Feature Story | 20-Dec-2005

Innovative tools for high-performance computing

DOE/Pacific Northwest National Laboratory



Solving complex scientific problems requires not only advanced high-performance supercomputers but also innovative software programs that can discover patterns and integrate data across different space and time scales. Researchers at PNNL are creating innovative software and processes to do just that. Among them are:

Global Arrays Toolkit (GA Toolkit)--provides an efficient and portable "shared memory" programming interface for distributed-memory computers.

NWChem--a computational chemistry package that runs large chemistry problems efficiently and is used by thousands of people worldwide. NWChem was developed using the GA Toolkit and is designed to run on high-performance parallel supercomputers as well as conventional workstation clusters. It aims to be scalable in its ability to treat large problems efficiently and in its usage of available parallel computing resources.

ScalaBLAST--a program that processes genomic sequences in minutes rather than weeks. Genomes often contain millions of sequences, making them "data-intensive." ScalaBLAST was also developed using the GA Toolkit. ScalaBLAST scales well on both shared and distributed memory machines while scheduling queries across available process groups and sharing the target database across available memory. With ScalaBLAST, researchers can perform a whole proteome analysis on the human genome in 50 hours.

Fuel cell modeling--a process used to model fuel cell materials and fuel cell systems to better understand the fluid, thermal, electrochemical and structural response of fuel cells and determine how they would perform before they're actually built. Researchers have developed electrochemistry codes, for example, that allow modeling of the steady-state response of solid oxide fuel cell (SOFC) stacks. SOFCs offer attractive benefits for energy production because of their high-power density and fuel flexibility. Electrochemistry modeling is key to predicting the behavior of the cell (including performance, fuel use, thermal and flow characteristics).

###

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.