1,619 research outputs found
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Design of Efficient TLB-based Data Classification Mechanisms in Chip Multiprocessors
Most of the data referenced by sequential and parallel applications running in current chip multiprocessors are referenced by a single thread, i.e., private. Recent proposals leverage this observation to improve many aspects of chip multiprocessors, such as reducing coherence overhead or the access latency to distributed caches. The effectiveness of those proposals depends to a large extent on the amount of detected private data. However, the mechanisms proposed so far either do not consider either thread migration or the private use of data within different application phases, or do entail high overhead. As a result, a considerable amount of private data is not detected. In order to increase the detection of private data, this thesis proposes a TLB-based
mechanism that is able to account for both thread migration and private application phases with low overhead. Classification status in the proposed TLB-based classification mechanisms is determined by the presence of the page translation stored in other
core's TLBs. The classification schemes are analyzed in multilevel TLB hierarchies, for systems with both private and distributed shared last-level TLBs.
This thesis introduces a page classification approach based on inspecting other core's TLBs upon every TLB miss. In particular, the proposed classification approach is based on exchange and count of tokens. Token counting on TLBs is a natural and efficient way for classifying memory pages. It does not require the use of complex and undesirable persistent requests or arbitration, since when two ormore TLBs race for accessing a page, tokens are appropriately distributed classifying the page as shared.
However, TLB-based ability to classify private pages is strongly dependent on TLB size, as it relies on the presence of a page translation in the system TLBs. To overcome that, different TLB usage predictors (UP) have been proposed, which allow a page classification unaffected by TLB size. Specifically, this thesis introduces a predictor that obtains system-wide page usage information by either employing a shared last-level TLB structure (SUP) or cooperative TLBs working together (CUP).La mayor parte de los datos referenciados por aplicaciones paralelas y secuenciales que se ejecutan enCMPs actuales son referenciadas por un único hilo, es decir, son privados. Recientemente, algunas propuestas aprovechan esta observación para mejorar muchos aspectos de los CMPs, como por ejemplo reducir el sobrecoste de la coherencia o la latencia de los accesos a cachés distribuidas. La efectividad de estas propuestas depende en gran medida de la cantidad de datos que son considerados privados. Sin embargo, los mecanismos propuestos hasta la fecha no consideran la migración de hilos de ejecución ni las fases de una aplicación. Por tanto, una cantidad considerable de datos privados no se detecta apropiadamente. Con el fin de aumentar la detección de datos privados, proponemos un mecanismo basado en las TLBs, capaz de reclasificar los datos a privado, y que detecta la migración de los hilos de ejecución sin añadir complejidad al sistema. Los mecanismos de clasificación en las TLBs se han analizado en estructuras de varios niveles, incluyendo TLBs privadas y con un último nivel de TLB compartido y distribuido.
Esta tesis también presenta un mecanismo de clasificación de páginas basado en la inspección de las TLBs de otros núcleos tras cada fallo de TLB. De forma particular, el mecanismo propuesto se basa en el intercambio y el cuenteo de tokens (testigos).
Contar tokens en las TLBs supone una forma natural y eficiente para la clasificación de páginas de memoria. Además, evita el uso de solicitudes persistentes o arbitraje alguno, ya que si dos o más TLBs compiten para acceder a una página, los tokens se
distribuyen apropiadamente y la clasifican como compartida.
Sin embargo, la habilidad de los mecanismos basados en TLB para clasificar páginas privadas depende del tamaño de las TLBs. La clasificación basada en las TLBs se basa en la presencia de una traducción en las TLBs del sistema. Para evitarlo, se han propuesto diversos predictores de uso en las TLBs (UP), los cuales permiten una clasificación independiente del tamaño de las TLBs. En concreto, esta tesis presenta un sistema mediante el que se obtiene información de uso de página a nivel de sistema con la ayuda de un nivel de TLB compartida (SUP) o mediante TLBs cooperando juntas (CUP).La major part de les dades referenciades per aplicacions paral·leles i seqüencials que s'executen en CMPs actuals són referenciades per un sol fil, és a dir, són privades. Recentment, algunes propostes aprofiten aquesta observació per a millorar molts aspectes dels CMPs, com és reduir el sobrecost de la coherència o la latència d'accés a memòries cau distribuïdes. L'efectivitat d'aquestes propostes depen en gran mesura de la quantitat de dades detectades com a privades. No obstant això, els mecanismes proposats fins a la data no consideren la migració de fils d'execució ni les fases d'una aplicació. Per tant, una quantitat considerable de dades privades no es detecta apropiadament. A fi d'augmentar la detecció de dades privades, aquesta tesi proposa un mecanisme basat en les TLBs, capaç de reclassificar les dades com a privades, i que detecta la migració dels fils d'execució sense afegir complexitat al sistema. Els mecanismes de classificació en les TLBs s'han analitzat en estructures de diversos nivells, incloent-hi sistemes amb TLBs d'últimnivell compartides i distribuïdes.
Aquesta tesi presenta un mecanisme de classificació de pàgines basat en inspeccionar les TLBs d'altres nuclis després de cada fallada de TLB. Concretament, el mecanisme proposat es basa en l'intercanvi i el compte de tokens. Comptar tokens en les TLBs suposa una forma natural i eficient per a la classificació de pàgines de memòria. A més, evita l'ús de sol·licituds persistents o arbitratge, ja que si dues o més TLBs competeixen per a accedir a una pàgina, els tokens es distribueixen apropiadament i la classifiquen com a compartida.
No obstant això, l'habilitat dels mecanismes basats en TLB per a classificar pàgines privades depenen de la grandària de les TLBs. La classificació basada en les TLBs resta en la presència d'una traducció en les TLBs del sistema. Per a evitar-ho, s'han proposat diversos predictors d'ús en les TLBs (UP), els quals permeten una classificació independent de la grandària de les TLBs. Específicament, aquesta tesi introdueix un predictor que obté informació d'ús de la pàgina a escala de sistema mitjançant un nivell de TLB compartida (SUP) or mitjançant TLBs cooperant juntes (CUP).Esteve García, A. (2017). Design of Efficient TLB-based Data Classification Mechanisms in Chip Multiprocessors [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86136TESI
A scalable parallel finite element framework for growing geometries. Application to metal additive manufacturing
This work introduces an innovative parallel, fully-distributed finite element
framework for growing geometries and its application to metal additive
manufacturing. It is well-known that virtual part design and qualification in
additive manufacturing requires highly-accurate multiscale and multiphysics
analyses. Only high performance computing tools are able to handle such
complexity in time frames compatible with time-to-market. However, efficiency,
without loss of accuracy, has rarely held the centre stage in the numerical
community. Here, in contrast, the framework is designed to adequately exploit
the resources of high-end distributed-memory machines. It is grounded on three
building blocks: (1) Hierarchical adaptive mesh refinement with octree-based
meshes; (2) a parallel strategy to model the growth of the geometry; (3)
state-of-the-art parallel iterative linear solvers. Computational experiments
consider the heat transfer analysis at the part scale of the printing process
by powder-bed technologies. After verification against a 3D benchmark, a
strong-scaling analysis assesses performance and identifies major sources of
parallel overhead. A third numerical example examines the efficiency and
robustness of (2) in a curved 3D shape. Unprecedented parallelism and
scalability were achieved in this work. Hence, this framework contributes to
take on higher complexity and/or accuracy, not only of part-scale simulations
of metal or polymer additive manufacturing, but also in welding, sedimentation,
atherosclerosis, or any other physical problem where the physical domain of
interest grows in time
Mobile Ad hoc Networking: Imperatives and Challenges
Mobile ad hoc networks (MANETs) represent complex distributed systems that comprise wireless mobile nodes that can freely and dynamically self-organize into arbitrary and temporary, "ad-hoc" network topologies, allowing people and devices to seamlessly internetwork in areas with no pre-existing communication infrastructure, e.g., disaster recovery environments. Ad hoc networking concept is not a new one, having been around in various forms for over 20 years. Traditionally, tactical networks have been the only communication networking application that followed the ad hoc paradigm. Recently, the introduction of new technologies such as the Bluetooth, IEEE 802.11 and Hyperlan are helping enable eventual commercial MANET deployments outside the military domain. These recent evolutions have been generating a renewed and growing interest in the research and development of MANET. This paper attempts to provide a comprehensive overview of this dynamic field. It first explains the important role that mobile ad hoc networks play in the evolution of future wireless technologies. Then, it reviews the latest research activities in these areas, including a summary of MANET\u27s characteristics, capabilities, applications, and design constraints. The paper concludes by presenting a set of challenges and problems requiring further research in the future
- …