Adaptive Resource-Centric Computing (ARCC) enables a simultaneous mix of high-throughput parallel, real-time, and interactive applications through automatic discovery of the correct mix of resource assignments necessary to achieve application requirements. This approach, embodied in the Tessellation manycore operating system, distributes resources to QoS domains called cells. Tessellation separates global decisions about the allocation of resources to cells from application-specific scheduling of resources within cells. We examine the implementation of ARCC in the Tessellation OS, highlight Tessellation's ability to provide predictable performance, and investigate the performance of Tessellation services within cells.

This research is supported by Microsoft (Award #024263), Intel (Award #024894), matching U.C. Discovery funding (Award #DIG07-102270), and DOE ASCR FastOS Grant #DE-FG02-08ER25849. Additional support comes from Par Lab aliates National Instruments, Nokia, NVIDIA, Oracle, and Samsung. No part of this paper repre- sents views and opinions of the sponsors mentioned above. We thank other Par Lab members for their collaboration and feedback. J. A. Colmenares participated in this work while he was a post-doctoral scholar at UC Berkeley. M. Moreto is supported by a MEC/Fulbright Fellowship.

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