Overcoming the Scalability Challenges of Epidemic Simulations on Blue Waters

Modeling dynamical systems represents an important application class covering a wide range of disciplines including but not limited to biology, chemistry, finance, national security, and health care. Such applications typically involve large-scale, irregular graph processing, which makes them difficult to scale due to the evolutionary nature of their workload, irregular communication and load imbalance. EpiSimdemics is such an application simulating epidemic diffusion in extremely large and realistic social contact networks. It implements a graph-based system that captures dynamics among co-evolving entities. This paper presents an implementation of EpiSimdemics in Charm++ that enables future research by social, biological and computational scientists at unprecedented data and system scales. We present new methods for application-specific processing of graph data and demonstrate the effectiveness of these methods on a Cray XE6, specifically NCSA's Blue Waters system.

Goal Recognition through Goal Graph Analysis

We present a novel approach to goal recognition based on a two-stage paradigm of graph construction and analysis. First, a graph structure called a Goal Graph is constructed to represent the observed actions, the state of the world, and the achieved goals as well as various connections between these nodes at consecutive time steps. Then, the Goal Graph is analysed at each time step to recognise those partially or fully achieved goals that are consistent with the actions observed so far. The Goal Graph analysis also reveals valid plans for the recognised goals or part of these goals. Our approach to goal recognition does not need a plan library. It does not suffer from the problems in the acquisition and hand-coding of large plan libraries, neither does it have the problems in searching the plan space of exponential size. We describe two algorithms for Goal Graph construction and analysis in this paradigm. These algorithms are both provably sound, polynomial-time, and polynomial-space. The number of goals recognised by our algorithms is usually very small after a sequence of observed actions has been processed. Thus the sequence of observed actions is well explained by the recognised goals with little ambiguity. We have evaluated these algorithms in the UNIX domain, in which excellent performance has been achieved in terms of accuracy, efficiency, and scalability.

Using CORBA's advanced services to enhance the integrity of QoS management programmable networks

The development of wideband network services and the new network infrastructures to support them have placed much more requirements on current network management systems. Issues such as scalability, integrity and interoperability have become more important. Existing management systems are not flexible enough to support the provision of Quality of Service (QoS) in these dynamic environments. The concept of Programmable Networks has been proposed to address these requirements. Within this framework, CORBA is regarded as a middleware technology that can enable interoperation among the distributed entities founds in Programmable Networks. By using the basic CORBA environment in a heterogeneous network environment, a network manager is able to control remote Network Elements (NEs) in the same way it controls its local resources. Using this approach both the flexibility and intelligence of the overall network management can be improved. This paper proposes the use of two advanced features of CORBA to enhance the QoS management in a Programmable Network environment. The Transaction Service can be used to manage a set of tasks, whenever the management of elements in a network is correlated; and the Concurrency Service can be used to coordinate multiple accesses on the same network resources. It is also shown in this paper that proper use of CORBA can largely reduce the development and administration of network management applications.

Uniplanar left-handed artificial metamaterials

Planar periodic arrays of metallic elements printed on grounded dielectric substrates are presented to exhibit left-handed properties for surface wave propagation. The proposed structures dispense with the need for grounding vias and ease the implementation of uniplanar left-handed metamaterials at higher frequencies. A transmission line description is used for the initial design and interpretation of the left-handed property. A thorough study based on full wave simulations is carried out with regards to the effect of the element geometrical characteristics and the array periodicity to the properties of the artificial material. Dispersion curves are presented and studied. The distribution of the modal fields in the unit cell is also studied in order to provide an explanation of the material properties. The scalability of the proposed structures to infrared frequencies is demonstrated.

Joined Spectral Trees for Scalable SPIHT-Based Multispectral Image Compression

In this paper, the compression of multispectral images is addressed. Such 3-D data are characterized by a high correlation across the spectral components. The efficiency of the state-of-the-art wavelet-based coder 3-D SPIHT is considered. Although the 3-D SPIHT algorithm provides the obvious way to process a multispectral image as a volumetric block and, consequently, maintain the attractive properties exhibited in 2-D (excellent performance, low complexity, and embeddedness of the bit-stream), its 3-D trees structure is shown to be not adequately suited for 3-D wavelet transformed (DWT) multispectral images. The fact that each parent has eight children in the 3-D structure considerably increases the list of insignificant sets (LIS) and the list of insignificant pixels (LIP) since the partitioning of any set produces eight subsets which will be processed similarly during the sorting pass. Thus, a significant portion from the overall bit-budget is wastedly spent to sort insignificant information. Through an investigation based on results analysis, we demonstrate that a straightforward 2-D SPIHT technique, when suitably adjusted to maintain the rate scalability and carried out in the 3-D DWT domain, overcomes this weakness. In addition, a new SPIHT-based scalable multispectral image compression algorithm is used in the initial iterations to exploit the redundancies within each group of two consecutive spectral bands. Numerical experiments on a number of multispectral images have shown that the proposed scheme provides significant improvements over related works.

Attosecond phase locking of harmonics emitted from laser-produced plasmas

Laser-driven coherent extreme-ultraviolet (XUV) sources provide pulses lasting a few hundred attoseconds(1,2), enabling real-time access to dynamic changes of the electronic structure of matter(3,4), the fastest processes outside the atomic nucleus. These pulses, however, are typically rather weak. Exploiting the ultrahigh brilliance of accelerator-based XUV sources(5) and the unique time structure of their laser-based counterparts would open intriguing opportunities in ultrafast X-ray and high-field science, extending powerful nonlinear optical and pump-probe techniques towards X-ray frequencies, and paving the way towards unequalled radiation intensities. Relativistic laser-plasma interactions have been identified as a promising approach to achieve this goal(6-13). Recent experiments confirmed that relativistically driven overdense plasmas are able to convert infrared laser light into harmonic XUV radiation with unparalleled efficiency, and demonstrated the scalability of the generation technique towards hard X-rays(14-19). Here we show that the phases of the XUV harmonics emanating from the interaction processes are synchronized, and therefore enable attosecond temporal bunching. Along with the previous findings concerning energy conversion and recent advances in high-power laser technology, our experiment demonstrates the feasibility of confining unprecedented amounts of light energy to within less than one femtosecond.

Real-valued fixed-complexity sphere decoder for high dimensional QAM-MIMO systems

The development of high performance, low computational complexity detection algorithms is a key challenge for real-time Multiple-Input Multiple-Output (MIMO) communication system design. The Fixed-Complexity Sphere Decoder (FSD) algorithm is one of the most promising approaches, enabling quasi-ML decoding accuracy and high performance implementation due to its deterministic, highly parallel structure. However, it suffers from exponential growth in computational complexity as the number of MIMO transmit antennas increases, critically limiting its scalability to larger MIMO system topologies. In this paper, we present a solution to this problem by applying a novel cutting protocol to the decoding tree of a real-valued FSD algorithm. The new Real-valued Fixed-Complexity Sphere Decoder (RFSD) algorithm derived achieves similar quasi-ML decoding performance as FSD, but with an average 70% reduction in computational complexity, as we demonstrate from both theoretical and implementation perspectives for Quadrature Amplitude Modulation (QAM)-MIMO systems.

An On Demand Queue Management Architecture for a Programmable Traffic Manager

A queue manager (QM) is a core traffic management (TM) function used to provide per-flow queuing in access andmetro networks; however current designs have limited scalability. An on-demand QM (OD-QM) which is part of a new modular field-programmable gate-array (FPGA)-based TM is presented that dynamically maps active flows to the available physical resources; its scalability is derived from exploiting the observation that there are only a few hundred active flows in a high speed network. Simulations with real traffic show that it is a scalable, cost-effective approach that enhances per-flow queuing performance, thereby allowing per-flow QM without the need for extra external memory at speeds up to 10 Gbps. It utilizes 2.3%–16.3% of a Xilinx XC5VSX50t FPGA and works at 111 MHz.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

Relativistic High Harmonic Generation In Gas Jet Targets

We experimentally demonstrate a new regime of high-order harmonic generation by relativistic-irradiance lasers in gas jet targets. Bright harmonics with both odd and even orders, generated by linearly as well as circularly polarized pulses, are emitted in the forward direction, while the base harmonic frequency is downshifted. A 9 TW laser generates harmonics up to 360 eV, within the 'water window' spectral region. With a 120 TW laser producing 40 uJ/sr per harmonic at 120 eV, we demonstrate the photon number scalability. The observed harmonics cannot be explained by previously suggested scenarios. A novel high-order harmonics generation mechanism [T. Zh. Esirkepov et al., AIP Proceedings, this volume], which explains our experimental findings, is based on the phenomena inherent in the relativistic laser - underdense plasma interactions (self-focusing, cavity evacuation, and bow wave generation), mathematical catastrophe theory which explains formation of electron density singularities (cusps), and collective radiation due to nonlinear oscillations of a compact charge.

Large Scale Verification of MPI Programs Using Lamport Clocks with Lazy Update

We propose a dynamic verification approach for large-scale message passing programs to locate correctness bugs caused by unforeseen nondeterministic interactions. This approach hinges on an efficient protocol to track the causality between nondeterministic message receive operations and potentially matching send operations. We show that causality tracking protocols that rely solely on logical clocks fail to capture all nuances of MPI program behavior, including the variety of ways in which nonblocking calls can complete. Our approach is hinged on formally defining the matches-before relation underlying the MPI standard, and devising lazy update logical clock based algorithms that can correctly discover all potential outcomes of nondeterministic receives in practice. can achieve the same coverage as a vector clock based algorithm while maintaining good scalability. LLCP allows us to analyze realistic MPI programs involving a thousand MPI processes, incurring only modest overheads in terms of communication bandwidth, latency, and memory consumption. © 2011 IEEE.