arXiv subjects

Paolo Romano

Publications and source records attributed to Paolo Romano.

At least 37 records · Page 2Linked to original sources

arXiv2024

Photospheric signatures of CME onset

Coronal mass ejections (CMEs) are solar eruptions that involve large-scale changes to the magnetic topology of an active region. There exists a range of models for CME onset which are based on twisted or sheared magnetic field above a polarity inversion line (PIL). We present observational evidence that topological changes at PILs, in the photosphere, form a key part of CME onset, as implied by many models. In particular, we study the onset of 30 CMEs and investigate topological changes in the photosphere by calculating the magnetic winding flux, using the \texttt{ARTop} code. By matching the times and locations of winding signatures with CME observations produced by the \texttt{ALMANAC} code, we confirm that these signatures are indeed associated with CMEs. Therefore, as well as presenting evidence that changes in magnetic topology at the photosphere are a common signature of CME onset, our approach also allows for the finding of the source location of a CME within an active region.

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arXiv2024

Hyper-parameter Tuning for Adversarially Robust Models

This work focuses on the problem of hyper-parameter tuning (HPT) for robust (i.e., adversarially trained) models, shedding light on the new challenges and opportunities arising during the HPT process for robust models. To this end, we conduct an extensive experimental study based on 3 popular deep models, in which we explore exhaustively 9 (discretized) HPs, 2 fidelity dimensions, and 2 attack bounds, for a total of 19208 configurations (corresponding to 50 thousand GPU hours). Through this study, we show that the complexity of the HPT problem is further exacerbated in adversarial settings due to the need to independently tune the HPs used during standard and adversarial training: succeeding in doing so (i.e., adopting different HP settings in both phases) can lead to a reduction of up to 80% and 43% of the error for clean and adversarial inputs, respectively. On the other hand, we also identify new opportunities to reduce the cost of HPT for robust models. Specifically, we propose to leverage cheap adversarial training methods to obtain inexpensive, yet highly correlated, estimations of the quality achievable using state-of-the-art methods. We show that, by exploiting this novel idea in conjunction with a recent multi-fidelity optimizer (taKG), the efficiency of the HPT process can be enhanced by up to 2.1x.

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arXiv2024

PIM-STM: Software Transactional Memory for Processing-In-Memory Systems

Processing-In-Memory (PIM) is a novel approach that augments existing DRAM memory chips with lightweight logic. By allowing to offload computations to the PIM system, this architecture allows for circumventing the data-bottleneck problem that affects many modern workloads. This work tackles the problem of how to build efficient software implementations of the Transactional Memory (TM) abstraction by introducing PIM-STM, a library that provides a range of diverse TM implementations for UPMEM, the first commercial PIM system. Via an extensive study we assess the efficiency of alternative choices in the design space of TM algorithms on this emerging architecture. We further quantify the impact of using different memory tiers of the UPMEM system (having different trade-offs for what concerns latency vs capacity) to store the metadata used by different TM implementations. Finally, we assess the gains achievable in terms of performance and memory efficiency when using PIM-STM to accelerate TM applications originally conceived for conventional CPU-based systems.

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arXiv2023

Analysis of full-disc H alpha observations: Carrington maps and filament properties in 1909-2022

Full disc observations of the Sun in the H$α$ line provide information about the solar chromosphere and in particular about the filaments, which are dark and elongated features that lie along magnetic field polarity inversion lines. This makes them important for studies of solar magnetism. Since full disc H$α$ observations have been performed at various sites since 1800s, with regular photographic data having started in the beginning of the 20th century, they are an invaluable source of information on past solar magnetism. In this work we aimed at deriving accurate information about filaments from historical and modern full disc H$α$ observations. We have consistently processed observations from 15 H$α$ archives spanning 1909-2022. Our data processing includes photometric calibration of the data stored on photographic plates. We have constructed also Carrington maps from the calibrated H$α$ images. We find that filament areas are affected by the bandwidth of the observation. Thus, cross-calibration of the filament areas derived from different archives is needed. We have produced a composite of filament areas from individual archives by scaling all of them to the Meudon series. Our composite butterfly diagram shows very distinctly the common features of filament evolution, that is the poleward migration as well as a decrease in the mean latitude of filaments as the cycle progresses. We also find that during activity maxima, filaments on average cover about 1% of the solar surface. We see only a weak change in the amplitude of cycles in filament areas, in contrast to sunspot and plage areas. Analysis of H$α$ data for archives with contemporaneous Ca II K observations allowed us to identify and verify archive inconsistencies, which will also have implications for reconstructions of past solar magnetism and irradiance from Ca II K data.

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arXiv2023

Observations of the chromospheric Evershed flow of sunspot penumbra

The sunspot penumbra is usually observed in the photosphere and it is of particular interest for its magneto-convection which seems to transport the heat from the top of the convection zone into the solar atmosphere. It is well known that the penumbra magnetic field extends in the upper layers of the solar atmosphere forming the so called super-penumbra. Thanks to the application of the Self Organizing Map technique to a spectral dataset containing monochromatic images acquired along the Ca II 854.2 nm and H$α$ 656.28 nm lines, we were able to segment the penumbra and to measure the plasma velocity along the chromospheric portions of penumbral filaments. We found that the head, body and tail of penumbral filaments show vertical flows compatible with the persistence of the Evershed flow. Instead, the inverse Evershed flow has been observed only in the outer portion of the super-penumbra. We found that two opposite Evershed regimes work next to each other, without overlapping and both contribute to the downflow around sunspots. These results confirm the uncombed model of the sunspot penumbra and provide some hints that the downflow around sunspots may be ascribed to the magnetic field dragging the plasma down.

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arXiv2023

Adversarial training for tabular data with attack propagation

Adversarial attacks are a major concern in security-centered applications, where malicious actors continuously try to mislead Machine Learning (ML) models into wrongly classifying fraudulent activity as legitimate, whereas system maintainers try to stop them. Adversarially training ML models that are robust against such attacks can prevent business losses and reduce the work load of system maintainers. In such applications data is often tabular and the space available for attackers to manipulate undergoes complex feature engineering transformations, to provide useful signals for model training, to a space attackers cannot access. Thus, we propose a new form of adversarial training where attacks are propagated between the two spaces in the training loop. We then test this method empirically on a real world dataset in the domain of credit card fraud detection. We show that our method can prevent about 30% performance drops under moderate attacks and is essential under very aggressive attacks, with a trade-off loss in performance under no attacks smaller than 7%.

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arXiv2023

Coronal Heating Rate in the Slow Solar Wind

This Letter reports the first observational estimate of the heating rate in the slowly expanding solar corona. The analysis exploits the simultaneous remote and local observations of the same coronal plasma volume with the Solar Orbiter/Metis and the Parker Solar Probe instruments, respectively, and relies on the basic solar wind magnetohydrodynamic equations. As expected, energy losses are a minor fraction of the solar wind energy flux, since most of the energy dissipation that feeds the heating and acceleration of the coronal flow occurs much closer to the Sun than the heights probed in the present study, which range from 6.3 to 13.3 solar radii. The energy deposited to the supersonic wind is then used to explain the observed slight residual wind acceleration and to maintain the plasma in a non-adiabatic state. As derived in the Wentzel-Kramers-Brillouin limit, the present energy transfer rate estimates provide a lower limit, which can be very useful in refining the turbulence-based modeling of coronal heating and subsequent solar wind acceleration.

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arXiv2023

Bandwidth-Aware Page Placement in NUMA

Page placement is a critical problem for memoryintensive applications running on a shared-memory multiprocessor with a non-uniform memory access (NUMA) architecture. State-of-the-art page placement mechanisms interleave pages evenly across NUMA nodes. However, this approach fails to maximize memory throughput in modern NUMA systems, characterised by asymmetric bandwidths and latencies, and sensitive to memory contention and interconnect congestion phenomena. We propose BWAP, a novel page placement mechanism based on asymmetric weighted page interleaving. BWAP combines an analytical performance model of the target NUMA system with on-line iterative tuning of page distribution for a given memory-intensive application. Our experimental evaluation with representative memory-intensive workloads shows that BWAP performs up to 66% better than state-of-the-art techniques. These gains are particularly relevant when multiple co-located applications run in disjoint partitions of a large NUMA machine or when applications do not scale up to the total number of cores.

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arXiv2022

HyperJump: Accelerating HyperBand via Risk Modelling

In the literature on hyper-parameter tuning, a number of recent solutions rely on low-fidelity observations (e.g., training with sub-sampled datasets) in order to efficiently identify promising configurations to be then tested via high-fidelity observations (e.g., using the full dataset). Among these, HyperBand is arguably one of the most popular solutions, due to its efficiency and theoretically provable robustness. In this work, we introduce HyperJump, a new approach that builds on HyperBand's robust search strategy and complements it with novel model-based risk analysis techniques that accelerate the search by skipping the evaluation of low risk configurations, i.e., configurations that are likely to be eventually discarded by HyperBand. We evaluate HyperJump on a suite of hyper-parameter optimization problems and show that it provides over one-order of magnitude speed-ups, both in sequential and parallel deployments, on a variety of deep-learning, kernel-based learning, and neural architectural search problems when compared to HyperBand and to several state-of-the-art optimizers.

cs.LG↗

arXiv2022

IBIS-A: The IBIS data Archive. High resolution observations of the solar photosphere and chromosphere with contextual data

The IBIS data Archive (IBIS-A) stores data acquired with the Interferometric BIdimensional Spectropolarimeter (IBIS), which was operated at the Dunn Solar Telescope of the US National Solar Observatory from 2003 to 2019. The instrument provided series of high-resolution narrowband spectropolarimetric imaging observations of the photosphere and chromosphere in the range 5800$-$8600 Å~ and co-temporal broadband observations in the same spectral range and with the same field of view of the polarimetric data. We present the data currently stored in IBIS-A, as well as the interface utilized to explore such data and facilitate its scientific exploitation. To this purpose we also describe the use of IBIS-A data in recent and undergoing studies relevant to solar physics and space weather research. IBIS-A includes raw and calibrated observations, as well as science-ready data. The latter comprise maps of the circular, linear, and net circular polarization, and of the magnetic and velocity fields derived for a significant fraction of the series available in the archive. IBIS-A furthermore contains links to observations complementary to the IBIS data, such as co-temporal high-resolution observations of the solar atmosphere available from the instruments onboard the Hinode and IRIS satellites, and full-disc multiband images from INAF solar telescopes. IBIS-A currently consists of 30 TB of data taken with IBIS during 28 observing campaigns performed in 2008 and from 2012 to 2019 on 159 days. Metadata and movies of each calibrated and science-ready series are also available to help users evaluating observing conditions. IBIS-A represents a unique resource for investigating the plasma processes in the solar atmosphere and the solar origin of space weather events.

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arXiv2021

On the evolution of a sub-C class flare: a showcase for the capabilities of the revamped Catania Solar Telescope

Solar flares are occasionally responsible for severe Space Weather events, which can affect space-borne and ground-based infrastructures, endangering anthropic technological activities and even human health and safety. Thus, an essential activity in the framework of Space Weather monitoring is devoted to the observation of the activity level of the Sun. In this context, the acquisition system of the Catania Solar Telescope has been recently upgraded in order to improve its contribution to the European Space Agency (ESA) - Space Weather Service Network through the ESA Portal, which represents the main asset for Space Weather in Europe. Here, we describe the hardware and software upgrades of the Catania Solar Telescope and the main data products provided by this facility, which include full-disc images of the photosphere and chromosphere, together with a detailed characterization of the sunspot groups. As a showcase of the observational capabilities of the revamped Catania Solar Telescope, we report the analysis of a B5.4 class flare occurred on 2020 December 7, simultaneously observed by the IRIS and SDO satellites.

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arXiv2021

Exploring the Solar Wind from its Source on the Corona into the Inner Heliosphere during the First Solar Orbiter - Parker Solar Probe Quadrature

This Letter addresses the first Solar Orbiter (SO) -- Parker Solar Probe (PSP) quadrature, occurring on January 18, 2021, to investigate the evolution of solar wind from the extended corona to the inner heliosphere. Assuming ballistic propagation, the same plasma volume observed remotely in corona at altitudes between 3.5 and 6.3 solar radii above the solar limb with the Metis coronagraph on SO can be tracked to PSP, orbiting at 0.1 au, thus allowing the local properties of the solar wind to be linked to the coronal source region from where it originated. Thanks to the close approach of PSP to the Sun and the simultaneous Metis observation of the solar corona, the flow-aligned magnetic field and the bulk kinetic energy flux density can be empirically inferred along the coronal current sheet with an unprecedented accuracy, allowing in particular estimation of the Alfvén radius at 8.7 solar radii during the time of this event. This is thus the very first study of the same solar wind plasma as it expands from the sub-Alfvénic solar corona to just above the Alfvén surface.

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arXiv2021

Comparative case study of two methods to assess the eruptive potential of selected active regions

Solar eruptive events, like flares and coronal mass ejections, are characterized by the rapid release of energy that can give rise to emission of radiation across the entire electromagnetic spectrum and to an abrupt significant increase in the kinetic energy of particles. These energetic phenomena can have important effects on the Space Weather conditions and therefore it is necessary to understand their origin, in particular, what is the eruptive potential of an active region (AR). In these case studies, we compare two distinct methods that were used in previous works to investigate the variations of some characteristic physical parameters during the pre-flare states of flaring ARs. These methods consider: i) the magnetic flux evolution and the magnetic helicity accumulation, and ii) the fractal and multi-fractal properties of flux concentrations in ARs. Our comparative analysis is based on time series of photospheric data obtained by the Solar Dynamics Observatory between March 2011 and June 2013. We selected two distinct samples of ARs: one is distinguished by the occurrence of more energetic M- and X-class flare events, that may have a rapid effect on not just the near-Earth space, but also on the terrestrial environment; the second is characterized by no-flares or having just few C- and B-class flares. We found that the two tested methods complement each other in their ability to assess the eruptive potentials of ARs and could be employed to identify ARs prone to flaring activity. Based on the presented case study, we suggest that using a combination of different methods may aid to identify more reliably the eruptive potentials of ARs and help to better understand the pre-flare states.

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arXiv2021

Direct evidence: twisted flux tube emergence creates solar active regions

The magnetic nature of the formation of solar active regions lies at the heart of understanding solar activity and, in particular, solar eruptions. A widespread model, used in many theoretical studies, simulations and the interpretation of observations is that the basic structure of an active region is created by the emergence of a large tube of pre-twisted magnetic field. Despite plausible reasons and the availability of various proxies suggesting the veracity of this model, there has not yet been any direct observational evidence of the emergence of large twisted magnetic flux tubes. Thus, the fundamental question, "are active regions formed by large twisted flux tubes?" has remained open. In this work, we answer this question in the affirmative and provide direct evidence to support this. We do this by investigating a robust topological quantity, called magnetic winding, in solar observations. This quantity, combined with other signatures that are currently available, provides the first direct evidence that large twisted flux tubes do emerge to create active regions.

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arXiv2020

TrimTuner: Efficient Optimization of Machine Learning Jobs in the Cloud via Sub-Sampling

This work introduces TrimTuner, the first system for optimizing machine learning jobs in the cloud to exploit sub-sampling techniques to reduce the cost of the optimization process while keeping into account user-specified constraints. TrimTuner jointly optimizes the cloud and application-specific parameters and, unlike state of the art works for cloud optimization, eschews the need to train the model with the full training set every time a new configuration is sampled. Indeed, by leveraging sub-sampling techniques and data-sets that are up to 60x smaller than the original one, we show that TrimTuner can reduce the cost of the optimization process by up to 50x. Further, TrimTuner speeds-up the recommendation process by 65x with respect to state of the art techniques for hyper-parameter optimization that use sub-sampling techniques. The reasons for this improvement are twofold: i) a novel domain specific heuristic that reduces the number of configurations for which the acquisition function has to be evaluated; ii) the adoption of an ensemble of decision trees that enables boosting the speed of the recommendation process by one additional order of magnitude.

cs.LG↗

arXiv2020

Stretching the capacity of Hardware Transactional Memory in IBM POWER architectures

The hardware transactional memory (HTM) implementations in commercially available processors are significantly hindered by their tight capacity constraints. In practice, this renders current HTMs unsuitable to many real-world workloads of in-memory databases. This paper proposes SI-HTM, which stretches the capacity bounds of the underlying HTM, thus opening HTM to a much broader class of applications. SI-HTM leverages the HTM implementation of the IBM POWER architecture with a software layer to offer a single-version implementation of Snapshot Isolation. When compared to HTM- and software-based concurrency control alternatives, SI-HTM exhibits improved scalability, achieving speedups of up to 300% relatively to HTM on in-memory database benchmarks.

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arXiv2020

Lynceus: Cost-efficient Tuning and Provisioning of Data Analytic Jobs

Modern data analytic and machine learning jobs find in the cloud a natural deployment platform to satisfy their notoriously large resource requirements. Yet, to achieve cost efficiency, it is crucial to identify a deployment configuration that satisfies user-defined QoS constraints (e.g., on execution time), while avoiding unnecessary over-provisioning. This paper introduces Lynceus, a new approach for the optimization of cloud based data analytic jobs that improves overstate-of-the-art approaches by enabling significant cost savings both in terms of the final recommended configuration and of the optimization process used to recommend configurations. Unlike existing solutions, Lynceus optimizes in a joint fashion both the cloud-related and the application-level parameters. This allows for a reduction of the cost of recommended configurations by up to 3.7x at the 90-th percentile with respect to existing approaches, which treat the optimization of cloud-related and application-level parameters as two independent problems. Further, Lynceus reduces the cost of the optimization process (i.e., the cloud cost incurred for testing configurations) by up to 11x. Such an improvement is achieved thanks to two mechanisms: i) a timeout approach which allows to abort the exploration of configurations that are deemed suboptimal, while still extracting useful information to guide future explorations and to improve its predictive model - differently from recent works, which either incur the full cost for testing suboptimal configurations or are unable to extract any knowledge from aborted runs; ii) a long-sighted and budget-aware technique that determines which configurations to test by predicting the long-term impact of each exploration - unlike state-of-the-art approaches for the optimization of cloud jobs, which adopt greedy optimization methods.

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arXiv2019

HeTM: Transactional Memory for Heterogeneous Systems

Modern heterogeneous computing architectures, which couple multi-core CPUs with discrete many-core GPUs (or other specialized hardware accelerators), enable unprecedented peak performance and energy efficiency levels. Unfortunately, though, developing applications that can take full advantage of the potential of heterogeneous systems is a notoriously hard task. This work takes a step towards reducing the complexity of programming heterogeneous systems by introducing the abstraction of Heterogeneous Transactional Memory (HeTM). HeTM provides programmers with the illusion of a single memory region, shared among the CPUs and the (discrete) GPU(s) of a heterogeneous system, with support for atomic transactions. Besides introducing the abstract semantics and programming model of HeTM, we present the design and evaluation of a concrete implementation of the proposed abstraction, which we named Speculative HeTM (SHeTM). SHeTM makes use of a novel design that leverages on speculative techniques and aims at hiding the inherently large communication latency between CPUs and discrete GPUs and at minimizing inter-device synchronization overhead. SHeTM is based on a modular and extensible design that allows for easily integrating alternative TM implementations on the CPU's and GPU's sides, which allows the flexibility to adopt, on either side, the TM implementation (e.g., in hardware or software) that best fits the applications' workload and the architectural characteristics of the processing unit. We demonstrate the efficiency of the SHeTM via an extensive quantitative study based both on synthetic benchmarks and on a porting of a popular object caching system.

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