Accurate Performance Bounds Calculation for Dynamic Voltage-Freq Islands in Best Effort NoCs

2018 ◽  
Author(s):  
Dara Rahmati ◽  
Sobhan Masoudi ◽  
Ahmad Khonsari ◽  
Reza Sabbaghi-Nadooshan
Keyword(s):  
Performance Bounds ◽  
Best Effort ◽  
Accurate Performance ◽  
Dynamic Voltage

scholarly journals Computing Accurate Performance Bounds for Best Effort Networks-on-Chip

2013 ◽  
Vol 62 (3) ◽  
pp. 452-467 ◽  
Author(s):  
Dara Rahmati ◽  
Srinivasan Murali ◽  
Luca Benini ◽  
Federico Angiolini ◽  
Giovanni De Micheli ◽  
...  
Keyword(s):  
Performance Bounds ◽  
Best Effort ◽  
Networks On Chip ◽  
Accurate Performance ◽  
On Chip

Green Cloud Computing with Efficient Resource Allocation Approach

2015 ◽  
pp. 116-148 ◽  
Author(s):  
Fei Cao ◽  
Michelle M. Zhu ◽  
Chase Q. Wu
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Performance Metrics ◽  
Scheduling Algorithm ◽  
Scientific Workflow ◽  
Performance Bounds ◽  
Energy Aware ◽  
Efficient Resource ◽  
Dynamic Voltage

Due to the increasing deployment of data centers around the globe escalated by the higher electricity price, the energy cost on running the computing, communication and cooling together with the amount of CO2 emissions have skyrocketed. In order to maintain sustainable Cloud computing facing with ever-increasing problem complexity and big data size in the next decades, this chapter presents vision and challenges for energy-aware management of Cloud computing environments. We design and develop energy-aware scientific workflow scheduling algorithm to minimize energy consumption and CO2 emission while still satisfying certain Quality of Service (QoS). Furthermore, we also apply Dynamic Voltage and Frequency Scaling (DVFS) and DNS scheme to further reduce energy consumption within acceptable performance bounds. The effectiveness of our algorithm is evaluated under various performance metrics and experimental scenarios using software adapted from open source CloudSim simulator.

Antibody Screening Results for Anti-Nucleocapsid Antibodies Towards the Development of a SARS-CoV-2 Nucleocapsid Protein Antigen Detecting Lateral Flow Assay

2021 ◽  
Author(s):  
David Cate ◽  
Helen Hsieh ◽  
Veronika Glukhova ◽  
Joshua D Bishop ◽  
H Gleda Hermansky ◽  
...  
Keyword(s):  
Nucleocapsid Protein ◽  
Point Of Care ◽  
Lateral Flow ◽  
Screening Methods ◽  
Antibody Screening ◽  
Liquid Handling ◽  
Large Numbers ◽  
Accurate Performance ◽  
Further Development ◽  
Assay Conditions

<p></p><p>The global COVID-19 pandemic has created an urgent demand for large numbers of inexpensive, accurate, rapid, point-of-care diagnostic tests. Analyte-based assays are suitably inexpensive and can be rapidly mass-produced, but for sufficiently accurate performance they require highly optimized antibodies and assay conditions. We used an automated liquid handling system, customized to handle arrays of lateral flow immunoassay (LFA) tests in a high-throughput screen, to identify anti-nucleocapsid antibodies that will perform optimally in an LFA. We tested 1021 anti-nucleocapsid antibody pairs as LFA capture and detection reagents with the goal of highlighting pairs that have the greatest affinity for unique epitopes of the nucleocapsid protein of SARS-CoV-2 within the LFA format. In contrast to traditional antibody screening methods (e.g., ELISA, bio-layer interferometry), the method described here integrates real-time reaction kinetics with transport in, and immobilization directly onto, nitrocellulose. We have identified several candidate antibody pairs that are suitable for further development of an LFA for SARS-CoV-2.</p><p></p>

Sign in / Sign up

Export Citation Format

Share Document