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The Tropospheric Emission Spectrometer (TES) is one of four instruments onboard the Earth Observing System Aura satellite. The TES Science Investigator-led Processing System (SIPS) Facility performs production processing of all TES science data. When the TES project was proposed in 1988, its science algorithms were still evolving, but it was already understood to be at least two orders of magnitude more complex than its NASA predecessor, the Atmospheric Trace Molecule Spectroscopy (ATMOS) instrument. In addition, the expected data volume of the TES instrument would be more than 1000 times greater than that of ATMOS. Development of the TES SIPS faced a number of technical challenges. It also would have been impractical and prohibitively costly to develop the TES SIPS facility without carefully deploying the computing technologies that have recently become available. This paper describes how the challenges were met in the development of the facility by making use of evolving hardware technology and software refinement. The process revealed that the architecture of the hardware implemented was highly dependent upon the processing algorithm, and a stable algorithm was needed early in the hardware development process for performance analysis and benchmarking. [ABSTRACT FROM AUTHOR]

The Event Filter (EF) selection stage is a fundamental component of the ATLAS Trigger and Data Acquisition architecture. Its primary function is the reduction of data flow and rate to values acceptable by the mass storage operations and by the subsequent offline data reconstruction and analysis steps. The computing instrument of the EF is organized as a set of independent subfarms, each connected to one output of the Event Builder (EB) switch fabric. Each subfarm comprises a number of processors analyzing several complete events in parallel. This paper describes the design of the ATLAS EF system, its deployment in the 2004 ATLAS combined test beam together with some examples of integrating selection and monitoring algorithms. Since the processing algorithms are not explicitly designed for EF but are adapted from the offline ones, special emphasis is reserved to system reliability and data security, in particular for the case of failures in the processing algorithms. Other key design elements have been system modularity and scalability. The EF shall be able to follow technology evolution and should allow for using additional processing resources possibly remotely located [ABSTRACT FROM PUBLISHER]