br>Giving visibility and legitimacy to the debate on singular care practices in the territories is to strengthen the SUS! ¡Dar visibilidad

Next-generation Multiprocessor, or Multicore, Systems-on-Chip offer very high computing performance at the expense of a very high power density unevenly distributed on the chip. The hot spots thus generated represent a significant source of performance and reliability degradation, as well as power consumption increase. In recent years, run-time thermal control strategies have been developed to deal with this issue by acting on some "computational knobs" (e.g., clock frequencies and supply voltages). In this context, schemes based on Model Predictive Control (MPC) are particularly suitable due to their capability to deal with constraints explicitly. In this paper, we first discuss relevant properties for the design of predictive controllers for thermal systems. Starting from the Partial Differential Equation (PDE) describing heat diffusion in a solid, we prove meaningful feasibility properties that can be leveraged for constraint reduction. We then present a procedure to derive approximated but effective modular thermal models intended to build an efficient distributed MPC. Finally, a two-layer control solution is proposed to maximize performance while preserving feasibility despite model approximations. The effectiveness of this approach is validated through extensive and realistic numerical simulations.

We introduce a new version of the FONLL code, now capable of calculating differential distributions for top quark production with next-to-leading-log resummation of log(p_t/m) terms. Numerical results for LHC and FCC kinematics are presented. In the transverse momentum region presently explored by ATLAS and CMS, no significant difference with respect to available fixed order predictions is predicted by FONLL. The large transverse momentum resummation of FONLL may instead become relevant if top is ever measured at transverse momentum scales of several TeV.

This corrects the article DOI: 10.1103/PhysRevLett.115.082002.

This report summarises the properties of Standard Model processes at the 100 TeV pp collider. We document the production rates and typical distributions for a number of benchmark Standard Model processes, and discuss new dynamical phenomena arising at the highest energies available at this collider. We discuss the intrinsic physics interest in the measurement of these Standard Model processes, as well as their role as backgrounds for New Physics searches.

Today and future many-core systems are facing the utilization wall and dark silicon problems, for which not all the processing engines can be powered at the same time as this will lead to a power consumption higher than the Total Design Power (TDP) budget. Recently, computational sprinting approaches addressed the problem by exploiting the intrinsic thermal capacitance of the chip and the properties of common applications, which require intense, but temporary, use of resources. The thermal capacitance, possibly augmented with phase change materials, enables the temporary activation of all the resources simultaneously, although they largely exceed the steady-state thermal design power. In this article, we present an innovative and low-overhead hierarchical model-predictive controller for managing thermally safe sprinting with predictable resprinting rate, which ensures the correct execution of mixed-criticality tasks. Well-targeted simulations, also based on real workload benchmarks, show the applicability and the effectiveness of our solution.

The use of charged pileup tracks in a jet to predict the neutral pileup component in that same jet could potentially lead to improved pileup removal techniques, provided there is a strong local correlation between charged and neutral pileup. In a Monte Carlo simulation we find that the correlation is however moderate, a feature that we attribute to characteristics of the underlying nonperturbative dynamics. Consequently, pure ``neutral-proportional-to-charge'' (NpC) pileup mitigation approaches do not outperform existing, area-based pileup removal methods. This finding contrasts with the arguments made in favor of a new method, ``jet cleansing,'' in part based on the NpC approach. We identify the critical differences between the performances of linear cleansing and trimmed NpC as being due to the former's rejection of subjets that have no charged tracks from the leading vertex, a procedure that we name ``zeroing.'' Zeroing, an extreme version of the ``charged-track trimming'' proposed by ATLAS, can be combined with a range of pileup mitigation methods, and appears to have both benefits and drawbacks. We show how the latter can be straightforwardly alleviated. We also discuss the limited potential for improvement that can be obtained by linear combinations of the NpC and area-subtraction methods.

We calculate the fully differential next-to-next-to-leading-order (NNLO) corrections to vector-boson fusion (VBF) Higgs boson production at proton colliders, in the limit in which there is no cross talk between the hadronic systems associated with the two protons. We achieve this using a new "projection-to-Born" method that combines an inclusive NNLO calculation in the structure-function approach and a suitably factorized next-to-leading-order VBF Higgs plus three-jet calculation, using appropriate Higgs plus two-parton counterevents. An earlier calculation of the fully inclusive cross section had found small NNLO corrections, at the 1% level. In contrast, the cross section after typical experimental VBF cuts receives NNLO contributions of about (5-6)%, while differential distributions show corrections of up to (10-12)% for some standard observables. The corrections are often outside the next-to-leading-order scale-uncertainty band.

We review the history of jets in high energy physics, and describe in more detail the developments of the past ten years, discussing new algorithms for jet finding and their main characteristics, and summarising the status of perturbative calculations for jet cross sections in hadroproduction. We also describe the emergence of jet grooming and tagging techniques and their application to boosted jets analyses.

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index.

Nowadays automated manufacturing systems are designed as the complex interconnection of components belonging to different engineering domains. Actually high performances are required in order to satisfy market needs and standards. In this framework the validation via simulation plays a crucial role as it allows to verify the system during the design phase. Software-in-the-loop architectures represent a good practice to take into account also technological side-effects that represent a classical cause of long time-to-market or, in the worst case, to project failure. In this paper we present a mathematical simulator to be used within a software-in-the-loop prototyping system.

Eurora (EURopean many integrated cORe Architecture) is today the most energy efficient supercomputer in the world. Ranked 1st in the Green500 in July 2013, is a prototype built from Eurotech and Cineca toward next-generation Tier-0 systems in the PRACE 2IP EU project. Eurora's outstanding energy-efficiency is achieved by adopting a direct liquid cooling solution and a heterogeneous architecture with best-in-class general purpose HW components (Intel Xeon E5, Intel Xeon Phi and NVIDIA Kepler K20). In this paper we present a novel, low-overhead monitoring infrastructure capable to track in detail and in real-time the thermal and power characteristics of Eurora's components with fine-grained resolution. Our experiments give insights on Eurora's thermal/power trade-offs and highlight opportunities for run-time power/thermal management and optimization.

MultiProcessor Systems-on-Chip (MPSoC) are the core of nowadays and next generation computing platforms. Their relevance in the global market continuously increase, occupying an important role both in everydaylife products (e.g. smartphones, tablets, laptops, cars) and in strategical market sectors as aviation, defense, robotics, medicine. Despite of the incredible performance improvements in the recent years processors manufacturers have had to deal with issues, commonly called “Walls”, that have hindered the processors development. After the famous “Power Wall”, that limited the maximum frequency of a single core and marked the birth of the modern multiprocessors system-on-chip, the “Thermal Wall” and the “Utilization Wall” are the actual key limiter for performance improvements. The former concerns the damaging effects of the high temperature on the chip caused by the large power densities dissipation, whereas the second refers to the impossibility of fully exploiting the computing power of the processor due to the limitations on power and temperature budgets. In this thesis we faced these challenges by developing efficient and reliable solutions able to maximize performance while limiting the maximum temperature below a fixed critical threshold and saving energy. This has been possible by exploiting the Model Predictive Controller (MPC) paradigm that solves an optimization problem subject to constraints in order to find the optimal control decisions for the future interval. A fully-distributedMPC-based thermal controller with a far lower complexity respect to a centralized one has been developed. The control feasibility and interesting properties for the simplification of the control design has been proved by studying a partial differential equation thermal model. Finally, the controller has been efficiently included in more complex control schemes able to minimize energy consumption and deal with mixed-criticalities tasks

This report of the BOOST2012 workshop presents the results of four working groups that studied key aspects of jet substructure. We discuss the potential of the description of jet substructure in first-principle QCD calculations and study the accuracy of state-of-the-art Monte Carlo tools. Experimental limitations of the ability to resolve substructure are evaluated, with a focus on the impact of additional proton proton collisions on jet substructure performance in future LHC operating scenarios. A final section summarizes the lessons learnt during the deployment of substructure analyses in searches for new physics in the production of boosted top quarks.

Jets in high energy hadronic collisions often contain the fingerprints of the particles that produced them. Those fingerprints, and thus the nature of the particles that produced the jets, can be read off with the help of quantities known as jet shapes. Jet shapes are, however, severely affected by pileup, the accumulation in the detector of the residues of the many simultaneous collisions taking place in the Large Hadron Collider (LHC). We introduce a method to correct for pileup effects in jet shapes. Relative to earlier, limited approaches, the key advance resides in its full generality, achieved through a numerical determination, for each jet, of a given shape's susceptibility to pileup. The method rescues the possibility of using jet shapes in the high pileup environment of current and future LHC running, as we show with examples of quark-gluon discrimination and top tagging.

The nature of a jet's fragmentation in heavy-ion collisions has the potential to cast light on the mechanism of jet quenching. However the presence of the huge underlying event complicates the reconstruction of the jet fragmentation function as a function of the momentum fraction z of hadrons in the jet. Here we propose the use of moments of the fragmentation function. These quantities appear to be as sensitive to quenching modifications as the fragmentation function directly in z. We show that they are amenable to background subtraction using the same jet-area based techniques proposed in the past for jet p_t's. Furthermore, complications due to correlations between background-fluctuation contributions to the jet's p_t and to its particle content are easily corrected for.

As result of technology scaling, single-chip multicore power density increases and its spatial and temporal workload variation leads to temperature hot-spots, which may cause nonuniform ageing and accelerated chip failure. These critical issues can be tackled by closed-loop thermal and reliability management policies. Model predictive controllers (MPC) outperform classic feedback controllers since they are capable of minimizing performance loss while enforcing safe working temperature. Unfortunately, MPC controllers rely on a priori knowledge of thermal models and their complexity exponentially grows with the number of controlled cores. In this paper, we present a scalable, fully distributed, energy-aware thermal management solution for single-chip multicore platforms. The model-predictive controller complexity is drastically reduced by splitting it in a set of simpler interacting controllers, each one allocated to a core in the system. Locally, each node selects the optimal frequency to meet temperature constraints while minimizing the performance penalty and system energy. Comparable performance with state-of-the-art MPC controllers is achieved by letting controllers exchange a limited amount of information at runtime on a neighborhood basis. In addition, we address model uncertainty by supporting learning of the thermal model with a novel distributed self-calibration approach that matches well the controller architecture.

The 2011 Les Houches workshop was the first to confront LHC data. In the two years since the previous workshop there have been significant advances in both soft and hard QCD, particularly in the areas of multi-leg NLO calculations, the inclusion of those NLO calculations into parton shower Monte Carlos, and the tuning of the non-perturbative parameters of those Monte Carlos. These proceedings describe the theoretical advances that have taken place, the impact of the early LHC data, and the areas for future development.