29157947
Massively parallel computation of conservation laws
Abstract We present a new method for computing solutions of conservation laws based on the use of cellular automata with the method of characteristics. The method exploits the high degree of parallelism available with cellular automata and retains important features of the method of characteristics. It yields high numerical accuracy and extends naturally to adaptive meshes and domain decomposition methods for perturbed conservation laws. We describe the method and its implementation for a Dirichlet problem with a single conservation law for the one-dimensional case. Numerical results for the one-dimensional law with the classical Burgers nonlinearity or the Buckley-Leverett equation show good numerical accuracy outside the neighborhood of the shocks. The error in the area of the shocks is of the order of the mesh size. The algorithm is well suited for execution on both massively parallel computers and vector machines. We present timing results for an Alliant FX/8, Connection Machine Model 2, and CRAY X-MP.
9657478
Computational Electromagnetics and Parallel Dense Matrix Computations
We present computational results using CORAL, a parallel, three-dimensional, nonlinear magnetostatic code based on a volume integral equation formulation. A key feature of CORAL is the ability to solve, in parallel, the large, dense systems of linear equations that are inherent in the use of integral equation methods. Using the Chameleon and PSLES libraries ensures portability and access to the latest linear algebra solution technology.
139273
Applications-driven parallel I/O
The authors investigate the needs of some massively parallel applications running on distributed-memory parallel computers at Argonne National Laboratory and identify some common parallel I/O operations. For these operations, routines were developed that hide the details of the actual implementation (such as the number of parallel disks) from the application, while providing good performance. An important feature is the ability for the application programmer to specify that a file be accessed either as a high-performance parallel file or as a conventional Unix file, simply by changing the value of a parameter on the file open call. These routines are examples of a parallel I/O abstraction that can enhance development, portability, and performance of I/O operations in applications. Some of the specific issues in their design and implementation in a distributed-memory toolset are discussed.
37714806
Parallel Solution of the Three-Dimensional, Time-Dependent Ginzburg-Landau Equation
The recent discovery of superconductivity in a class of copper-oxide compounds (the cuprate superconductors) at liquid nitrogen temperatures has generated a renewed interest in the magnetic properties of type-II superconductors. In our work, we are investigating these properties using the phenomenological time- dependent Ginzburg-Landau equation. This paper describes the parallelization of this equation.
16053840
Parallel computation of three-dimensional nonlinear magnetostatic problems
We describe a general-purpose parallel electromagnetic code for computing accurate solutions to large computationally demanding, 3D, nonlinear magnetostatic problems. The code, CORAL, is based on a volume integral equation formulation. Using an IBM SP parallel computer and iterative solution methods, we successfully solved the dense linear systems inherent in such formulations. A key component of our work was the use of the PETSc library, which provides parallel portability and access to the latest linear algebra solution technology.
6061688
Mobile Agent Connection Establishment and Management (CEMA)—Message Exchange for Pervasive Computing Environments
Pervasive computing is an emerging technology that offers new possibilities to distributed computing and computer networking; it employs a wide variety of smart, ubiquitous devices throughout an individual's working and living environment. Mobile agents are software entities that can migrate between servers (mobile agent environments) of the network accomplishing various tasks on the behalf of their owners. The objective of this paper is to describe a test and prototyping environment for experimenting with mobile agents in pervasive environments. A prototype environment for a novel, proactive infrastructure is described for mobile agent assisted pervasive computing. In addition, a new message passing algorithm is provided for mobile agent connection establishment and management (CEMA). Simulation results show the performance of the proposed approach.
38463254
Locating and Ranking XML Documents Based on Content and Structure Synopses
We present a new framework for indexing, locating and ranking XML documents based on content and structural synopses extracted from the documents. Instead of indexing each single element or term in a document, we extract a structural summary and a small number of data synopses from the document, which are indexed in an efficient way suitable for query evaluation. Our query language is XPath extended with full-text search. The result of query evaluation is a ranked list of document locations that best match the query. We propose a novel aggregated ranking scheme, which is integrated into the query evaluation to score the documents based on those data synopses. Our experimental evaluation shows that our indexing scheme outperforms the standard XML indexing scheme based on inverted lists and our ranking scheme is effective in terms of precision and recall.
2370359
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
Electrical power management in large-scale IT systems such as commercial data-centers is an application area of rapidly growing interest from both an economic and ecological perspective, with billions of dollars and millions of metric tons of CO2 emissions at stake annually. Businesses want to save power without sacrificing performance. This paper presents a reinforcement learning approach to simultaneous online management of both performance and power consumption. We apply RL in a realistic laboratory testbed using a Blade cluster and dynamically varying HTTP workload running on a commercial web applications middleware platform. We embed a CPU frequency controller in the Blade servers' firmware, and we train policies for this controller using a multi-criteria reward signal depending on both application performance and CPU power consumption. Our testbed scenario posed a number of challenges to successful use of RL, including multiple disparate reward functions, limited decision sampling rates, and pathologies arising when using multiple sensor readings as state variables. We describe innovative practical solutions to these challenges, and demonstrate clear performance improvements over both hand-designed policies as well as obvious "cookbook" RL implementations.
35397691
Accomplishing More by Doing Less - Lessons from Spanish Language Instruction
20665084
Parallel performance of two applications in the Boeing high performance computing benchmark suite
Abstract We describe our work to evaluate the performance of the parallel versions of two floating-point-intensive engineering applications from Boeing's high performance computing benchmark suite (BHPCBS) on emerging RISC parallel systems and PC clusters. The first application is a computational fluid dynamics (CFD) code, OVERFLOW, developed by NASA and used by Boeing for analysis and design of advanced aircraft. The second application is a prototype of a computational electromagnetics (CEM) code, developed by Boeing and used for radar cross-section studies. The distributed memory parallel versions of both applications use the message passing interface (MPI) standard for message passing. The goal of our work was to determine whether RISC parallel systems and PC clusters, which offer high performance at low cost, may be able to meet Boeing's computing requirements in the future. We describe the test environments for the studies, discuss parallelization issues and strategies and present performance data for the two applications.