Spatial object association, also referred to as crossmatch of spatial datasets, is the problem of identifying and comparing objects in two or more datasets based on their positions in a common spatial coordinate system. In this work, we evaluate two crossmatch algorithms that are used for astronomical sky surveys, on the following database system architecture configurations: (1) Netezza Performance Serverreg, a parallel database system with active disk style processing capabilities, (2) MySQL Cluster, a high-throughput network database system, and (3) a hybrid configuration consisting of a collection of independent database system instances with data replication support. Our evaluation provides insights about how architectural characteristics of these systems affect the performance of the spatial crossmatch algorithms. We conducted our study using real use-case scenarios borrowed from a large-scale astronomy application known as the large synoptic survey telescope (LSST).

Abstract A major challenge facing software libraries for scientific computing is the ability to provide adequate flexibility to meet sophisticated, diverse, and evolving application requirements. Object‐oriented design techniques are valuable tools for capturing characteristics of complex applications in a software architecture. In this paper, we describe certain prominent object‐oriented features of the SAMRAI software library that have proven to be useful in application development. SAMRAI is used in a variety of applications and has demonstrated a substantial amount of code and design re‐use in those applications. This flexibility and extensibility is illustrated with three different application codes. We emphasize two important features of our design. First, we describe the composition of complex numerical algorithms from smaller components which are usable in different applications. Second, we discuss the extension of existing framework components to satisfy new application needs. Published in 2002 by John Wiley & Sons, Ltd.

This paper discusses the design and performance of the parallel data communication infrastructure in SAMRAI, a software framework for structured adaptive mesh refinement (SAMR) multi-physics applications. We describe requirements of such applications and how SAMRAI abstractions manage complex data communication operations found in them. Parallel performance is characterized for two adaptive problems solving hyperbolic conservation laws on up to 512 processors of the IBM ASCI Blue Pacific system. Results reveal good scaling for numerical and data communication operations but poorer scaling in adaptive meshing and communication schedule construction phases of the calculations. We analyze the costs of these different operations, addressing key concerns for scaling SAMR computations to large numbers of processors, and discuss potential changes to improve our current implementation.

Describes work in progress to develop a standard for interoperability among high-performance scientific components. This research stems from the growing recognition that the scientific community needs to better manage the complexity of multidisciplinary simulations and better address scalable performance issues on parallel and distributed architectures. The driving force for this is the need for fast connections among components that perform numerically intensive work and for parallel collective interactions among components that use multiple processes or threads. This paper focuses on the areas we believe are most crucial in this context, namely an interface definition language that supports scientific abstractions for specifying component interfaces and a port connection model for specifying component interactions.

Structured adaptive mesh algorithms dynamically allocate computational resources to accurately resolve interesting portions of a numerical calculation. Such methods are difficult to implement and parallelize because they rely on dynamic, irregular data structures. We have developed an efficient, portable, parallel software infrastructure for adaptive mesh methods; our software provides computational scientists with high-level facilities that hide low-level details of parallelism and resource management. We have applied our software infrastructure to the solution of adaptive eigenvalue problems arising in materials design. We describe our software infrastructure and analyze its performance. We also present computational results which indicate that the uniformity restrictions imposed by a data parallel Fortran implementation of a structured adaptive mesh application would significantly impact performance. 1 Introduction The accurate solution of many problems in science and engineering ...