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The advent of experimental science facilities-instruments and observatories,such as the Large Hadron Collider, the Laser Interferometer Gravitational WaveObservatory, and the upcoming Large Synoptic Survey Telescope-has brought aboutchallenging, large-scale computational and data processing requirements.Traditionally, the computing infrastructure to support these facility'srequirements were organized into separate infrastructure that supported theirhigh-throughput needs and those that supported their high-performance computingneeds. We argue that to enable and accelerate scientific discovery at the scaleand sophistication that is now needed, this separation between high-performancecomputing and high-throughput computing must be bridged and an integrated,unified infrastructure provided. In this paper, we discuss several case studieswhere such infrastructure has been implemented. These case studies spandifferent science domains, software systems, and application requirements aswell as levels of sustainability. A further aim of this paper is to provide abasis to determine the common characteristics and requirements of suchinfrastructure, as well as to begin a discussion of how best to support thecomputing requirements of existing and future experimental science facilities.

Supporting High-Performance and High-Throughput Computing for Experimental Science