An Area Efficient Wide Range On-Chip Delay Measurement Architecture

Energy of computing is a serious environmental concern and mitigating it is an important technological challenge. Accurate measurement of energy consumption during an application execution is key to application-level energy minimization techniques. There are three popular approaches to providing it: (a) System-level physical measurements using external power meters; (b) Measurements using on-chip power sensors and (c) Energy predictive models. In this work, we present a comprehensive study comparing the accuracy of state-of-the-art on-chip power sensors and energy predictive models against system-level physical measurements using external power meters, which we consider to be the ground truth. We show that the average error of the dynamic energy profiles obtained using on-chip power sensors can be as high as 73% and the maximum reaches 300% for two scientific applications, matrix-matrix multiplication and 2D fast Fourier transform for a wide range of problem sizes. The applications are executed on three modern Intel multicore CPUs, two Nvidia GPUs and an Intel Xeon Phi accelerator. The average error of the energy predictive models employing performance monitoring counters (PMCs) as predictor variables can be as high as 32% and the maximum reaches 100% for a diverse set of seventeen benchmarks executed on two Intel multicore CPUs (one Haswell and the other Skylake). We also demonstrate that using inaccurate energy measurements provided by on-chip sensors for dynamic energy optimization can result in significant energy losses up to 84%. We show that, owing to the nature of the deviations of the energy measurements provided by on-chip sensors from the ground truth, calibration can not improve the accuracy of the on-chip sensors to an extent that can allow them to be used in optimization of applications for dynamic energy. Finally, we present the lessons learned, our recommendations for the use of on-chip sensors and energy predictive models and future directions.

Download Full-text

Bioprinting for Liver Transplantation

Bioengineering ◽

10.3390/bioengineering6040095 ◽

2019 ◽

Vol 6 (4) ◽

pp. 95 ◽

Cited By ~ 4

Author(s):

Christina Kryou ◽

Valentina Leva ◽

Marianneza Chatzipetrou ◽

Ioanna Zergioti

Keyword(s):

Direct Writing ◽

Liver Tissue Engineering ◽

Liver Model ◽

Cell Structures ◽

Wide Range ◽

Ink Jet ◽

Functional Complex ◽

On Chip ◽

2D And 3D

Bioprinting techniques can be used for the in vitro fabrication of functional complex bio-structures. Thus, extensive research is being carried on the use of various techniques for the development of 3D cellular structures. This article focuses on direct writing techniques commonly used for the fabrication of cell structures. Three different types of bioprinting techniques are depicted: Laser-based bioprinting, ink-jet bioprinting and extrusion bioprinting. Further on, a special reference is made to the use of the bioprinting techniques for the fabrication of 2D and 3D liver model structures and liver on chip platforms. The field of liver tissue engineering has been rapidly developed, and a wide range of materials can be used for building novel functional liver structures. The focus on liver is due to its importance as one of the most critical organs on which to test new pharmaceuticals, as it is involved in many metabolic and detoxification processes, and the toxicity of the liver is often the cause of drug rejection.

Download Full-text