide showed a lower yield stress value than those for the samples with 40 and 50 wt.% (Zone I). A plausible explanation for this behavior could also be given in terms of the thickness of the walls formed during the sinterization, as mentioned above. However, on the other hand, the mechanical behavior could be improved with the small additions of Sn or Mg powders [17,18].

Effect of the proposed sintering device

The proposed sintering device probed to be rather effective for sintering, in this case, Al foams. It is thought that the highly controlled atmosphere that the design/introduction of such device does allow, prevented the oxidation of the metal powder in such fashion that even at high temperatures the resulting aluminum oxide of the Al foam came from the ROW material, although further investigation is required to confirm this assumption. It is believe that the purpose of adapting the ss tubing spiral to the main device, i.e. introducing Ar for bottom and taking it away from the top, did help to carry all the fumes and gases produced during the sintering process out of the device, preventing the contamination of the sample that is being sintered. Therefore, by using the proposed device, the sinterization process of the Al powders could be carried out under a fully controlled atmosphere.

Conclusions

Metallic foams with SH concentrations between 40 and 60 wt.% of carbamide were successfully produced with the use of the proposed original device, through the powder metallurgy method known as sintering and dissolution process (SDP). The sinterization temperature of 620 ºC was found to be the optimum process temperature to produce Al foams with good metallurgical bond among its constituent metallic particles. The foams manufactured with carbamide contents of 60 %, exhibited porosity 70 %. The high P f value obtained was probably caused by the carbamide content and the voids formed within the Al particles after the sinterization process. The maximum,  r , values were obtained for the sample with 50 % of carbamide, this was attributed to the combination of the blocking walls size and the good sinterization between Al particles. The strain values significantly rises when the carbamide content increased from 40 to 60 wt.%.The sample with 60 wt.% of carbamide showed the lowest yield stress value of the Al foams produced. It is though that this behavior is due to the thickness of the Al particles walls, which were produced during the sintering process. With the proposed sintering device it was possible to control, efficiently, the temperature and the atmosphere during the sintering stage.

Figure 1 .

 1 Figure 1. a) SEM micrographs of the Al powders and b) image of the carbamide

Figure 2 .

 2 Figure 2. Proposed sintering device

Figure 3 .Figure 4 .

 34 Figure 3. Al foam images a) sintered at 640 0 C, b) sintered at 620 0 C and c) sintered at 600 0 C

Figure 5 .Figure 6 .

 56 Figure 5. a) Relative density and b) porosity of Al foams after the sinterization process and cleaning, as a function of the Al concentration and carbamide content respectability

Acknowledgements

The authors would like to acknowledge the financial support from SENER-CONACYT 151496 and SEP-CONACYT 178289 for funding the project. A. Tejeda, J. J. Camacho, J. Morales-Rosales, E. Hernandez, M. Garcia de León, D. Cabrero, R. Reyes and C. Flores are also acknowledged for their technical support.


Cristina Silvano

Giovanni Agosta

Andrea Bartolini

Andrea R Beccari
email: andrea.beccari@dompe.it

Luca Benini
email: lbenini@iis.ee.ethz.ch

Loïc Besnard

João Bispo

Radim Cmar
email: rcmar@sygic.com

João M P Cardoso

Carlo Cavazzoni

Daniele Cesarini

Stefano Cherubin

Federico Ficarelli

Davide Gadioli

Martin Golasowski

Imane Lasri

Antonio Libri

Jan Martinovič

Gianluca Palermo

Pedro Pinto

Erven Rohou

Nico Sanna

Kateřina Slaninová

Emanuele Vitali

Adaptive Optimization and Enforcement of Extra-Functional Properties in High Performance Computing: The ANTAREX Project

Keywords: High Performance Computing, Autotuning, Adaptivity, DSL, Compilers, Energy Efficiency dseInfo.execute(opListPath); 46

établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

I. INTRODUCTION

The design and optimisation of applications for High Performance Computing systems is an extremely challenging problem, even more so when taking into account the need for energy efficiency and extreme scalability. Indeed, to achieve an Exascale supercomputer, a radical improvement in energy efficiency is necessary, as the power demand under current technology constraints would reach hundreds of MW, against a state target of 20-30 MW. According to the Green500 list 1 , which ranks supercomputers according to the GigaFlops per Watt figure of metric, the "most green" supercomputer SHOUBU SystemB installed in Japan exceeds 18 GigaFlops/W during its 857-TeraFlop/s Linpack performance run. The top positions in Green500 are all occupied by heterogeneous systems based on high-performance processors and co-processors such as the latest NVIDIA Volta GV100 GPU and PEZY SC2 accelerator to further accelerate the computation. The dominance of heterogeneous systems in the Green500 list is expected to continue for the next coming years to reach the target of 20MW Exascale supercomputers. Furthermore, even the Top500 list 2 , which measures pure performance, is dominated by the Summit supercomputer installed in the USA, which reaches a peak performance of over 187 PetaFlops with a power envelop of less than 9 MW -still above the target for Exascale.

To fulfil the Exascale target, a goal that the European Union aims at reaching by 2023 3 , energy-efficient supercomputers need to be 1 www.green500.org, June 2018 2 www.top500.org, June 2018 3 https://www.consilium.europa.eu/en/press/pressreleases/2018/06/25/supercomputers-council-agrees-to-develop-high-techinfrastructure/ coupled with a radically new software stack capable of exploiting the benefits offered by architecture heterogeneity at different abstraction levels to meet the scalability and energy efficiency required by the Exascale era. Furthermore, the current development model where the HPC center staff directly supports the development of applications will become unsustainable in the long term, due to the inherent challenges of developing applications for heterogeneous systems. Thus, the availability of effective standard programming languages and APIs is crucial to provide migration paths towards novel heterogeneous HPC platforms as well as to guarantee the ability of developers to work effectively on these platforms.

To conclude, heterogeneous systems currently dominate the top of the Top500 and Green500 lists and this dominance is expected to be a trend for the next coming years to reach the target of 20MW Exascale supercomputers. To fulfil the 20MW target, energy-efficient heterogeneous supercomputers need to be coupled with radically new software stacks to exploit the benefits offered by heterogeneity at all levels (supercomputer, job, node) to meet the scalability and energy efficiency required by the Exascale era.

Goals of the project. The ANTAREX [START_REF] Silvano | AutoTuning and Adaptivity appRoach for Energy efficient eXascale HPC systems: the ANTAREX Approach[END_REF][START_REF] Silvano | The ANTAREX approach to autotuning and adaptivity for energy efficient HPC systems[END_REF][START_REF] Silvano | The ANTAREX Tool Flow for Monitoring and Autotuning Energy Efficient HPC Systems[END_REF][START_REF] Silvano | Antarex: A dsl-based approach to adaptively optimizing and enforcing extra-functional properties in high performance computing[END_REF]] project aims at providing a holistic approach spanning all the decision layers composing the supercomputer software stack and exploiting effectively the full system capabilities, including heterogeneity and energy management. The main goal of ANTAREX is to express by means of a DSL the application self-adaptivity and to runtime manage and autotune applications for green heterogeneous HPC systems up to the Exascale level. The use of a DSL allows the introduction of a separation of concerns, where self-adaptivity and energy efficient strategies are specified separately from the application functionalities. This is promoted by the definition of a DSL inspired by aspect-oriented programming concepts for heterogeneous systems. The DSL is based on previous efforts regarding the LARA language [START_REF] Cardoso | LARA: An Aspect-oriented Programming Language for Embedded Systems[END_REF][START_REF] Cardoso | Performance-driven instrumentation and mapping strategies using the LARA aspect-oriented programming approach[END_REF] and makes possible to express at compile time the adaptivity/energy/performance strategies and to enforce at runtime application autotuning and resource and power management. The goal is to support the parallelism, scalability and adaptivity in a dynamic workload by exploiting the full system capabilities (including energy management) for emerging large-scale and extreme-scale systems, while reducing the Total Cost of Ownership (TCO) for companies and public organizations.

Key innovations.

The ANTAREX approach provides: (1) A new DSL for expressing adaptivity and autotuning strategies; (2) Enabling the performance/energy control capabilities by tuning software knobs (including application parameters, code transformations and code variants); (3) Designing scalable and hierarchical optimal controlloops capable of dynamically leveraging them together with performance/energy control knobs at different time scale (compile-, deploy-and run-time) to always operate the supercomputer and each application at the maximum energy-efficient and thermally-safe point. This can be done by monitoring the evolution of the supercomputer as well as the application status and requirements and bringing this information to the ANTAREX energy/performance-aware software stack.

The project is driven by two use cases taken from highly relevant HPC application scenarios: (1) a biopharmaceutical application for drug discovery deployed on the Marconi system at CINECA and (2) a self-adaptive navigation system for smart cities deployed on the server-side on the Anselm and Salomon systems provided by IT4Innovations National Supercomputing Center.

The ANTAREX Consortium. To achieve the ANTAREX goals, a broad range of technical expertise is needed. As a consequence, the ANTAREX Consortium comprises some of the foremost institution in European research. The consortium is led by Politecnico di Milano, one of the largest technical universities in Europe, and comprises top-ranked academic partners such as ETH Zürich, Universidade do Porto, and INRIA (with additional support from IRISA/CNRS). Realworld applications are provided by one of the leading biopharmaceutical companies, Dompè, and by the top navigation software company in Europe, Sygic. To effectively validate the tool flow, as well as to support the deployment and scale-up of the target applications, the consortium also includes two supercomputing centers, CINECA in Italy and IT4Innovations in Czech Republic. CINECA's Marconi supercomputer is ranked 18 in the Top500 as of June 2018, making it the 3rd most powerful supercomputer in the European Union, while IT4Innovations' Salomon is ranked 139.

Organization of the paper The rest of this paper is organized as follows. In section II we outline the ANTAREX approach, while in section II-A we introduce the ANTAREX DSL. In sections III and IV we introduce the target platforms and use case scenarios employed for the validation of the ANTAREX tools and methodologies. Finally, in section V we draw some conclusions.

II. THE ANTAREX APPROACH

Figure 1 shows the ANTAREX approach through its tool flow, covering both the design-time and runtime operation. The functionality of the target application is expressed through a standard programming language -the current tools support both C and C++and can therefore include legacy code. On the other hand, the extrafunctional aspects of the application are expressed through a separate specification, written in the ANTAREX DSL. The ANTAREX DSL is based on LARA [START_REF] Cardoso | Lara: An aspect-oriented programming language for embedded systems[END_REF], extended to provide support for parallelisation, mapping, precision tuning and adaptivity strategies. In this way, the expression of extra-functional concerns is fully decoupled from the functional code, allowing the application domain expert and the performance tuning expert to operate as independently as possible.

The DSL specification is weaved into the functional code at compile time, through a source-to-source transformation tool, Clava, which performs a refactoring of the application code based on the [START_REF] Kistler | Continuous program optimization: A case study[END_REF]. It allows the compiler to further optimise the code, during the execution of long runs of an application, which are typical of HPC scenarios. While most high level languages include mechanisms for selective compilation which can be exploited for fine tuning the dynamic compilation options, e.g. for hiding compilation latencies [START_REF] Campanoni | Dynamic look ahead compilation: a technique to hide jit compilation latencies in multicore environment[END_REF], the C/C++ applications commonly used in HPC scenarios generally lack this option. Some support is provided by domain-specific tools, such as RuntimeCompiledC++ [START_REF] Binks | Runtime compiled c++ for rapid ai development[END_REF], which focuses on interactive modification and recompilation of program fragments by the programmer. To enable partial dynamic compilation, ANTAREX DSL aspects can introduce calls to a support library, libVC [START_REF] Cherubin | libVersioningCompiler: An easy-to-use library for dynamic generation and invocation of multiple code versions[END_REF], allowing to weaken the boundary between compile-time and runtime, and enabling continuous optimisation.

b) Precision Tuning: Among the optimisation techniques, ANTAREX developed in particular tools for precision tuning, which has emerged as a promising approach to improve power/performance trade-offs. Precision tuning originates from the fact that many applications can tolerate some loss of quality during computation, as in the case of media processing (audio, video and image), data mining, machine learning, etc. Error-tolerating applications are increasingly common in the emerging field of real-time HPC. In ANTAREX, we explored both precision tuning of floating point computation on GPGPU accelerators [START_REF] Nobre | Aspect-driven mixed-precision tuning targeting gpus[END_REF] and floating to fixed point conversion, followed by tuning of the fixed point representation in terms of bit width and point position [START_REF] Cherubin | Implications of Reduced-Precision Computations in HPC: Performance, Energy and Error[END_REF][START_REF] Cattaneo | Embedded Operating System Optimization through Floating to Fixed Point Compiler Transformation[END_REF]. c) Memoization: Memoization has been employed for a long time as a performance optimization technique, albeit primarilyin functional languages. A survey of techniques to handle memoization at programming language level, as well as references to applications can be found in [START_REF] Acar | Selective memoization[END_REF]. More recently, memoization has been shown as a promising path for energy saving in computation-intensive workloads [START_REF] Agosta | Dynamic memoization for energy efficiency in financial applications[END_REF][START_REF]Automatic memoization for energy efficiency in financial applications[END_REF]. In ANTAREX, a library to support memoiza-tion [START_REF] Suresh | Compile-Time Function Memoization[END_REF][START_REF] Suresh | Intercepting Functions for Memoization: A Case Study Using Transcendental Functions[END_REF] has been integrated in the DSL, allowing automated exploration of memoization opportunities.

d) System Monitoring: System monitoring is a key aspect of HPC infrastructures. In ANTAREX, we leverage the ability of processing elements to provide performance metrics at hardware level through the ExaMon tool [START_REF] Beneventi | Continuous learning of hpc infrastructure models using big data analytics and in-memory processing tools[END_REF], which provides a virtualisation of the performance and power monitoring, decoupling sensor readings from sensor value use. This approach increases the scalability of the monitoring, and at the same time provides an easy access to monitoring APIs through the ANTAREX DSL.

e) Performance Tuning and Power Management: Techniques for controlling the performance of one or more applications according to system parameters such as power consumption have been developed through the last decade in both high performance and embedded computing [START_REF] Silvano | 2parma: Parallel paradigms and run-time management techniques for many-core architectures[END_REF]. Typically, a design-time phase leverage optimisation tools [START_REF]Multicube: Multi-objective design space exploration of multicore architectures[END_REF] to allow the identification of specific operating points, among which the runtime controller selects the actual configuration depending on the workload, as well as the system parameters.

In ANTAREX, at runtime, the mARGOt tool [START_REF] Gadioli | Application autotuning to support runtime adaptivity in multicore architectures[END_REF] configures the available software knobs (application parameters, code transformations and code variants) according to the runtime information coming from application self-monitoring and system monitoring, thus creating an autotuning control loop. Finally, the runtime power manager, PowerCapper, is used to control the resource usage for the underlying computing infrastructure given the changing conditions [START_REF] Bartolini | Self-aware thermal management for high performance computing processors[END_REF][START_REF] Cesarini | Prediction horizon vs. efficiency of optimal dynamic thermal control policies in hpc nodes[END_REF].

At runtime, the application control code, thanks to the designtime phase, now contains also runtime monitoring and adaptivity strategy code derived from the DSL extra-functional specification. Thus, the application is continuously monitored to guarantee the required Service Level Agreement (SLA), while communication with the runtime resource-manager takes place to control the amount of processing resources needed by the application. The application monitoring and autotuning is supported by a runtime layer implementing an application level collect-analyse-decide-act loop.

A. The ANTAREX DSL

HPC applications might profit from adapting to operational and situational conditions, such as changes in contextual information (e.g., workloads), in requirements (e.g., deadlines or energy budgets), and in availability of resources (e.g., connectivity or number of processor nodes available). A simplistic approach to both adaptation specification and implementation (see, e.g., [START_REF] Floch | Using architecture models for runtime adaptability[END_REF]) employs hard coding of conditional expressions and parameterizations, among others. In our approach, the specification of runtime adaptability strategies relies on a DSL implementing key concepts from the Aspect-Oriented Programming (AOP) paradigm [START_REF] Irwin | Aspect-oriented Programming[END_REF]. We use this language to target specific execution points and specify adaptation concerns.

Our approach is based on the idea that certain application/system requirements (e.g., target-dependent optimizations, adaptivity behavior and concerns) should be specified separately from the source code that defines the main functionality, and without changes to the original application source code. Those requirements are expressed as DSL aspects that embody strategies. An extra compilation step, performed by a weaver, merges the original source code and aspects into the intended program [START_REF] Elrad | Aspect-oriented Programming: Introduction[END_REF]. Using aspects to separate concerns from the core objective of the program results in cleaner programs. Moreover, the reusability of strategies can be a viable path to increase productivity. The development process of HPC applications typically involves two types of experts (application-domain experts and HPC system architects) that split their responsibilities along the boundary of functional description and extra-functional aspects. Our DSL-aided toolflow provides a suitable approach for helping to express their concerns.

The ANTAREX DSL relies on the already existing LARA language and framework [START_REF] Cardoso | LARA: An Aspect-oriented Programming Language for Embedded Systems[END_REF][START_REF] Cardoso | Performance-driven instrumentation and mapping strategies using the LARA aspect-oriented programming approach[END_REF], which was adopted and extended. We developed the Clava4 weaver to leverage the rest of the ANTAREX tool flow through aspects and APIs. Compared to other approaches that usually focus on code injection (e.g., [START_REF] Spinczyk | AspectC++: An Aspect-oriented Extension to the C++ Programming Language[END_REF]), LARA provides access to other types of actions, e.g., code refactoring, compiler optimizations, and inclusion of additional information, all of which can guide compilers to generate more efficient implementations. Additional types of actions may be defined in the language specification and associated weaver, such as software/hardware partitioning [START_REF] Cardoso | Controlling a complete hardware synthesis toolchain with LARA aspects[END_REF] or compiler optimization sequences [START_REF] Nobre | Use of Previously Acquired Positioning of Optimizations for Phase Ordering Exploration[END_REF].

The LARA language is compatible with the ECMAScript 5 specification 5 , which means that JavaScript code that conforms to that specification is usually considered valid LARA code. Besides supporting plain JavaScript in .js files, LARA extends JavaScript with several new keywords and syntax constructs, which can only be used in .lara files.

On a more detailed level, the keyword aspectdef marks the beginning of an aspect. An aspect is similar to a JavaScript function but where LARA keywords and constructs can be used. The weaver, before execution of a .lara file, implicitly parses the target sourcecode (e.g., a C++ program) and creates an abstract representation that will be accessible during the execution of the LARA strategy. The keyword select allows specifying the points in the code (e.g., function calls) that one wants to analyze or transform. The selection is hierarchical and similar to a query. For instance, select function.loop end selects all the loops inside all the functions in the target source code. The apply block is similar to a for loop that iterates over all the points of the previous selection, herein simply referred as join point. Each join point has a set of attributes, which can be accessed, and a set of actions, which can be used to transform the code. Finally, the condition keyword can be used to filter a join point selection.

These are the basic elements of the LARA language that can be used to define strategies for code transformation and runtime adaptability. For more specific operations, the Clava weaver provides APIs that implement commonly used strategies (e.g., time measurement around program segments), as well as APIs for the integration of other ANTAREX components.

As an example of an integration API, consider the LARA code presented in Figure 2, which is an excerpt of a LARA strategy that fully integrates the mARGOt autotuner into an application. The shown strategy will generate the needed configuration files for mARGOt and also enhance the original application with calls to the mARGOt API in order to provide runtime adaptation capabilities. The aspect is parameterized with the name of function whose calls we will be targeting, as well as the paths to configuration files. There is a top level aspect, MargotIntegration, that calls the other aspects, which one performing a specific task. in MargotConfig, using the API provided with Clava, the user configures all information for mARGOT. This is done in lines 13-26 and configures the knob the autotuner will set, the metric to be collected and the objective function to minimize. At the end of this aspect, the configuration object is used to generate and return additional information for the following steps. Then, in MargotDse, in lines 32-43, this strategy performs a design-space exploration. This generates a list of operating points that map each tested value of the knob to a value of the collected metric. In this specific case, the application will be tested 30 times with the values defined in line 41 and the average execution time for each of those values is reported. This will be written to a file that represents the initial knowledge base of the autotuner. Finally, in the MargotCodeGen aspect (lines 47-54), the application code is changed to include calls to the autotuner interface. These are the calls that will cause mARGOt to check its internal state and update the values of the knob. The strategy selects function calls using their name as a filter and then pass the selected points to the API calls that will surround them with the necessary code. Using such an API, one does not need to know what code is going to be inserted, but rather needs to specify what actions need to be performed.

III. TARGET PLATFORMS

The target platforms are two PetaFlop class systems, the CINECA's top-level supercomputer, Marconi, and IT4Innovations Salomon supercomputer.

A. CINECA Platform & Roadmap

CINECA, to further its institutional mission to support the competitiveness of the Italian research infrastructure, including its participation to the international supercomputing enviroment in Europe (PRACE), operates an evolving, massive infrastructure aiming at a convergence of computing and data handling tasks. CINECA aims at growing its infrastructure to bridge the gap to Exascale around 2023, as well as to support emerging paradigms such as Big Data analytics, real-time HPC, and cloud HPC.

The current supercomputing machine (Marconi), in production from the second-half of 2016, is set up as a scalable hybrid cluster starting at 10 PFLOPS, and currently benchmarked at a peak of 16 PFPLOS 6 . The CINECA roadmap will lead to a scale up of the Marconi machine to over 20 PFLOPS in 2019, and up over 200 PFLOPS by 2022, with a power envelop growing from the current 3 MW to around 10 MW.

However the path following to high-end computing and data managing has revealed during the last ten years or so, a major constraint in the exponential growth of power consumption in a way that is now commonly accepted the sustainable limit of 20MW for the first exaFLOPS supercomputing system. With this limit in mind, CINECA is modelling its strategy for future HPC/DA systems in order to experiment, design and deploy energy-aware supercomputing facilities. To this end, CINECA has been involved in several projects at national and EU level to take advantage of the most promising techniques for limiting the overall requirements of energy-to-solution computing workflow [START_REF] Cavazzoni | EURORA: A European Architecture Toward Exascale[END_REF][START_REF] Bartolini | Unveiling Eurora -Thermal and Power Characterization of the Most Energy-efficient Supercomputer in the World[END_REF][START_REF]Mont-Blanc (FP7-ICT-2011-7 European project): European scalable and power efficient HPC platform based on lowpower embedded technology[END_REF][START_REF]Mont-Blanc 2 (FP7-ICT-2013-10 European project), European scalable and power efficient HPC platform based on low-power embedded technology[END_REF].

In the context of ANTAREX, CINECA is employing the A2 partition of Marconi7 , which includes 3,600 nodes, each equipped with a 68-cores Intel Xeon Phi7250 (Knights Landing), clocked at 1.4 GHz, for a total of 244,800 cores. Each node is equipped with 16 GB/node MCDRAM + 96 GB/node DDR4. The partition has a peak performance of 11 PFLOPS.

B. IT4Innovations Platform & Roadmap

IT4Innovations as the National Supercomputing Center of the Czech Republic operates two HPC clusters as of 2018. The first one is a 2 PFLOP/s system called Salomon having 1008 nodes based on Intel Haswell CPUs8 . Half of its computing power is provided by Intel Xeon Phi accelerators 9 based on the Knights Corner architecture. It uses InfiniBand FDR56 interconnect in 7D Enhanced hypercube topology.

The second cluster is a smaller 94 TFLOP/s system called Anselm. It has 209 nodes based on Intel Sandy Bridge CPUs 10 . It also contains 23 GPU accelerated nodes 11 and 4 MIC accelerated nodes 12 .

Each cluster has its own dedicated storage available, including distributed filesystem LUSTRE. Apart from this, each cluster has a set of nodes dedicated for virtualization with its own storage which can be used to run virtual machines providing auxiliary services. The ANTAREX project used both machines including their virtualization infrastructure extensively.

During the project a small portion (18 nodes) from the Anselm cluster has been removed from the PBS scheduler queues and dedicated entirely for development and integration activities related to the UC2. The dedicated partition has been isolated in a private network segment accessible only through a VPN operated by IT4Innovations. Access to the this infrastructure has been restricted only for members of the ANTAREX consortium involved in the UC2 activities.

Main purpose of the dedicated partition was to gain a privileged access to the computing hardware for testing of various network settings and running performance monitoring tools which require privilege It has been used mainly for verification and validation of the server-side routing service using the traffic simulator. Integration of the mARGOt autotuner has been also tested there. The next step is to use the dedicated partition to test tools which require privilege escalation, mainly mARGOt autotuner with energy constraints measured by PAPI and other related experiment.

The remaining production part of the Anselm cluster has been used for scalability and performance tests of the experimental server-side routing service. It is also used for ongoing verification and validation of the developed service using the traffic simulator and large number Sygic navigation app instances.

The Salomon cluster is used mainly for computing what-if scenarios using the betweenness centrality algorithm. It has been also used for performance and scalability testing of multi-node implementation of the algorithm and also to verify and validate tools developed by INRIA integrated in the algorithm.

IV. APPLICATION SCENARIOS

To demonstrate the impact of the ANTAREX toolchain, the project leverages two applications from emerging domains.

The first application is drawn from the computational chemistry domain, and aims at speeding up dramatically the early phases of the drug discovery process, allowing a fast screening of a large amount of potential drug molecules. The second application is drawn from the navigation system domain, and aims at introducing a server-side aspect to the navigation, with the final goal of providing directions to vehicles in a coordinated manner, to ensure a near-optimal transit time to each vehicle.

The two applications are well positioned, since they represent two critical societal challenges, and map to two different classes of HPC applications -the massively parallel class, and the real-time HPC class.

A. Drug Discovery

The goal of a drug discovery process is to find novel drugs starting from a huge exploration space of possible molecules. Typically, this process involves several in vivo, in vitro and in silico tasks ranging 10 2 x Intel Sandy Bridge E5, 2.4 GHz, 8 cores, 64/96 GB RAM, per node 11 NVIDIA Kepler K20m 12 Intel Xeon Phi 5110P from chemical design to toxicity analysis. Molecular docking is one stage of this process. It aims at estimating the three-dimensional pose of a given molecule, named ligand, when it interacts with the target protein. The ligand is much smaller than the target protein, therefore we focus a small region of the target protein (or receptor), named pocket (or binding site). Given the three-dimensional pose of the ligand within the pocket, we are able to estimate the strength of the chemical and physical interactions between the ligand and the pocket by computing a geometric fitting score.

The evaluation of the pose of each ligand is independent from the evaluation of all the other candidates. Given that in drug discovery the number of ligands that we are interested in analyzing is above the billion of units, this problem can be considered embarrassingly parallel. However, to find the three-dimensional pose of the ligand when it interacts with the pocket, we have to deal with a large number of degrees of freedom.

As evaluating the chemical and physical interactions between the ligand and the pocket is a computationally intensive problem, the of splitting the pose prediction task from the virtual screening task is a clear consequence. The pose prediction task focuses on providing the best pose for a given ligand within a given binding site, whereas the virtual screening task aims at selecting among a huge database of candidates a small set of promising ligands which best fit the given binding site. A remarkable difference between the pose prediction and the virtual screening task lies in the approach to the estimation of the chemical and physical interactions between the ligand and the pocket, and how to determine the pose to be evaluated.

The estimation of the interactions between the ligand and the pocket can be done with either a geometrical or a pharmacophoric approach. The geometrical approach estimates the ligand-pocket interactions by only using the shape and volume information, whilst the pharmacophoric approach evaluates the actual chemical and physical interactions. Although the best solution according to a pharmacophoric approach has also a very good geometrical score, the best geometrical solution does not guarantee to be either a valid solution or a good solution from a pharmacophoric perspective. On the other side the geometrical evaluation is orders of magnitude faster than the pharmacophoric.

On the other side, to estimate the poses to be evaluated we have also 2 alternatives: a pure geometrical and a molecular dynamic based approach. The former is based on playing on the molecule flexibility to geometrically fit the ligand in the pocket, while the latter is based on a molecular simulation that places the atoms on a minimal energy point. Also in this case, while the geometrical approach provides a faster time to solution, the other one is more accurate in finding better poses.

The use of molecular simulations together with a pharmacophoric estimation represents the most accurate solution but also the most computational-intensive approach. it is regularly exploited on the pose prediction task. The combined geometrical approach on the other side ca be exploited for the virtual screening phase.

In ANTAREX, we focused on the combination of the geometrical approaches with the goal of screening a huge amounts of ligand. Indeed, we developed within LIGEN a completely new module GeoDock for molecular docking that is based only on geometric evaluations. This reduces a lot the cost of the docking process by enabling the user to increase the size of the ligand database to be processed during the virtual-screening task. Given that, it is possible to process each ligand of the chemical library in an independent way, and given the size of the target ligand library, the problem can be considered embarrassing parallel. GeoDock is a typical example of batch application optimized for homogeneous HPC platforms that can scale up to exascale.

Figure 3 and4 show a preliminary analysis of the week and strong scaling for the GeoDock module while running on the MARCONI-A2 partition composed of Intel KNL nodes. In particular, Figure 3 shows the elapsed time of a GeoDock run while considering 100 ligands. The considered number of nodes ranges from 8 to 128, while each node runs 68 MPI processes. From the figure it is possible to notice how starting from 128 nodes we see a bad weak-scaling behavior. While the small oscillations up to 64 are due to the different types of ligands we are screening (the computation is data-dependent), at 128 nodes we noticed a bottleneck on the I/O that almost double the execution time. These initial results have been used to optimize the I/O part of the GeoDock module. On the opposite, Figure 4 show how the application throughput varies while increasing the number of ligands per MPI process while considering a setup with 32 nodes and 68 MPI procesess per node. Given that there is no synchronization inside the application, this experiment can be considered as a proxy of a strong scaling. In particular we can notice a smooth performance degradation starting from around 30 ligands per MPI process. As for the previous case, the small oscillations we can observes for values larger than 30 are due to the data variability.

B. Navigation

Main focus of this use case is to integrate and verify the ANTAREX tools in an experimental server-side navigation system.

The navigation system provides an on-line navigation service which maintains a global view on state of the road network at a given geographical area as well as the means for executing a hypothetical traffic scenarios which can occur in the road network.

Many modern cities need to cope with rapid growth of traffic volume in the recent years. Expansion of the road network is a very expensive and long-term task and in some cases (city centers, dense agglomerations) virtually impossible due to lack of available space. The other option is to divert the traffic in a way which would be nearly optimal for each individual car. This can be achieved by various means such as dynamic road signs and large displays, lane switching or dynamic signaling plans for junctions. These means can be inefficient because it is impractical to deploy them on every street in a city. Another approach is to implement an on-line navigation service and use smart phones as endpoints for such system. Modern phones have all capabilities needed for using such system. The GPS receiver is used to get actual position with sufficient precision and mobile data connection can be used to communicate with the service in real time. Both approaches can be combined as the serverside routing service can be enriched by data from various other sources (weather models, stationary traffic sensors) and the traffic infrastructure can from results of this data fusion to provide more precise information for the dynamic elements of the infrastructure (junction signaling, overhead highway displays and others).

The communication with the service can be bi-directional, as the mobile phone obtains the optimal route from the system and can provide feedback which would enhance the service awareness of the traffic network current state. In order to provide consistent service for the user, the smartphone application should be able to switch between offline and online navigation, in case there is a lack of mobile phone coverage and optimize the amount of communication needed for sending the feedback.

In the context of UC2, the server-side routing service is developed by IT4Innovations in collaboration with Sygic who provides its navigation smartphone app as a client-side endpoint for the routing service. Part of the server-side routing service is also a web-based interface for computing a betweenness centrality of a road network which can be used to model behavior of the traffic under certain conditions [START_REF] Hanzelka | Betweenness propagation[END_REF]. The web-based interface allows defining a number of what-if scenarios, including road closure, event which affects speed on roads in a given area and other options. The system is seamlessly integrated with HEAppE service 13 which is used to submit the computation job with the scenarios on the cluster [START_REF] Svatoň | Floreon+: A web-based platform for flood prediction, hydrologic modelling and dynamic data analysis[END_REF]. Results of the computation can be access using the same interface when the job is finished.

UC2 makes use mainly of these tools, LARA DSL, mARGOt autotuner [START_REF] Gadioli | Application autotuning to support runtime adaptivity in multicore architectures[END_REF] and library for precision reduction and memoization provided by INRIA. Both parts of the system use the tools. On the server-side, the DSL is used to generate a part of the data access layer for the routing index stored in a HDF5 format [START_REF] Golasowski | Expressing and applying c++ code transformations for the hdf5 api through a dsl[END_REF]. It is also used to inject the integration code for the autotuner. mARGOt itself is integrated in the Probabilistic Time-Dependent Routing (PTDR) algorithm in the routing pipeline [START_REF] Golasowski | Performance evaluation of probabilistic time-dependent travel time computation[END_REF]. It is used to estimate a number of Monte Carlo samples needed to obtain estimation of the travel time with sufficient precision. The autotuner is also used in a management process which facilitates communication with the actual routing workers to estimate number of workers of each type needed to satisfy current intensity of requests while conforming to a given SLA. Also the client side makes use of the the mARGOt autotuner with the goal to optimize the requesting frequencies towards server-side services subject to constraints on navigation quality and data transfer limits. This is to alleviate server-side processing load to make system scalable and more robust across dynamic conditions.

In order to validate function of the server-side routing a traffic simulator has been developed. This software simulates cars driving around a given region along routes provided by the routing service [START_REF] Ptošek | Real time traffic simulator for self-adaptive navigation system validation[END_REF]. A snapshot of such simulation in progress is shown in Figure 5. Global view on the traffic situation in this simulated traffic network is derived from the output of the simulator and fed back to the service by the generated probabilistic-speed profiles. This simulator will be used to prepare a set of deterministic scenarios with given traffic obstacles which will be used to validate the integrated tools. This part is the main experiment of the UC2, where the routing service will be validated along with the individual tools. We expect that the routing service will optimize traffic for the specified scenarios such that all simulated cars will arrive at their destinations in shorter time in case they are using the server-side navigation that in case when only offline navigation is used. This will be tested by generating probabilistic speed profiles for each scenario with given traffic event and comparing the results with simulation executed only with simple routing algorithm which is not aware of the traffic network state.

The next step is to validate function of the autotuning tools. Operating points for the mARGOt autotuner used in the PTDR algorithm will be derived from the profiles, which in turn are derived from the traffic scenarios described above. The same scenario will be executed again with the autotuner, while the expectation is that it will not affect the SLA and the sum of Monte Carlo samples required for the entire simulation will be lower than in the case without any autotuning. Simulation logs will provide timing of the individual requests passing through the stages of the routing pipeline. These data will be used to generate operating points for the autotuner used in the management process for workers autotuning. The same scenario will be executed again, this time with workers autotuning enabled. The expectation is that the SLA is again not violated and the number of running workers at any time during the simulation will be less or same as without the workers autotuning enabled. Similarly the autotuner on the client-side, derived from data transfer statistics of simulations and augmented with the definition of quality functions, will prove to achieve comparable navigation quality using less number of requests towards server-side services.

The Betweenness algorithm implementation utilizes tools developed by INRIA for reduction of floating point precision and memoization. Small scale tests (single city) have been executed with promising results, the results are shown in Figure 6. Large scale tests (entire region or country) are planned for near future to be executed on the Salomon cluster. We expect that tools provided by INRIA will improve the scalability of the algorithm while maintaining its sufficient precision.

V. CONCLUSIONS

To fully exploit the heterogeneous resources of future Exascale HPC systems, new software stacks are needed to provide power management, optimization, and autotuning to the parallel applications deployed on such systems. The ANTAREX project provides a holistic system-wide adaptive approach for next generation HPC systems, centered around a domain specific language that allows a full decoupling of functional and extra-functional specifications for each application, providing integration with a wide range of support tools.

We have shown how the ANTAREX tool flow allows developers to control the precision of a computation, to manage dynamic code specialization, monitoring, power capping, and dynamic autotuning. The impact and benefits of such technology are far reaching, beyond traditional HPC domains.

The ANTAREX tools are being used to support large scale experiments on supercomputing systems with peak performances in the order of one to ten PFLOPS, allowing the project to project its results towards the incoming pre-Exascale machines that will be deployed in Europe in the next couple of years.

Fig. 1 .

 1 Fig. 1. The ANTAREX Tool Flow

Fig. 2 .

 2 Fig.2. Excerpt of a LARA strategy for the integration of the mARGOt autotuner into an application.

Fig. 3 .

 3 Fig. 3. Weak scaling analysis for the GeoDock module.

Fig. 4 .

 4 Fig. 4. Strong scaling analysis for the GeoDock module.

Fig. 5 .

 5 Fig. 5. Snapshot of the traffic simulation in progress, with both simulated floating car data (points) and state of the virtual traffic network (lines) visible.

Fig. 6 .

 6 Fig. 6. Small scale test of the multi-node implementation of the betweenness algorithm executed on road network of Vienna with various floating point types.

https://github.com/specs-feup/clava

Support for some features of more recent specifications has been added, such as the for...of statement, when used in .lara files.

https://www.top500.org/list/2018/06

https://wiki.u-gov.it/confluence/pages/viewpage.action?pageId=131696536

2 x Intel Xeon E5-2680v3, 2.5 GHz, 12 cores, 128 GB RAM per node

2 x Intel Xeon Phi 7120P, 61 cores, 16 GB RAM

http://heappe.eu

ACKNOWLEDGEMENTS

The ANTAREX project is supported by the EU H2020 FET-HPC program under grant 671623. The IT4Innovations infrastructure is supported by the Large Infrastructures for Research, Experimental Development and Innovations project "IT4Innovations National Supercomputing Center -LM2015070". The CINECA infrastructure is supported by the EU and the Italian Ministry for Education, University and Research (MIUR) under the PRACE project.


Lamy Laurent

Rousselot Philippe

1) Introduction

The study of the solar system is fundamental to answer key questions from the NASA Strategic Plan Objective 1.5: "Ascertain the content, origin, and evolution of the solar system and the potential for life elsewhere". The UV spectral range is a crucial window to investigate a large area of phenomena associated to this objective from the surface to the atmosphere and magnetosphere of the solar system bodies. The UV measurements of the surface albedo and polarisation can provide information on the surface activity (volcanisms, plumes), its composition in water ices / organic matter and its texture (particule size, roughness, ...). The remote UV measurements are also a very useful tool to investigate the composition of the planetary atmospheres and aerosols content, especially for objects far from the sun, where in-situ missions will not be sent in the future. Finally, UV studies (for example from HST or Hisaki) have provided a large amount of information on the planetary magnetospheres of the giant gas planets Jupiter and Saturn and their electromagnetic interaction with their satellites that can be extended to giant ices planets (Uranus and Neptune) and used to interpret possible weakest detection of exoplanets auroral emissions. In this white paper, we will summarize few examples of the major science results that could be obtained from future UV measurements of surfaces (section 3), atmospheres (section 4) and magnetosphere (section 5) for different objects in the solar system.

2) Planetary Surfaces

UV observations uniquely probe the surface of telluric bodies of the solar system. They diagnose their volcanic and plume activity, their interaction with the solar wind and their composition in the frame of space weather and exobiology/habitability fields [START_REF] Hendrix | Ultraviolet properties of planetary ices[END_REF]. For example, UV emissions associated to the plume activity from the surface of Europa [START_REF] Roth | Transient water vapor at Europa's south pole[END_REF]) has been detected from Hubble Space Telescope (HST). This activity could be due to tidal stress opening and closing fractures at the surface, but the frequency of this activity is still unknown and new observations are required to confirm this theory. UV emissions from the Io plasma torus, produced from Io volcanoes can be used to study the effect of the volcanic activity at the Io surface on the Jovian magnetosphere [START_REF] Mendillo | Io's volcanic control of Jupiter's extended neutral clouds[END_REF][START_REF] Yoneda | Brigthening event seen in observations of Jupiter's extended sodium nebula[END_REF]. UV spectroscopy with imaging and polarimetric capability will be useful, not only to study transient event due to geological processes but also to study the composition and texture of the surface ices, their spatial variations and the atmosphere bubbles trapped in them. Several UV spectral features can be used to study the composition of the surface of icy objects. For example the strong absorption features of the albedo near 330 nm or near 180 nm is a typical signatures of SO 2 ices and H 2 O ices observed at Io and Ganymede respectively, while iceless surfaces have a featureless UV spectra [START_REF] Hendrix | Ultraviolet properties of planetary ices[END_REF]. For icy surfaces, UV features can also be due to the absorption by trapped gas ("microatmosphere") like the absorption near 260 nm in the reflected solar flux by the surface of Ganymede, Rhea, Dione, Tethys due to O 3 in the surface ices [START_REF] Noll | Detection of ozone on Ganymede[END_REF][START_REF] Noll | Detection of ozone on Saturn's satellites Rhea and Dione[END_REF]. Knowing the composition of the surface ices and trapped gas is important to better understand the chemistry induced by surface sputtering [START_REF] Johnson | O2/O3 Microatmospheres in the surface of Ganymede[END_REF]. Imaging of the surfaces has been used in the past to study longitudinal variations of the surface reflectance showing leading/trailing asymmetry associated to the ion bombardement of the surface from magnetospheric heavy ions [START_REF] Johnson | Analysis of Voyager images of Europa -Plasma bombardment[END_REF]) and jovian/anti-jovian assymetries associated to neutral or dust impact. The determination of the surface composition of primitive bodies in the solar system is fundamental to understand the origins and formation of the planets. Organic and ice composition of the crust of comets, asteroids, Kuiper Belt Objects (KBOs) can be studied from their surface UV spectrum. The UV spectral regime is important to assess the presence of carbon on primitive bodies such as C, B, D asteroids and comets nuclei, since this element is nearly featureless both in the visible and in the IR but in the UV ,carbon in various forms (amorphous, graphitized, hydrogenated, glassy), has a very important peak at 210-220 nm, and an absorption signature at 80 nm.

When the solar unpolarized light is scattered by a rough surface or a dust covered surface of a solar system body, it becomes partially linearly polarized. At low phase angle, the polarisation is negative (parallel to the scattering plane) while at large phase angle, the polarisation is positive (perpendicular to the scattering plane) [START_REF] Geake | Experiments to test theoretical models of the polarization of light by rough surfaces[END_REF]. The variations of the polarisation with the phase angle curve is a signature of one surface, and has been used in the past to infer properties of the surfaces of solar system bodies (e.g. [START_REF] Geake | Planetary surface texture and albedo from parameter plots of optical polarization data[END_REF]. It is therefore another useful tool to characterize surface properties. Numerous polarimetric observations of solar system bodies have been done in the optical spectrum but very few at UV wavelengths were obtained so far. For example, The Wisconsin Ultraviolet Photopolarimeter Experiment (WUPPE) observations of Io has revealed a surface spatially covered by 25% SO 2 frost with polarization variations associated to different volcanic regions (Fox et al. 1997a). Observations of the Moon show a transition in the scattering of the UV light near 220 nm with a scattering from grains surface for wavelength < 220 nm and volume scattering for wavelength > 220 nm [START_REF] Fox | Solar sytem observations by the Wisconsin Ultraviolet Photopolarimeter experiment: III The first ultraviolet linear spectropolarimetry of the Moon[END_REF]). Such processes have been studied in the past to explain the change of polarisation with phase angle at visible wavelength (e.g. [START_REF] Steigmann | A polarimetric model for a dust-covered planetary surface[END_REF] but systematic observations of the UV polarisation of the surface of different objects in the solar sytem could open a new field of investigation to constrain the surface properties (refractive index, surface roughness, particle size). Remote measurements of the surface properties of the objects of the solar system could be validated/calibrated in the future and then be used to study surface properties of exoplanets, interstellar objects (like Oumuamua) that can not be reached by spacecrafts.

3) Planetary Atmospheres

Several processes can polarize the light in planetary atmospheres: Rayleigh diffusion, hazes, aerosols, etc. The Rayleigh scattering cross section varies as ~ 1/λ 4 while the scattering by aerosols varies as ~ 1/λ. Therefore the Rayleigh scattering is generally dominant at short wavelength while aerosols scattering is dominant at large wavelength in UV range. The transition between the two processes depends on the size of aerosols and pressure. On Mars, at a phase angle V = 21.7°, the linear polarized reflected light in the spectral range 200 -400 nm is due to the atmosphere, while the reflected light in this spectral range is due to the surface and the atmosphere (Fox et al. 1997b) (Fig. 1). Fox et al. 1997b). Between 200 and 400 nm, the sun unpolarized can be scattered by the atmosphere (Rayleigh scattering and aerosols) and the surface. The linear polarization P(λ) = (I perp (λ) -I para (λ))/(I perp (λ)+I para (λ)) is mostly due to the atmosphere, while the total reflected light : I perp (λ)+I para (λ) is due to the surface and the atmosphere.

Fig. 1 Example of UV polarimetric observations for an optically thin atmosphere like Mars at low phase angle (based on

Therefore, the combination of both can be used to derive simultaneously the UV albedo the surface and the atmosphere as done in the past from the WUPPE observations. From these observations, the surface pressure of Mars was derived. These observations prove that polarized observations of other bodies with tenous atmosphere in the solar system like Ganymede, Pluto, etc will be useful to study the aerosol content and atmospheric pressure and its composition. On Venus, because of the thick atmosphere, the polarisation is only due to the atmosphere. It has been measured at few wavelengths by Pioneer Venus Orbiter for different phase angle showing a contrast in the polarisation of the dark regions and the bright region of the atmosphere of Venus [START_REF] Esposito | Polarization studies of the Venus UV contrats: Cloud height and haze variability[END_REF] and the Rayleigh optical thickness and haze optical thickness deduced from a fit with a three layers model. The full UV spectrum at high spectral resolution coordinated with spectral imaging of Venus could be used to derive new information on the unknown absorber responsible of the dark UV regions (e.g. [START_REF] Frandsen | Identification of OSSO as a near-UV absorber in the Venusian atmosphere[END_REF]. Such studies could be extended to other objects with a thick atmosphere like gas giants and ice giants planets, although the phase curve will be limited for an observer near Earth. Independantly of polarimetric observations spectroscopy in the UV range permits to detect a large number of lines corresponding to many atomic or molecular species observed in the gas phase. It is especially true for cometary atmospheres where the UV spectral range corresponds to several interesting molecular / atomic species in the cometary coma / tails. We can mention CO, OH, H 2 , CS 2 , CS, H, C, N, S, O, CO + , CO 2 + . For OH and CO isotopic ratios can be derived, especially D/H with OH (emission lines at 309 nm). The recent discovery of N 2 in comet 67P by the ROSINA instrument on-board Rosetta [START_REF] Altwegg | Molecular nitrogen in comet 67P/Churyumov-Gerasimenko indicates a low formation temperature[END_REF], an important tracer of physical conditions prevailing at the time of comet formation, offers also a good opportunity to search for this species in the UV range (even if N 2 + can also, only in a very few cases, be observed in the optical range). The Rosetta/ALICE UV observations revealed a different environment in the low activity 67P comet, driven by electron impact rather than photochemistry [START_REF] Feldman | FUV Spectral Signatures of Molecules and the Evolution of the Gaseous Coma of Comet 67P/Churyumov-Gerasimenko[END_REF]. Such observations open also a new field of investigations for an instrument observing in the UV.

Instruments with high sensitivity will observe the tenuous atmospheres that should be present around small bodies like Ceres. Search for UV atomic emission lines (H, O, S) in the exosphere of Ceres have been done with HST but no detectable emissions have been observed [START_REF] Roth | Constraints on water vapor and sulfur dioxide at Ceres: Exploiting the sensitivity of the Hubble Space Telescope[END_REF]. Such detections could be important to know if there is a persistent exosphere around Ceres or only a transient exosphere associated to enhancements of the solar wind flux (Schorgofer et al. 2017).

4) Planetary magnetospheres and Auroral emissions

The giant planets' UV aurorae are mainly radiated from atmospheric H and H 2 species, collisionally-excited by accelerated charged particles precipitating along the auroral magnetic field lines. Aurorae thus directly probe complex interactions between the ionosphere, the magnetosphere, the moons and the solar wind [START_REF] Clarke | Jupiter's aurora[END_REF]. Aurorae can be used to understand the energy transport and dissipation through the giant magnetospheres [START_REF] Bhardwaj | Auroral emissions on the giant planets[END_REF]. Precipitation of auroral particles is additionally a major source of atmospheric heating, whose knowledge is needed to assess the energy budget, the dynamics and the chemical balance of the atmosphere [START_REF] Majeed | Process of auroral thermal structure at Jupiter: Analysis of multispectral temperature observations with the Jupiter Thermosphere General Circulation Model[END_REF]. A high sensitive UV spectro-imager will measure the complex aurorae of Jupiter and Saturn and, the fainter ones of Uranus and catch those of Neptune, only seen by Voyager 2 [START_REF] Lamy | The aurorae of Uranus pas equinox[END_REF]. A spectrometer with a high spectral resolution will be used to finely map the energy of precipitating electrons from partial spectral absorption of H 2 by hydrocarbons [START_REF] Ménager | H Lyman α line in Jovian aurorae: electron transport and radiative transfer coupled modelling[END_REF][START_REF] Gustin | Statistical study of Saturn's auroral electron properties with Cassini/UVIS FUV spectral images[END_REF] and the thermospheric wind shear from the H Lyman-α line [START_REF] Chaufray | Asymmetry in the Jovian auroral Lyman-α line profile due to thermospheric high-speed flow[END_REF]. The measurement of the linear polarization induced by the Hanle effect on the Lyman-α line could provide a way to measure the magnetic field at the "surface" of Jupiter (near 1 bar) (BenJaffel et al. 2005). Finally, highly sensitive observations of the temporal variations of the auroral structures (oval or bright spots) of the jovian moons like Ganymede and Io can be used to constrain their conductive layer (thickness, conductivity) below their surface [START_REF] Saur | The search for a subsurface ocean in Ganymede with Hubble Space Telescope observations of its auroral ovals[END_REF][START_REF] Roth | Constrains on Io's interior from auroral spot oscillations[END_REF]. Such a method is more difficult to use for a rather patchy auroral structure as observed on Europa [START_REF] Roth | Europa's far ultraviolet oxygen aurora from a comprehensive set of HST observations[END_REF]), but spectro-imaging with a better sensitivity could help to extend this method to Europa and provide constrain on the conductivity and then, ion concentration of its water ocean, possibly linked with the surface plumes observed (see section 2).

Conclusion

The UV spectral range is a crucial window to investigate a large area of phenomena associated to the surface, the atmosphere and the magnetosphere of the solar system bodies.

In this white paper, we have presented few examples of major science that should be studied thanks to the higher sensitivity and new techniques (polarization) from the next generation of UV telescope (e.g.. LUVOIR) that will open new possibilities of exploration in the solar system.