Heterogeneous parallel computing combines various processing elements with different characteristics that share a single memory system. Normally multiple cores (like the 'multicores' in some smart phones or personal computers) are combined with graphic cards and other components to process large quantities of data.
"We hope to help transform code so that it can be run in heterogeneous parallel platforms with multiple graphic cards and reconfigurable hardware," explains the project's coordinator, José Daniel García, an associate professor in UC3M's Computer Science department. "We've made significant improvements in both performance and energy efficiency, comparable to those that can be made with a manual development process; the difference is that with a manual development process, we need months of engineering, while with our semiautomatic process we can do the same tasks in a few days."
Heterogeneous parallel computing combines various processing elements with different characteristics that share a single memory system. Normally multiple cores (like the 'multicores' in some smart phones or personal computers) are combined with graphic cards and other components to process large quantities of data.
"We hope to help transform code so that it can be run in heterogeneous parallel platforms with multiple graphic cards and reconfigurable hardware," explains the project's coordinator, José Daniel García, an associate professor in UC3M's Computer Science department. "We've made significant improvements in both performance and energy efficiency, comparable to those that can be made with a manual development process; the difference is that with a manual development process, we need months of engineering, while with our semiautomatic process we can do the same tasks in a few days."
These computation tasks can be applied to a variety of sectors, such as health (protein docking prediction), transportation (monitoring of railways systems), robotics (stereoscopic vision and navigation), and industry (analysis of defects in parts manufacturing).
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Image: Argonne's High-Performance Computing Research Center installed an SP1, the world's largest parallel processing supercomputer, in 1993.
Credits: Argonne National Laboratory
