The fusion of high-performance computing (HPC) and high-performance data (HPD) could potentially result in the generation of robust systems that are at least one order of magnitude faster than anything the HPC community currently uses for certain applications, says San Diego Supercomputer Center (SDSC) interim director Michael Norman. Last November, SDSC announced plans to construct Gordon, a data-intensive supercomputer that is expected to read latency-bound files at 10 times the speed and efficiency of current HPC systems with the help of flash memory solid state drives. Ultimately, Gordon will possess 245 teraflops of total compute power, 64 TB of digital random access memory, and 256 TB of flash memory. Gordon also will assist in the integration of HPC and HPD because it is designed for data-intensive predictive science as well as data-mining applications.
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University of Bath scientists have developed a biometric system for identifying people based on their nose shape. The researchers used a photographic system called PhotoFace to scan the three-dimensional shape of volunteers’ noses and used software to analyze them according to six main nose shapes. The researchers focused on the ridge profile, the nose tip, and the section between the eyes at the top of the nose. The researchers say their system offers a good recognition rate and a faster rate of image processing than whole face recognition techniques. “The technique is able to achieve a level of detail that is beyond current competing technologies and can be extended to a myriad of other applications, ranging from industrial surface inspection to cosmetics,” says University of West England professor Melvyn Smith. The researchers plan to build a larger database of noses to test the software to see if it can identify individuals from a bigger group of people or from blood relatives.
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