Next Monday (3:00pm, May 13), Fabrizio Petrini will visit and give a presentation on Streaming Applications on the Cell B.E. Processor. Here’s the abstract:

“We increasingly need to process large and complex data volumes to enable near-real-time informed human decisions or automated response actions. Current limitations in I/O and processing capabilities hinder the timely acquisition, processing, and presentation information to decision makers for rapid response. Multi-core processors, such as the Cell B.E. processor, provide an unprecedented computational capability to curb this data deluge. In this talk I will describe the challenge in designing new data streaming algorithms for multi-core processors and and present some recent results obtained with the Cell B.E. processor.”

David Chapman will defend his MS thesis, A General Algorithm for Gridding Earth Sensing Scanning Instruments, at 10:00am Monday May 5 in room 325 ITE. The abstract is below.

Gridding in remote sensing must re-project observations from their original coordinate system based on satellite orbit and attitude to a grid defined by Earth coordinates. Primitive methods assume that observations are located at points on Earth and typically average observations in grid cells, or interpolate geolocated observations. These approaches are inaccurate, because they do not make use of the instrument’s footprint geometry, and spatial response. Observation Coverage (Obscov) gridding techniques make use of the satellite optics and geometry to more accurately describe coverage of a footprint on within each grid cell. Obscov gridding provides significant accuracy improvements exceeding 1 Kelvin Brightness Temperature over most regions on Earth for a 12 micron window channel on-board the Atmospheric Infrared Sounder (AIRS). Existing Obscov algorithms are only applicable to specific instruments and depend heavily on implicitly defined spatial response functions. We make use of raycasting and adaptive grid numerical integration to compute Obscov for the spatial response function of any instrument while processing streaming satellite observation data faster than 400 Megabits/second on a 6 machine cluster. We discuss the quality benefits of our algorithm by analyzing the results of gridded AIRS infrared sensor data with 324 operational spectral channels. We also address parallel processing issues to integrate AIRS Obscov gridding with SOAR, an on demand climate processing system built on a 122 processor blade server.

Sandia and Oak Ridge national laboratories have established the Institute for Advanced Architectures to work toward computers that are a million times faster than todays supercomputers.

“An exaflop is a thousand times faster than a petaflop, itself a thousand times faster than a teraflop. Teraflop computers —the first was developed 10 years ago at Sandia — currently are the state of the art. They do trillions of calculations a second. Exaflop computers would perform a million trillion calculations per second.” (link)

Initial funding of $7.4M is provided by congressional mandate from the National Nuclear Security Administration and the Department of Energy’s Office of Science.