Computing in Science and Engineering

A Personal Reflection

AEIC Jim Chen reflects on his involvement with CiSE magazine and why it matters as a forum for computational scientists and engineers.

Computational Science Research and Graduate Studies at San Diego State University

This installment of the News department focuses on one particular CS program and what it's doing to prepare CS students for their future careers.

Computation in Modern Physics

Norman Chonacky reviews Computation in Modern Physics.

Introducing Computing Now

One of Computing Now's editorial board members talks about this IEEE Computer Society initiative and all that it has to offer members and nonmembers alike.

Guest Editor's Introduction: Cloud Computing for the Sciences

The guest editor of this special issue on cloud computing defines the term and describes the articles highlighted.

SQL in the Clouds

In a cloud computing context, the MapReduce algorithm comprises two massively parallel operations linked by a generic sorting and data-distribution process. Although this algorithm is the workhorse in most cloud computing strategies, it's a special case of a more general dataflow. In place of the two cloud operations, the proposed method substitutes longer sequences and then lets the user direct outputs to any subsequent downstream operation. However, the method retains the job-supervisor infrastructure, which performs the necessary sorting, collating, and distributing of these outputs prior to initiating operations. To evaluate SQL database queries, particularly those with correlated subqueries, a computation identifies and aligns data elements from widely separated storage locations, suggesting cloud algorithms that exploit the supervisory sorting process to achieve the desired alignments. Exploring such algorithms reveals that a few customizable templates, assembled recursively as necessary, can handle a wide class of SQL data-mining queries.

Graph Twiddling in a MapReduce World

As the size of graphs for analysis continues to grow, methods of graph processing that scale well have become increasingly important. One way to handle large datasets is to disperse them across an array of networked computers, each of which implements simple sorting and accumulating, or MapReduce, operations. This cloud computing approach offers many attractive features. If decomposing useful graph operations in terms of MapReduce cycles is possible, it provides incentive for seriously considering cloud computing. Moreover, it offers a way to handle a large graph on a single machine that can't hold the entire graph as well as enables streaming graph processing. This article examines this possibility.

A High-Performance Computing Forecast: Partly Cloudy

Cloud computing is emerging as an important computational resource allocation trend in commercial, academic, and industrial sectors. However, for high-performance computing (HPC), extreme scalability, efficiency, reliability, and security requirements extend beyond cloud computing capabilities, at least in its current form. Clouds could serve the general data processing workload within the HPC community, some large and potentially distributed datasets, and decoupled throughput-computing tasks. Yet, the cloud concept doesn't address and can't satisfy the needs of other workflow classes requiring extreme-scale, tightly coupled capability computing, large sensitive datasets, and optimized algorithms. This article explores the relationship of clouds to this spectrum of HPC needs and predicts a partly cloudy forecast.

Scientific Scripting for the Java Platform with jLab

By modifying Groovy with Matlab-like constructs, the authors created a compiled mathematical scripting language called GroovySci for the jLab platform. The resulting code generation enhancements could ultimately extend Java's potential for scientific computing.

Getting Started with GPU Programming

This tutorial describes a step-by-step procedure for programming a Macintosh Nvidia GPU. General scientific programmers with some C knowledge can get started in parallel processing application development with relative ease.

3D Imaging and Simulation of Elastic Properties of Porous Materials

Obtaining accurate estimates of elastic properties of disordered materials has been a problem of interest for decades. Recent advances in 3D computed tomography and numerical simulations have led to a new digital approach.

A Virtual Platform for Auditory Organ Mechanics Analysis

To better understand the relationship between the sound conduction system's structure and function, the authors developed a virtual platform that integrates 3D reconstruction and finite element modeling of the peripheral auditory organ to simulate biomechanical behavior of the middle and inner ear.

Postprocessing in Automated Grading Systems, Part 2

The authors discuss a few simple grading algorithms for handling a wide array of homework and test questions that aren't otherwise handled well by the standard algorithm.

The Promises of Functional Programming

Trailblazing with Roadrunner

The authors look at the changes occurring in computer system design, the rise of heterogeneous computing, and the effects these changes have on high-performance computing.

Vets 1, Docs 1

Columnist Charles Day compares the experience of digitized medical records vs. paper versions in two recent trips—one to the vet's office for his dog, Gemma, and the other to his own doctor's office for a personal checkup.