Book of Abstracts of the Sixth SIAM Workshop on Combinatorial Scientific Computing

Book of Abstracts of CSC14 edited by Bora UçarInternational audienceThe Sixth SIAM Workshop on Combinatorial Scientific Computing, CSC14, was organized at the Ecole Normale Supérieure de Lyon, France on 21st to 23rd July, 2014. This two and a half day event marked the sixth in a series that started ten years ago in San Francisco, USA. The CSC14 Workshop's focus was on combinatorial mathematics and algorithms in high performance computing, broadly interpreted. The workshop featured three invited talks, 27 contributed talks and eight poster presentations. All three invited talks were focused on two interesting fields of research specifically: randomized algorithms for numerical linear algebra and network analysis. The contributed talks and the posters targeted modeling, analysis, bisection, clustering, and partitioning of graphs, applied in the context of networks, sparse matrix factorizations, iterative solvers, fast multi-pole methods, automatic differentiation, high-performance computing, and linear programming. The workshop was held at the premises of the LIP laboratory of ENS Lyon and was generously supported by the LABEX MILYON (ANR-10-LABX-0070, Université de Lyon, within the program ''Investissements d'Avenir'' ANR-11-IDEX-0007 operated by the French National Research Agency), and by SIAM

Revisiting Actor Programming in C++

The actor model of computation has gained significant popularity over the last decade. Its high level of abstraction makes it appealing for concurrent applications in parallel and distributed systems. However, designing a real-world actor framework that subsumes full scalability, strong reliability, and high resource efficiency requires many conceptual and algorithmic additives to the original model. In this paper, we report on designing and building CAF, the "C++ Actor Framework". CAF targets at providing a concurrent and distributed native environment for scaling up to very large, high-performance applications, and equally well down to small constrained systems. We present the key specifications and design concepts---in particular a message-transparent architecture, type-safe message interfaces, and pattern matching facilities---that make native actors a viable approach for many robust, elastic, and highly distributed developments. We demonstrate the feasibility of CAF in three scenarios: first for elastic, upscaling environments, second for including heterogeneous hardware like GPGPUs, and third for distributed runtime systems. Extensive performance evaluations indicate ideal runtime behaviour for up to 64 cores at very low memory footprint, or in the presence of GPUs. In these tests, CAF continuously outperforms the competing actor environments Erlang, Charm++, SalsaLite, Scala, ActorFoundry, and even the OpenMPI.Comment: 33 page

Energy efficiency in wireless communications for mobile user devices

Mención Internacional en el título de doctorMobile user devices’ market has experi-enced an exponential growth worldwide over the last decade, and wireless communications are the main driver for the next generation of 5G networks. The ubiquity of battery-powered connected devices makes energy efficiency a major research issue. While most studies assumed that network interfaces dominate the energy consumption of wireless communications, a recent work unveils that the frame processing carried out by the device could drain as much energy as the interface itself for many devices. This discovery poses doubts on prior energy models for wireless communications and forces us to reconsider existing energy-saving schemes. From this standpoint, this thesis is de-voted to the study of the energy efficiency of mobile user devices at multiple layers. To that end, we assemble a comprehensive en-ergy measurement framework, and a robust methodology, to be able to characterise a wide range of mobile devices, as well as individual parts of such devices. Building on this, we first delve into the en-ergy consumption of frame processing within the devices’ protocol stack. Our results identify the CPU as the leading cause of this energy consumption. Moreover, we discover that the characterisation of the energy toll ascribed to the device is much more complex than the previous work showed. Devices with complex CPUs (several frequencies and sleep states) require novel methodologies and models to successfully characterise their consumption. We then turn our attention to lower levels of the communication stack by investigating the behaviour of idle WiFi interfaces. Due to the design of the 802.11 protocol, together with the growing trend of network densification, WiFi devices spend a long time receiving frames addressed to other devices when they might be dormant. In order to mitigate this issue, we study the timing constraints of a commercial WiFi card, which is developed into a standard-compliant algorithm that saves energy during such transmissions. At a higher level, rate adaptation and power control techniques adapt data rate and output power to the channel conditions. However, these have been typically studied with other metrics rather than energy efficiency in mind (i.e., performance figures such as throughput and capacity). In fact, our analyses and sim-ulations unveil an inherent trade-off between throughput and energy efficiency maximisa-tion in 802.11. We show that rate adaptation and power control techniques may incur inef-ficiencies at mode transitions, and we provide energy-aware heuristics to make such decisions following a conservative approach. Finally, our research experience on simula-tion methods pointed us towards the need for new simulation tools commited to the middle-way approach: less specificity than complex network simulators in exchange for easier and faster prototyping. As a result, we developed a process-oriented and trajectory-based discrete-event simulation package for the R language, which is designed as a easy-to-use yet pow-erful framework with automatic monitoring capabilities. The use of this simulator in net-working is demonstrated through the energy modelling of an Internet-of-Things scenario with thousands of metering devices in just a few lines of code.El mercado de los dispositivos de usuario móviles ha experimentado un crecimiento exponencial a nivel mundial en la última década, y las comunicaciones inalámbricas son el principal motor de la siguiente generación de redes 5G. La ubicuidad de estos dispos-itivos alimentados por baterías hace de la eficiencia energética un importante tema de investigación. Mientras muchos estudios asumían que la interfaz de red domina el consumo energético de las comuni-caciones inalámbricas, un trabajo reciente revela que el procesado de tramas que se lleva a cabo en el disposi-tivo podría gastar tanta energía como la propia interfaz para muchos dispositivos. Este descubrimiento plantea dudas sobre los anteriores modelos energéticos para comunicaciones inalámbricas y nos obliga a reconsid-erar los esquemas de ahorro energético existentes. Desde este punto de vista, esta tesis está dedicada al estudio de la eficiencia energética de dispositivos de usuario móviles en múltiples capas. Para ello, se construye un completo sistema de medida de energía, y una metodología robusta, capaz de caracterizar un amplio rango de dispositivos móviles, así como partes individuales de tales dispositivos. A partir de esto, en primer lugar se profundiza en el consumo energético del procesamiento de tramas en la pila de protocolos de los dispositivos. Nuestros resul-tados identifican a la CPU como principal causa de tal consumo. Además, se descubre que la caracterización de la cuota energética adscrita al dispositivo es mucho más compleja que lo mostrado por el trabajo ante-rior. Los dispositivos con CPU complejas (múltiples frecuencias y modos de apagado) requieren nuevas metodologías y modelos para caracterizar su consumo de manera existosa. En este punto, volvemos nuestra atención hacia niveles más bajos de la pila de comunicaciones para investigar el comportamiento de las interfaces WiFi en estado inactivo. Debido al diseño del protocolo 802.11, junto con la tendencia creciente hacia la densifi-cación de las redes, los dispositivos WiFi pasan mucho tiempo recibiendo tramas destinadas a otros dispos-itivos cuando podrían estar apagados. Para mitigar este problema, se estudian las limitaciones temporales de una tarjeta WiFi comercial, lo que posteriormente se utiliza para desarrollar un algoritmo conforme con el estándar que es capaz de ahorrar energía durante dichas transmisiones. A un nivel más alto, las técnicas de adaptación de tasa y control de potencia adaptan la tasa de datos y la potencia de salida a las condiciones del canal. No obstante, estas técnicas han sido típicamente es-tudiadas con otras métricas en mente (i.e., figuras de rendimiento como la tasa total y la capacidad). De hecho, nuestros análisis y simulaciones desvelan un conflicto entre la maximización de la tasa total y la efi-ciencia energética en 802.11. Se muestra que las técni-cas de adaptación de tasa y control de potencia pueden incurrir en ineficiencias en los cambios de modo, y se proporcionan heurísticos para tomar tales decisiones de un modo conservador y eficiente energéticamente. Finalmente, nuestra experiencia investigadora en métodos de simulación nos hizo conscientes de la necesidad de nuevas herramientas de simulación comprometidas con un enfoque intermedio: menos especificidad que los complejos simuladores de re-des a cambio de facilidad y rapidez en el prototipado. Como resultado, se desarrolló un paquete de simu-lación por eventos discretos para el lenguaje R orien-tado a procesos y basado en trayectorias, el cual está diseñado como una herramienta fácil de utilizar a la par que potente con capacidad de monitorización au-tomática integrada. El uso de este simulador en redes se demuestra mediante el modelado en energía de un escenario de la Internet de las Cosas con miles de dis-positivos de medida en tan solo unas pocas líneas de código.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Juan Manuel López Soler.- Secretario: Francisco Valera Pintor.- Vocal: Paul Horatiu Patra

ULTRA-FAST AND MEMORY-EFFICIENT LOOKUPS FOR CLOUD, NETWORKED SYSTEMS, AND MASSIVE DATA MANAGEMENT

Systems that process big data (e.g., high-traffic networks and large-scale storage) prefer data structures and algorithms with small memory and fast processing speed. Efficient and fast algorithms play an essential role in system design, despite the improvement of hardware. This dissertation is organized around a novel algorithm called Othello Hashing. Othello Hashing supports ultra-fast and memory-efficient key-value lookup, and it fits the requirements of the core algorithms of many large-scale systems and big data applications. Using Othello hashing, combined with domain expertise in cloud, computer networks, big data, and bioinformatics, I developed the following applications that resolve several major challenges in the area. Concise: Forwarding Information Base. A Forwarding Information Base is a data structure used by the data plane of a forwarding device to determine the proper forwarding actions for packets. The polymorphic property of Othello Hashing the separation of its query and control functionalities, which is a perfect match to the programmable networks such as Software Defined Networks. Using Othello Hashing, we built a fast and scalable FIB named \textit{Concise}. Extensive evaluation results on three different platforms show that Concise outperforms other FIB designs. SDLB: Cloud Load Balancer. In a cloud network, the layer-4 load balancer servers is a device that acts as a reverse proxy and distributes network or application traffic across a number of servers. We built a software load balancer with Othello Hashing techniques named SDLB. SDLB is able to accomplish two functionalities of the SDLB using one Othello query: to find the designated server for packets of ongoing sessions and to distribute new or session-free packets. MetaOthello: Taxonomic Classification of Metagenomic Sequences. Metagenomic read classification is a critical step in the identification and quantification of microbial species sampled by high-throughput sequencing. Due to the growing popularity of metagenomic data in both basic science and clinical applications, as well as the increasing volume of data being generated, efficient and accurate algorithms are in high demand. We built a system to support efficient classification of taxonomic sequences using its k-mer signatures. SeqOthello: RNA-seq Sequence Search Engine. Advances in the study of functional genomics produced a vast supply of RNA-seq datasets. However, how to quickly query and extract information from sequencing resources remains a challenging problem and has been the bottleneck for the broader dissemination of sequencing efforts. The challenge resides in both the sheer volume of the data and its nature of unstructured representation. Using the Othello Hashing techniques, we built the SeqOthello sequence search engine. SeqOthello is a reference-free, alignment-free, and parameter-free sequence search system that supports arbitrary sequence query against large collections of RNA-seq experiments, which enables large-scale integrative studies using sequence-level data

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Accelerating Network Functions using Reconfigurable Hardware. Design and Validation of High Throughput and Low Latency Network Functions at the Access Edge

Providing Internet access to billions of people worldwide is one of the main technical challenges in the current decade. The Internet access edge connects each residential and mobile subscriber to this network and ensures a certain Quality of Service (QoS). However, the implementation of access edge functionality challenges Internet service providers: First, a good QoS must be provided to the subscribers, for example, high throughput and low latency. Second, the quick rollout of new technologies and functionality demands flexible configuration and programming possibilities of the network components; for example, the support of novel, use-case-specific network protocols. The functionality scope of an Internet access edge requires the use of programming concepts, such as Network Functions Virtualization (NFV). The drawback of NFV-based network functions is a significantly lowered resource efficiency due to the execution as software, commonly resulting in a lowered QoS compared to rigid hardware solutions. The usage of programmable hardware accelerators, named NFV offloading, helps to improve the QoS and flexibility of network function implementations. In this thesis, we design network functions on programmable hardware to improve the QoS and flexibility. First, we introduce the host bypassing concept for improved integration of hardware accelerators in computer systems, for example, in 5G radio access networks. This novel concept bypasses the system’s main memory and enables direct connectivity between the accelerator and network interface card. Our evaluations show an improved throughput and significantly lowered latency jitter for the presented approach. Second, we analyze different programmable hardware technologies for hardware-accelerated Internet subscriber handling, including three P4-programmable platforms and FPGAs. Our results demonstrate that all approaches have excellent performance and are suitable for Internet access creation. We present a fully-fledged User Plane Function (UPF) designed upon these concepts and test it in an end-to-end 5G standalone network as part of this contribution. Third, we analyze and demonstrate the usability of Active Queue Management (AQM) algorithms on programmable hardware as an expansion to the access edge. We show the feasibility of the CoDel AQM algorithm and discuss the challenges and constraints to be considered when limited hardware is used. The results show significant improvements in the QoS when the AQM algorithm is deployed on hardware. Last, we focus on network function benchmarking, which is crucial for understanding the behavior of implementations and their optimization, e.g., Internet access creation. For this, we introduce the load generation and measurement framework P4STA, benefiting from flexible software-based load generation and hardware-assisted measuring. Utilizing programmable network switches, we achieve a nanosecond time accuracy while generating test loads up to the available Ethernet link speed

On Information-centric Resiliency and System-level Security in Constrained, Wireless Communication

The Internet of Things (IoT) interconnects many heterogeneous embedded devices either locally between each other, or globally with the Internet. These things are resource-constrained, e.g., powered by battery, and typically communicate via low-power and lossy wireless links. Communication needs to be secured and relies on crypto-operations that are often resource-intensive and in conflict with the device constraints. These challenging operational conditions on the cheapest hardware possible, the unreliable wireless transmission, and the need for protection against common threats of the inter-network, impose severe challenges to IoT networks. In this thesis, we advance the current state of the art in two dimensions. Part I assesses Information-centric networking (ICN) for the IoT, a network paradigm that promises enhanced reliability for data retrieval in constrained edge networks. ICN lacks a lower layer definition, which, however, is the key to enable device sleep cycles and exclusive wireless media access. This part of the thesis designs and evaluates an effective media access strategy for ICN to reduce the energy consumption and wireless interference on constrained IoT nodes. Part II examines the performance of hardware and software crypto-operations, executed on off-the-shelf IoT platforms. A novel system design enables the accessibility and auto-configuration of crypto-hardware through an operating system. One main focus is the generation of random numbers in the IoT. This part of the thesis further designs and evaluates Physical Unclonable Functions (PUFs) to provide novel randomness sources that generate highly unpredictable secrets, on low-cost devices that lack hardware-based security features. This thesis takes a practical view on the constrained IoT and is accompanied by real-world implementations and measurements. We contribute open source software, automation tools, a simulator, and reproducible measurement results from real IoT deployments using off-the-shelf hardware. The large-scale experiments in an open access testbed provide a direct starting point for future research

Annual Report, 2013-2014

Beginning in 2004/2005- issued in online format onl