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This paper proposes the design and implementation of an impedance meter in the UHF band using reflectometry techniques. The device has the ability to measure the amplitude ratio and the phase difference of the reflected signal of a system under test with respect to an input signal. The main novelty in the proposed setup is the arrangement of commercial detectors, combining RF techniques with signal processing, in order to perform signed phase measurements when the detectors themselves do not have that capability. The acquired values are processed in a computer to obtain the impedance of the system under test., En este trabajo se propone el diseño el implementación de un medidor de impedancia en la banda UHF mediante técnicas de reflectometría. El dispositivo posee la capacidad de medir la relación de amplitud y la diferencia de fase de la señal reflejada de un sistema bajo prueba con respecto a una señal incidente. La principal novedad propuesta es utilizar un detector comercial y, mediante un arreglo circuital implementado mediante técnicas de diseño en radiofrecuencias y procesamiento de señales, adecuarlo para que pueda medir en el rango completo de fase, distinguiendo el signo. Los valores adquiridos son procesados en una computadora para obtener la impedancia del sistema bajo prueba.

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., Peer Reviewed, Postprint (published version)