2,413 research outputs found

    TANDEM: taming failures in next-generation datacenters with emerging memory

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    The explosive growth of online services, leading to unforeseen scales, has made modern datacenters highly prone to failures. Taming these failures hinges on fast and correct recovery, minimizing service interruptions. Applications, owing to recovery, entail additional measures to maintain a recoverable state of data and computation logic during their failure-free execution. However, these precautionary measures have severe implications on performance, correctness, and programmability, making recovery incredibly challenging to realize in practice. Emerging memory, particularly non-volatile memory (NVM) and disaggregated memory (DM), offers a promising opportunity to achieve fast recovery with maximum performance. However, incorporating these technologies into datacenter architecture presents significant challenges; Their distinct architectural attributes, differing significantly from traditional memory devices, introduce new semantic challenges for implementing recovery, complicating correctness and programmability. Can emerging memory enable fast, performant, and correct recovery in the datacenter? This thesis aims to answer this question while addressing the associated challenges. When architecting datacenters with emerging memory, system architects face four key challenges: (1) how to guarantee correct semantics; (2) how to efficiently enforce correctness with optimal performance; (3) how to validate end-to-end correctness including recovery; and (4) how to preserve programmer productivity (Programmability). This thesis aims to address these challenges through the following approaches: (a) defining precise consistency models that formally specify correct end-to-end semantics in the presence of failures (consistency models also play a crucial role in programmability); (b) developing new low-level mechanisms to efficiently enforce the prescribed models given the capabilities of emerging memory; and (c) creating robust testing frameworks to validate end-to-end correctness and recovery. We start our exploration with non-volatile memory (NVM), which offers fast persistence capabilities directly accessible through the processor’s load-store (memory) interface. Notably, these capabilities can be leveraged to enable fast recovery for Log-Free Data Structures (LFDs) while maximizing performance. However, due to the complexity of modern cache hierarchies, data hardly persist in any specific order, jeop- ardizing recovery and correctness. Therefore, recovery needs primitives that explicitly control the order of updates to NVM (known as persistency models). We outline the precise specification of a novel persistency model – Release Persistency (RP) – that provides a consistency guarantee for LFDs on what remains in non-volatile memory upon failure. To efficiently enforce RP, we propose a novel microarchitecture mechanism, lazy release persistence (LRP). Using standard LFDs benchmarks, we show that LRP achieves fast recovery while incurring minimal overhead on performance. We continue our discussion with memory disaggregation which decouples memory from traditional monolithic servers, offering a promising pathway for achieving very high availability in replicated in-memory data stores. Achieving such availability hinges on transaction protocols that can efficiently handle recovery in this setting, where compute and memory are independent. However, there is a challenge: disaggregated memory (DM) fails to work with RPC-style protocols, mandating one-sided transaction protocols. Exacerbating the problem, one-sided transactions expose critical low-level ordering to architects, posing a threat to correctness. We present a highly available transaction protocol, Pandora, that is specifically designed to achieve fast recovery in disaggregated key-value stores (DKVSes). Pandora is the first one-sided transactional protocol that ensures correct, non-blocking, and fast recovery in DKVS. Our experimental implementation artifacts demonstrate that Pandora achieves fast recovery and high availability while causing minimal disruption to services. Finally, we introduce a novel target litmus-testing framework – DART – to validate the end-to-end correctness of transactional protocols with recovery. Using DART’s target testing capabilities, we have found several critical bugs in Pandora, highlighting the need for robust end-to-end testing methods in the design loop to iteratively fix correctness bugs. Crucially, DART is lightweight and black-box, thereby eliminating any intervention from the programmers

    Classical and quantum algorithms for scaling problems

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    This thesis is concerned with scaling problems, which have a plethora of connections to different areas of mathematics, physics and computer science. Although many structural aspects of these problems are understood by now, we only know how to solve them efficiently in special cases.We give new algorithms for non-commutative scaling problems with complexity guarantees that match the prior state of the art. To this end, we extend the well-known (self-concordance based) interior-point method (IPM) framework to Riemannian manifolds, motivated by its success in the commutative setting. Moreover, the IPM framework does not obviously suffer from the same obstructions to efficiency as previous methods. It also yields the first high-precision algorithms for other natural geometric problems in non-positive curvature.For the (commutative) problems of matrix scaling and balancing, we show that quantum algorithms can outperform the (already very efficient) state-of-the-art classical algorithms. Their time complexity can be sublinear in the input size; in certain parameter regimes they are also optimal, whereas in others we show no quantum speedup over the classical methods is possible. Along the way, we provide improvements over the long-standing state of the art for searching for all marked elements in a list, and computing the sum of a list of numbers.We identify a new application in the context of tensor networks for quantum many-body physics. We define a computable canonical form for uniform projected entangled pair states (as the solution to a scaling problem), circumventing previously known undecidability results. We also show, by characterizing the invariant polynomials, that the canonical form is determined by evaluating the tensor network contractions on networks of bounded size

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    The anisotropic grain size effect on the mechanical response of polycrystals: The role of columnar grain morphology in additively manufactured metals

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    Additively manufactured (AM) metals exhibit highly complex microstructures, particularly with respect to grain morphology which typically features heterogeneous grain size distribution, anomalous and anisotropic grain shapes, and the so-called columnar grains. In general, the conventional morphological descriptors are not suitable to represent complex and anisotropic grain morphology of AM microstructures. The principal aspect of microstructural grain morphology is the state of grain boundary spacing or grain size whose effect on the mechanical response is known to be crucial. In this paper, we formally introduce the notions of axial grain size and grain size anisotropy as robust morphological descriptors which can concisely represent highly complex grain morphologies. We instantiated a discrete sample of polycrystalline aggregate as a representative volume element (RVE) which has random crystallographic orientation and misorientation distributions. However, the instantiated RVE incorporates the typical morphological features of AM microstructures including distinctive grain size heterogeneity and anisotropic grain size owing to its pronounced columnar grain morphology. We ensured that any anisotropy arising in the macroscopic mechanical response of the instantiated sample is mainly associated with its underlying anisotropic grain size. The RVE was then used for meso-scale full-field crystal plasticity simulations corresponding to uniaxial tensile deformation along different axes via a spectral solver and a physics-based crystal plasticity constitutive model. Through the numerical analyses, we were able to isolate the contribution of anisotropic grain size to the anisotropy in the mechanical response of polycrystalline aggregates, particularly those with the characteristic complex grain morphology of AM metals. Such a contribution can be described by an inverse square relation

    Game Theory in Distributed Systems Security: Foundations, Challenges, and Future Directions

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    Many of our critical infrastructure systems and personal computing systems have a distributed computing systems structure. The incentives to attack them have been growing rapidly as has their attack surface due to increasing levels of connectedness. Therefore, we feel it is time to bring in rigorous reasoning to secure such systems. The distributed system security and the game theory technical communities can come together to effectively address this challenge. In this article, we lay out the foundations from each that we can build upon to achieve our goals. Next, we describe a set of research challenges for the community, organized into three categories -- analytical, systems, and integration challenges, each with "short term" time horizon (2-3 years) and "long term" (5-10 years) items. This article was conceived of through a community discussion at the 2022 NSF SaTC PI meeting.Comment: 11 pages in IEEE Computer Society magazine format, including references and author bios. There is 1 figur

    Investigating the impact of space weather on the polar atmosphere using rigorous statistical methods

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    I de senere Ă„r har det vĂŠrt en Ăžkning i observasjonsbaserte, re-analytiske og modellbaserte studier som viser korrelasjoner mellom dag-til-dag og Ă„r-til-Ă„r solaktivitet og klima-/vĂŠr-mĂžnstre. Det overordnede mĂ„let med avhandlingen er Ă„ undersĂžke to solklima-mekanismer, den Kjemisk-Dynamiske koblingen og Mansurov-effekten. Den Kjemisk-Dynamiske koblingen er knyttet til ioniseringen av den Ăžvre atmosfĂŠren (ÂĄ50 km) som skjer ved energisk partikkelnedbĂžr (EPP). Dette resulterer i produksjon av nitrogen- og hydrogenoksider (NOx og HOx). Disse molekylene bryter effektivt ned ozon, og kan derfor endre strĂ„lingsbalansen i atmosfĂŠren, noe som igjen potensielt kan fĂžre til en kaskadeeffekt av dynamisk induserte atmosfĂŠriske vĂŠrendringer i polaratmosfĂŠren. Mansurov-effekten er knyttet til det interplanetariske magnetfeltet (IMF) og dets evne til Ă„ modulere den globale elektriske kretsen (GEC). Dette antas Ă„ videre pĂ„virke den polare troposfĂŠren gjennom Ă„ endre de fysiske prosessene bak dannelse og vekst av skyer. Effekten antas Ă„ vĂŠre nesten umiddelbar, noe som gir en fysisk forbindelse mellom verdensrommet og den nedre del av Jordens atmosfĂŠre. Begge mekanismene har blitt studert ved hjelp av sofistikerte statistiske analysemetoder. For den Kjemisk-Dynamiske koblingen, bruker vi SOCOL3-MPIOM-modellen for Ă„ sammenligne temperaturforskjeller i den nordlige atmosfĂŠren i modellkjĂžringen med og uten EPP. Analysen bygger pĂ„ en nylig studie som viser at EPP hovedsakelig pĂ„virker den nordlige atmosfĂŠriske temperaturen rett fĂžr og under forstyrrede forhold i den stratosfĂŠriske polare jetstrĂžm. Vi finner svĂŠrt signifikante temperaturresponser rett fĂžr hendelser karakterisert som smĂ„ stratosfĂŠriske oppvarminger, forhold assosiert med en svekket polar jetstrĂžm og Ăžkt bĂžlgeaktivitet. De stĂžrste temperaturforskjellene er synlig i februar, men bare for den siste halvdel (1955–2008) av simuleringsperioden (1900–2008). Funnene antyder at den Kjemisk-Dynamiske koblingen kan spille en avgjĂžrende rolle i stratosfĂŠriske forhold om vinteren og bekrefter eksistensen av den Kjemisk-Dynamiske koblingen i modellen. Ved Ă„ bruke data fra OMNIweb og ERA5 re-analyse over tidsperioden 1968–2020, undersĂžkes forbindelsen mellom IMF By og polart atmosfĂŠrisk trykk pĂ„ havnivĂ„. I motsetning til tidligere publiserte studier om Mansurov-effekten, finner vi ingen signifikant respons etter Ă„ ha tatt hensyn til autokorrelasjon og kontrollert for falsk deteksjonsandel (false discovery rate). Tidligere studier har ogsĂ„ fremhevet en 27-dagers syklisk trykkrespons i sine resultater som indirekte bevis for en fysisk forbindelse. Vi demonstrerer at denne periodiske trykkresponsen oppstĂ„r som et resultat av de statistiske metodene som er brukt, og kan derfor ikke brukes som en indikator pĂ„ en fysisk sammenheng. Videre oppdages en hittil ukjent robust og statistisk signifikant korrelasjon mellom IMF By og polart atmosfĂŠrisk trykk ved havnivĂ„. Korrelasjonen er tydelig i perioden mars-april-mai pĂ„ begge halvkuler, men med en tilsynelatende ufysisk timing med hensyn til Mansurov-effekten. I alt fremhever resultatene det generelle behovet for grundig statistisk testing, samt behovet for varsomhet nĂ„r man bruker spesifikke metoder sammen med periodiske og autokorrelerte variabler.Recent years have seen a surge in observational, re-analysis, and model-based studies providing evidence of statistical correlations between day-to-day to interannual solar activity and climate/weather patterns. The overarching objective of this thesis is to delve into the theory of two solar-climate mechanisms, the Chemical-Dynamical coupling and the Mansurov effect. The Chemical-Dynamical coupling is linked to the ionization of the upper atmosphere (ÂĄ50 km) by energetic particle precipitation (EPP), resulting in the production of odd nitrogen and hydrogen oxides (NOx and HOx). These compounds are effective ozone depleters, and can alter the radiative balance of the atmosphere, potentially leading to a cascading effect in dynamically induced atmospheric weather changes observable in the polar atmosphere. The Mansurov effect is related to the interplanetary magnetic field (IMF) and its ability to modulate the global electric circuit (GEC), which is further assumed to impact the polar troposphere through cloud generation processes. It is hypothesised to occur nearly instantaneously, providing a physical link between near-Earth-space and the lower atmosphere. These topics will be studied with sophisticated statistical analysis methods. For the Chemical-Dynamical coupling, we use the SOCOL3-MPIOM model to compare the northern polar atmospheric temperature differences in ensemble members with and without EPP. The analyses builds on recent re-analysis evidence showing that EPP mostly impacts the northern polar atmospheric temperature right before and during disturbed Polar Vortex (PV) conditions. We find highly significant temperature responses during conditions set up by minor Sudden Stratospheric Warmings (SSW), associated with disturbed polar vortex and enhanced planetary wave activity. The largest anomalies are seen in February, and only for the latter half (1955–2008) of the simulation period (1900–2008). The findings suggest that during winter, the Chemical-Dynamical coupling could play a crucial role in stratospheric conditions and confirms the existence of the chemical-dynamical link in the model. By using ERA5 atmospheric re-analysis data and OMNIweb IMF data spanning 1968–2020, the connection between the IMF By and polar surface pressure is investigated. Contrary to prior published studies on the Mansurov effect, no significant response is found after accounting for autocorrelation and multiple hypothesis testing. In addition, prior studies highlight a 27-day cyclic pressure response as indirect evidence of a physical link. However, we show that this periodic pressure behaviour occurs as a statistical artefact of the methods, and is not a reliable indicator of a causal connection. Furthermore, a new robust and statistically significant correlation is determined between the IMF By and polar surface pressure. It is found in the time-period March-April-May for both hemispheres, but with an unphysical timing with respect to the Mansurov hypothesis. The analyses highlight the general need for rigorous statistical testing, as well as the need for caution when deploying certain methodologies with periodic and highly autocorrelated variables.Doktorgradsavhandlin

    Evaluation Methodologies in Software Protection Research

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    Man-at-the-end (MATE) attackers have full control over the system on which the attacked software runs, and try to break the confidentiality or integrity of assets embedded in the software. Both companies and malware authors want to prevent such attacks. This has driven an arms race between attackers and defenders, resulting in a plethora of different protection and analysis methods. However, it remains difficult to measure the strength of protections because MATE attackers can reach their goals in many different ways and a universally accepted evaluation methodology does not exist. This survey systematically reviews the evaluation methodologies of papers on obfuscation, a major class of protections against MATE attacks. For 572 papers, we collected 113 aspects of their evaluation methodologies, ranging from sample set types and sizes, over sample treatment, to performed measurements. We provide detailed insights into how the academic state of the art evaluates both the protections and analyses thereon. In summary, there is a clear need for better evaluation methodologies. We identify nine challenges for software protection evaluations, which represent threats to the validity, reproducibility, and interpretation of research results in the context of MATE attacks

    The role of quantum coherence and dissipation in cosmology

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    This thesis looks at different manifestations that the non-unitary dynamics proper of dissipation can have during the inflationary era and the late-time universe. For starters, we formalise the calculation of the primordial spectrum in warm inflation, which significantly differs in terms of phenomenology from the standard inflationary picture because of the extra degrees of freedom that originate due to the dissipation of energy from the inflaton field into a thermal radiation bath. Then, turning our attention to inflation in the context of string theory, we point out how the fluctuation-dissipation dynamic in warm inflation makes it robust against most of the so-called swampland conjectures. Nevertheless, that is not the case for the trans-Planckian censorship conjecture (TCC), which severely limits the duration of inflation to avoid trans-Planckian (TP) modes becoming observable, threatening the EFT description of inflation. In general, only models of inflation with a small energy scale can satisfy the TCC, effectively destroying any hope of experimental confirmation of inflation. To deal with this, we proposed a multi-stage warm inflation scenario with radiation-dominated eras in between. Such a model proved successful in opening a wider range of available energies that could make a model satisfying the TCC produce sizeable tensor perturbations. However, we also argue in favour of refinements of TCC that could make most high-energy models consistent with the conjecture. To do this, we looked at several mechanisms of subhorizon decoherence, like preheating and warm inflation itself, ultimately proving that keeping TP modes hidden inside the horizon is not enough to prevent their classicalisation, negating in this way the original premise of TCC. Next, in a different direction, we study inflationary perturbations as an open quantum system, with an environment composed of subhorizon fluctuations and a system of superhorizon modes. We argue that this is the most appropriate way to study the physics of inflationary perturbations, as opposed to standard Wilsonian EFTs. We use the technology of open quantum systems in two big setups: scalar and tensor perturbations. In both cases, we compute the corrections to the two-point correlation function due to gravitational nonlinearities present in the Einstein-Hilbert action. This allowed us to explore topics such as long-time IR behaviour, (non-)Markovian behaviour, and the relation between this method and a standard loop expansion. Finally, we changed our gears and looked at the viability of establishing quantum communication channels mediated by photons across astronomical and cosmological distances. For this, we survey multiple factors that could potentially disrupt the quantum state of the photons, like charged particles in space or the gravitational field of astrophysical bodies. We concluded that the x-ray portion of the electromagnetic spectrum would be ideal for establishing a quantum communication channel

    Synthetic Aperture Radar (SAR) Meets Deep Learning

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    This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports
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