In this report, we describe the design and implementation of Ibdxnet, a low-latency and high-throughput transport providing the benefits of InfiniBand networks to Java applications. Ibdxnet is part of the Java-based DXNet library, a highly concurrent and simple to use messaging stack with transparent serialization of messaging objects and focus on very small messages (< 64 bytes). Ibdxnet implements the transport interface of DXNet in Java and a custom C++ library in native space using JNI. Several optimizations in both spaces minimize context switching overhead between Java and C++ and are not burdening message latency or throughput. Communication is implemented using the messaging verbs of the ibverbs library complemented by an automatic connection management in the native library. We compared DXNet with the Ibdxnet transport to the MPI implementations FastMPJ and MVAPICH2. For small messages up to 64 bytes using multiple threads, DXNet with the Ibdxnet transport achieves a bi-directional message rate of 10 million messages per second and surpasses FastMPJ by a factor of 4 and MVAPICH by a factor of 2. Furthermore, DXNet scales well on a high load all-to-all communication with up to 8 nodes achieving a total aggregated message rate of 43.4 million messages per second for small messages and a throughput saturation of 33.6 GB s with only 2 kb message size.
@cite_32 is a network stack designed for next generation systems for applications with an highly multi-threaded environment. It provides three independent layers: UCS is a service layer with different cross platform utilities, such as atomic operations, thread safety, memory management and data structures. The transport layer UCT abstracts different hardware architectures and their low-level APIs, and provides an API to implement communication primitives. UCP implements high level protocols such as MPI or PGAS programming models by using UCT.
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This paper presents Unified Communication X (UCX), a set of network APIs and their implementations for high throughput computing. UCX comes from the combined effort of national laboratories, industry, and academia to design and implement a high-performing and highly-scalable network stack for next generation applications and systems. UCX design provides the ability to tailor its APIs and network functionality to suit a wide variety of application domains and hardware. We envision these APIs to satisfy the networking needs of many programming models such as Message Passing Interface (MPI), OpenSHMEM, Partitioned Global Address Space (PGAS) languages, task-based paradigms and I O bound applications. To evaluate the design we implement the APIs and protocols, and measure the performance of overhead-critical network primitives fundamental for implementing many parallel programming models and system libraries. Our results show that the latency, bandwidth, and message rate achieved by the portable UCX prototype is very close to that of the underlying driver. With UCX, we achieved a message exchange latency of 0.89 us, a bandwidth of 6138.5 MB s, and a message rate of 14 million messages per second. As far as we know, this is the highest bandwidth and message rate achieved by any network stack (publicly known) on this hardware. We investigate a wireless system of multiple cells, each having a downlink shared channel in support of high-speed packet data services. In practice, such a system consists of hierarchically organized entities including a central server, Base Stations (BSs), and Mobile Stations (MSs). Our goal is to improve global resource utilization and reduce regional congestion given asymmetric arrivals and departures of mobile users, a goal requiring load balancing among multiple cells. For this purpose, we propose a scalable cross-layer framework to coordinate packet-level scheduling, call-level cell-site selection and handoff, and system-level cell coverage based on load, throughput, and channel measurements. In this framework, an opportunistic scheduling algorithm--the weighted Alpha-Rule--exploits the gain of multiuser diversity in each cell independently, trading aggregate (mean) down-link throughput for fairness and minimum rate guarantees among MSs. Each MS adapts to its channel dynamics and the load fluctuations in neighboring cells, in accordance with MSs' mobility or their arrival and departure, by initiating load-aware handoff and cell-site selection. The central server adjusts schedulers of all cells to coordinate their coverage by prompting cell breathing or distributed MS handoffs. Across the whole system, BSs and MSs constantly monitor their load, throughput, or channel quality in order to facilitate the overall system coordination. Our specific contributions in such a framework are highlighted by the minimum-rate guaranteed weighted Alpha-Rule scheduling, the load-aware MS handoff cell-site selection, and the Media Access Control (MAC)-layer cell breathing. Our evaluations show that the proposed framework can improve global resource utilization and load balancing, resulting in a smaller blocking rate of MS arrivals without extra resources while the aggregate throughput remains roughly the same or improved at the hot-spots. Our simulation tests also show that the coordinated system is robust to dynamic load fluctuations and is scalable to both the system dimension and the size of MS population. In this paper we propose a distributed and scalable algorithm that eliminates congestion within a sensor network, and that ensures the fair delivery of packets to a central node, or base station. We say that fairness is achieved when equal number of packets are received from each node. Since in general we have many sensors transmitting data to the base station, we consider the scenario where we have many-to-one multihop routing, noting that it can easily be extended to unicast or many-to-many routing. Such routing structures often result in the sensors closer to the base station experiencing congestion, which inevitably cause packets originating from sensors further away from the base station to have a higher probability of being dropped. Our algorithm exists in the transport layer of the traditional network stack model, and is designed to work with any MAC protocol in the data-link layer with minor modifications. Our solution is scalable, each sensor mote requires state proportional to the number of its neighbors. Finally, we demonstrate the effectiveness of our solution with both simulations and actual implementation in UC Berkeley's sensor motes. The scalable video coding extension of H.264 AVC is a current standardization project. This paper deals with unequal error protection (UEP) scheme for scalable video bitstream over packet-lossy networks using forward error correction (FEC). The proposed UEP scheme is developed by exploiting jointly the unequal importance existing both in temporal layers and quality layers of hierarchial scalable video bitstream. For efficient assignment of FEC codes, the proposed UEP scheme uses a simple and efficient performance metric, namely layer-weighted expected zone of error propagation (LW-EZEP). The LW-EZEP is adopted for quantifying the error propagation effect on video quality degradation from packet loss in temporal layers and in quality layers. Compared to other UEP schemes, the proposed UEP scheme demonstrates strong robustness and adaptation for variable channel status. Intel Many Integrated Core (MIC) architecture is steadily being adopted in clusters owing to its high compute throughput and power efficiency. The current generation MIC coprocessor, Xeon Phi, provides a highly multi-threaded environment with support for multiple programming models. While regular programming models such as MPI OpenMP have started utilizing systems with MIC coprocessors, it is still not clear whether PGAS models can easily adopt and fully utilize such systems. In this paper, we discuss several ways of running UPC applications on the MIC architecture under Native Symmetric programming mode. These methods include the choice of process-based or thread-based UPC runtime for native mode and different communication channels between MIC and host for symmetric mode. We propose a thread-based UPC runtime with an improved “leader-to-all” connection scheme over InfiniBand and SCIF [3] through multi-endpoint support. For the native mode, we evaluate point-topoint and collective micro-benchmarks, Global Array Random Access, UTS and NAS benchmarks. For the symmetric mode, we evaluate the communication performance between host and MIC within a single node. Through our evaluations, we explore the effects of scaling UPC threads on the MIC and also highlight the bottlenecks (up to 10X degradation) involved in UPC communication routines arising from the per-core processing and memory limitations on the MIC. To the best of our knowledge, this is the first paper that evaluates UPC programming model on MIC systems. Aggregate traffic loads and topology in multihop wireless networks may vary slowly, permitting MAC protocols to "learn" how to spatially coordinate and adapt contention patterns. Such an approach could reduce contention, leading to better throughput. To that end, we propose a family of MAC scheduling algorithms and demonstrate general conditions, which, if satisfied, ensure lattice rate optimality (i.e., achieving any rate-point on a uniform discrete lattice within the throughput region). This general framework enables the design of MAC protocols that meet various objectives and conditions. In this paper, as instances of such a lattice-rate-optimal family, we propose distributed, synchronous contention-based scheduling algorithms that: 1) are lattice-rate-optimal under both the signal-to-interference-plus-noise ratio (SINR)-based and graph-based interference models; 2) do not require node location information; and 3) only require three-stage RTS CTS message exchanges for contention signaling. Thus, the protocols are amenable to simple implementation and may be robust to network dynamics such as topology and load changes. Finally, we propose a heuristic, which also belongs to the proposed lattice-rate-optimal family of protocols and achieves faster convergence, leading to a better transient throughput. Reliable storage of data with concurrent read write accesses (or query update) is an ever recurring issue in distributed settings. In mobile ad hoc networks, the problem becomes even more challenging due to highly dynamic and unpredictable topology changes. It is precisely this unpredictability that makes probabilistic protocols very appealing for such environments. Inspired by the principles of probabilistic quorum systems, we present a Probabilistic quorum system for ad hoc networks Pan), a collection of protocols for the reliable storage of data in mobile ad hoc networks. Our system behaves in a predictable way due to the gossip-based diffusion mechanism applied for quorum accesses, and the protocol overhead is reduced by adopting an asymmetric quorum construction. We present an analysis of our Pan system, in terms of both reliability and overhead, which can be used to fine tune protocol parameters to obtain the desired tradeoff between efficiency and fault tolerance. We confirm the predictability and tunability of Pan through simulations with ns-2. An Aloha-type access control mechanism for large mobile, multihop, wireless networks is defined and analyzed. This access scheme is designed for the multihop context, where it is important to find a compromise between the spatial density of communications and the range of each transmission. More precisely, the analysis aims at optimizing the product of the number of simultaneously successful transmissions per unit of space (spatial reuse) by the average range of each transmission. The optimization is obtained via an averaging over all Poisson configurations for the location of interfering mobiles, where an exact evaluation of signal over noise ratio is possible. The main mathematical tools stem from stochastic geometry and are spatial versions of the so-called additive and max shot noise processes. The resulting medium access control (MAC) protocol exhibits some interesting properties. First, it can be implemented in a decentralized way provided some local geographic information is available to the mobiles. In addition, its transport capacity is proportional to the square root of the density of mobiles which is the upper bound of Gupta and Kumar. Finally, this protocol is self-adapting to the node density and it does not require prior knowledge of this density. Global Computing platforms, large scale clusters and future TeraGRID systems gather thousands of nodes for computing parallel scientific applications. At this scale, node failures or disconnections are frequent events. This Volatility reduces the MTBF of the whole system in the range of hours or minutes. We present MPICH-V, an automatic Volatility tolerant MPI environment based on uncoordinated checkpoint roll-back and distributed message logging. MPICH-V architecture relies on Channel Memories, Checkpoint servers and theoretically proven protocols to execute existing or new, SPMD and Master-Worker MPI applications on volatile nodes. To evaluate its capabilities, we run MPICH-V within a framework for which the number of nodes, Channels Memories and Checkpoint Servers can be completely configured as well as the node Volatility. We present a detailed performance evaluation of every component of MPICH-V and its global performance for non-trivial parallel applications. Experimental results demonstrate good scalability and high tolerance to node volatility. It is now well established that the device scaling predicted by Moore's Law is no longer a viable option for increasing the clock frequency of future uniprocessor systems at the rate that had been sustained during the last two decades. As a result, future systems are rapidly moving from uniprocessor to multiprocessor configurations, so as to use parallelism instead of frequency scaling as the foundation for increased compute capacity. The dominant emerging multiprocessor structure for the future is a Non-Uniform Cluster Computing (NUCC) system with nodes that are built out of multi-core SMP chips with non-uniform memory hierarchies, and interconnected in horizontally scalable cluster configurations such as blade servers. Unlike previous generations of hardware evolution, this shift will have a major impact on existing software. Current OO language facilities for concurrent and distributed programming are inadequate for addressing the needs of NUCC systems because they do not support the notions of non-uniform data access within a node, or of tight coupling of distributed nodes.We have designed a modern object-oriented programming language, X10, for high performance, high productivity programming of NUCC systems. A member of the partitioned global address space family of languages, X10 highlights the explicit reification of locality in the form of places ; lightweight activities embodied in async, future, foreach, and ateach constructs; a construct for termination detection (finish); the use of lock-free synchronization (atomic blocks); and the manipulation of cluster-wide global data structures. We present an overview of the X10 programming model and language, experience with our reference implementation, and results from some initial productivity comparisons between the X10 and Java™ languages. Data communication across the Internet has significantly changed under the pressure of massive content delivery. Content-Centric Networking (CCN) rethinks Internet communication paradigm around named data retrieval, in contrast with the host-to-host transport model of TCP IP. Content retrieval is natively pull-based driven by user requests, point-to-multipoint and intrinsically coupled with the availability of network storage. By leveraging the key features of CCN transport, in this paper we propose for the first time a congestion control mechanism realizing efficient multipath communication over content-centric networks. Our proposal is based on a Remote Adaptive Active Queue Management (RAAQM) at the receiver that performs a per-route control of bottleneck queues along the paths. We analyze the stability of the proposed solution and assess its performance by means of CCN packet-level simulations under random and optimal route selection. Application development for distributed-computing "Grids" can benefit from tools that variously hide or enable application-level management of critical aspects of the heterogeneous environment. As part of an investigation of these issues, we have developed MPICH-G2, a Grid-enabled implementation of the Message Passing Interface (MPI) that allows a user to run MPI programs across multiple computers, at the same or different sites, using the same commands that would be used on a parallel computer. This library extends the Argonne MPICH implementation of MPI to use services provided by the Globus Toolkit for authentication, authorization, resource allocation, executable staging, and I O, as well as for process creation, monitoring, and control. Various performance-critical operations, including startup and collective operations, are configured to exploit network topology information. The library also exploits MPI constructs for performance management; for example, the MPI communicator construct is used for application-level discovery of, and adaptation to, both network topology and network quality-of-service mechanisms. We describe the MPICH-G2 design and implementation, present performance results, and review application experiences, including record-setting distributed simulations. One critical issue in multihop ad hoc networks is the medium access control (MAC). The IEEE 802.11 MAC protocol is originally designed for fully connected, one-hop ad hoc networks but not for multihop ad hoc networks. In addition to the well known hidden-terminal problem, we found that IEEE 802.11 also suffers from an erroneous reservation problem which occurs when RTS-CTS exchange fails but the channel is incorrectly reserved. In this paper, we propose a jamming-based MAC (JMAC) protocol that is not only free from both hidden-terminal and the erroneous reservation problems but also allows more concurrent transmission reception activities for stations within each other's transmission range. The idea behind the JMAC is to separate source stations' traffic from destination stations' traffic into different channels (i.e., dividing the shared medium into two channels), and explicitly signal the channel status by jamming the channels. Simulation results show that the JMAC can provide higher channel utilization when system is in high traffic load and the frame size is medium or large. We investigate architectures of discriminatively trained deep Convolutional Networks (ConvNets) for action recognition in video. The challenge is to capture the complementary information on appearance from still frames and motion between frames. We also aim to generalise the best performing hand-crafted features within a data-driven learning framework. Our contribution is three-fold. First, we propose a two-stream ConvNet architecture which incorporates spatial and temporal networks. Second, we demonstrate that a ConvNet trained on multi-frame dense optical flow is able to achieve very good performance in spite of limited training data. Finally, we show that multitask learning, applied to two different action classification datasets, can be used to increase the amount of training data and improve the performance on both. Our architecture is trained and evaluated on the standard video actions benchmarks of UCF-101 and HMDB-51, where it is competitive with the state of the art. It also exceeds by a large margin previous attempts to use deep nets for video classification. The looming challenges of exascale computing are generating renewed interest in the Partitioned Global Address Space (PGAS) parallel programming model. From a high-performance interconnect perspective, the one-sided communication model in PGAS addresses some of the challenges that could inhibit the viability of traditional two-sided MPI message passing on millions of cores. The OpenSHMEM project is a recent effort at standardizing a lightweight one-sided communication interface to enable the development of highly scalable PGAS applications. The Portals data movement layer is a low-level one-sided interface that has successfully supported several higher-level one-sided and two-sided interfaces, including PGAS network transport layers. This paper describes the design and implementation of OpenSHMEM on the latest generation of the Portals interface, including a description of how Portals has evolved to maximize performance for PGAS-style communication operations. We investigate architectures of discriminatively trained deep Convolutional Networks (ConvNets) for action recognition in video. The challenge is to capture the complementary information on appearance from still frames and motion between frames. We also aim to generalise the best performing hand-crafted features within a data-driven learning framework. Our contribution is three-fold. First, we propose a two-stream ConvNet architecture which incorporates spatial and temporal networks. Second, we demonstrate that a ConvNet trained on multi-frame dense optical flow is able to achieve very good performance in spite of limited training data. Finally, we show that multi-task learning, applied to two different action classification datasets, can be used to increase the amount of training data and improve the performance on both. Our architecture is trained and evaluated on the standard video actions benchmarks of UCF-101 and HMDB-51, where it is competitive with the state of the art. It also exceeds by a large margin previous attempts to use deep nets for video classification. We propose to use Vehicular ad hoc networks (VANET) as the infrastructure for an urban cyber-physical system for gathering up-to-date data about a city, like traffic conditions or environmental parameters. In this context, it is critical to design a data collection protocol that enables retrieving the data from the vehicles in almost real-time in an efficient way for urban scenarios. We propose Back off-based Per-hop Forwarding (BPF), a broadcast-based receiver-oriented protocol that uses the destination location information to select the forwarding order among the nodes receiving the packet. BFP does not require nodes to exchange periodic messages with their neighbors communicating their locations to keep a low management message overhead. It uses geographic information about the final destination node in the header of each data packet to route it in a hop-by-hop basis. It takes advantage of redundant forwarding to increase packet delivery to a destination, what is more critical in an urban scenario than in a highway, where the road topology does not represent a challenge for forwarding. We evaluate the performance of the BPF protocol using ns-3 and a Manhattan grid topology and compare it with well-known broadcast suppression techniques. Our results show that BPF achieves significantly higher packet delivery rates at a reduced redundancy cost. Universal mobile telecommunication system (UMTS) networks should be deployed according to cost-effective strategies that optimize a cost objective and satisfy target quality-of-service (QoS) requirements. In this paper, we propose novel algorithms for joint uplink downlink UMTS radio planning with the objective of minimizing total power consumption in the network. Specifically, we define two components of the radio planning problem: 1) continuous-based site placement and 2) integer-based site selection. In the site-placement problem, our goal is to find the optimal locations of UMTS base stations (BSs) in a certain geographic area with a given user distribution to minimize the total power expenditure such that a satisfactory level of downlink and uplink signal-to-interference ratio (SIR) is maintained with bounded outage constraints. We model the problem as a constrained optimization problem with SIR-based uplink and downlink power control scheme. An algorithm is proposed and implemented using pattern search techniques for derivative-free optimization with augmented Lagrange multiplier estimates to support general constraints. In the site-selection problem, we aim to select the minimum set of BSs from a fixed set of candidate sites that satisfies quality and outage constraints. We develop an efficient elimination algorithm by proposing a method for classifying BSs that are critical for network coverage and QoS. Finally, the problem is reformulated to take care of location constraints whereby the placement of BSs in a subset of the deployment area is not permitted due to, e.g., private property limitations or electromagnetic radiation constraints. Experimental results and optimal tradeoff curves are presented and analyzed for various scenarios. The publish subscribe (pub sub for short) paradigm is used to deliver events from a source to interested clients in an asynchronous way. Recently, extending a pub sub system in wireless networks has become a promising topic. However, most existing works focus on pub sub systems in infrastructured wireless networks. To adapt pub sub systems to mobile ad hoc networks, we propose DRIP, a dynamic Voronoi region-based pub sub protocol. In our design, the network is dynamically divided into several Voronoi regions after choosing proper nodes as broker nodes. Each broker node is used to collect subscriptions and detected events, as well as efficiently notify subscribers with matched events in its Voronoi region. Other nodes join their nearest broker nodes to submit subscriptions, publish events, and wait for notifications of their requested events. Broker nodes cooperate with each other for sharing subscriptions and useful events. Our proposal includes two major components: a Voronoi regions construction protocol, and a delivery mechanism that implements the pub sub paradigm. The effectiveness of DRIP is demonstrated through comprehensive simulation studies. Enterprise applications are increasingly being built using type-safe programming platforms and deployed over horizontally scalable systems. Horizontal scalability depends crucially on the ability to monitor resource usage and to define and enforce resource management policies capable of guaranteeing a desired service level. However, current safe language platforms have very limited support for resource management, and their cluster-enabled versions reflect this deficiency. We describe an architecture of federated Java spl trade virtual machines. Its distinguishing feature is an integrated resource management interface that addresses the above issues. It offers programmatic control over monitoring and controlling the allocation of resources to applications and their components. The scope of each policy can span multiple nodes, realizing finegrained control. New resource types can be defined and integrated into the framework. Remote management of local resources and the notion of cluster-global resources form a powerful combination capable of expressing policies that achieve effective performance isolation for cluster applications.