Multi-unit global energy management and optimization for network-on-chip applications

The problem of energy optimization in multi-core systems (such as single-chip multiprocessors) where the individual energy demands of various processing elements are governed by instantaneous workload requirements is well defined in literature. The significance of the problem is underlined by the increasing prominence of multi-core systems that must operate under strict power/energy budget constraints, both in mobile applications and in cases where special cooling arrangements can be very expensive. A range of solutions have been proposed over the last few years, which are mostly based on static, off-line calculation of a limited set of operating points in the form of optimum voltage and frequency assignments, that are subsequently chosen according to actual demands. Still, to our best knowledge, none of these studies have demonstrated an on-line solution to complex, multi-variable energy optimization problem which allows dynamic adjustment of individual operating frequencies and supply voltages of multiple processing elements. This thesis presents the design and silicon implementation of an analog-based energy optimizer unit, which is capable of dynamically adjusting power supply and clock frequencies of multiple embedded cores, tailored to the instantaneous workload information (computational task) and fully adaptive to variations in process and temperature. Our approach borrows from the basic principles of analog computation to continuously optimize the system-wide energy dissipation of multiple processing elements, converging on the global minima of the constrained optimization problem which are represented as stable operating points of a simple feedback loop. It is already well known that stable, approximate solutions of multi-variable optimization problems (such as gradient descent) can be obtained by using very compact analog circuits, e.g. resistive networks. The analogy between the energy minimization problem under timing constraints in a general task graph and the power minimization problem under Kirchhoff's current law constraints in an equivalent resistive network is exploited. The implementation of the on-line analog optimizer is then discussed. The realization of the blocks composing the system architecture is described, and circuit design issues are studied thoroughly. The three-loop demonstrator circuit of the proposed analog optimizer architecture has been implemented using a 0.18μm standard digital CMOS process. The overall circuit area of the optimizer is (245μm × 650μm) excluding decoupling capacitors, while each loop circuit occupies only (180μm × 120μm). Operating at a nominal supply of 1.8 V, the circuit is capable of supporting the desired frequency range of 170 MHz - 290 MHz, as well as the voltage range of 1.2 V - 1.8 V. Estimated workload levels for each task (loop) are provided as 4-bit binary inputs, and the corresponding solution for minimum energy consumption is observed as assigned supply voltages and operating frequencies for each processing element, for a certain task duration. The measured worst-case settling time for supply voltages is less than 50μs. The average power consumption of the entire three-loop optimizer is 4mW. Measurements experimentally validate the concept of fully analog, current-based solution to implement on-line energy minimization in complex multi-core systems under varying workload conditions. Key functional blocks of the proposed circuit operate in weak inversion, resulting in very low power dissipation for the optimizer. The prototype successfully demonstrates that the proposed optimizer block is also capable of taking into account the on-chip variations of temperature as well as process parameters. As such, it can be used as a generic building block for on-line energy optimization in complex systems

Elazığ Cezaevi tarihçesi ve 1970-2000 yıllarında diğer cezaevleri ile kıyası

Ankara : İhsan Doğramacı Bilkent Üniversitesi İktisadi, İdari ve Sosyal Bilimler Fakültesi, Tarih Bölümü, 2016.This work is a student project of the The Department of History, Faculty of Economics, Administrative and Social Sciences, İhsan Doğramacı Bilkent University.by Özer, Abdürrahim

Evaluating Resistance of MCML Technology to Power Analysis attacks using a Simulation-based Methodology

Abstract. This paper explores the resistance of MOS Current Mode Logic (MCML) against attacks based on the observation of the power consumption. Circuits implemented in MCML, in fact, have unique characteristics both in terms of power consumption and the dependency of the power profile from the input signal pattern. Therefore, MCML is suitable to protect cryptographic hardware from Differential Power Analysis and similar side-channel attacks. In order to demonstrate the effectiveness of different logic styles against power analysis attacks, two full cores implementing the AES algorithm were realized and implemented with CMOS and MCML technology, and a set of different types of attack was performed using power traces derived from SPICE-level simulations. Although all keys were discovered for CMOS, MCML traces did not presents characteristic that can lead to a successful attack.

COVID-19: vaccination vs. hospitalization

Objective Vaccination is the most efficient way to control the coronavirus disease 2019 (COVID-19) pandemic, but vaccination rates remain below the target level in most countries. This multicenter study aimed to evaluate the vaccination status of hospitalized patients and compare two different booster vaccine protocols. Setting Inoculation in Turkey began in mid-January 2021. Sinovac was the only available vaccine until April 2021, when BioNTech was added. At the beginning of July 2021, the government offered a third booster dose to healthcare workers and people aged > 50 years who had received the two doses of Sinovac. Of the participants who received a booster, most chose BioNTech as the third dose. Methods We collected data from 25 hospitals in 16 cities. Patients hospitalized between August 1 and 10, 2021, were included and categorized into eight groups according to their vaccination status. Results We identified 1401 patients, of which 529 (37.7%) were admitted to intensive care units. Nearly half (47.8%) of the patients were not vaccinated, and those with two doses of Sinovac formed the second largest group (32.9%). Hospitalizations were lower in the group which received 2 doses of Sinovac and a booster dose of BioNTech than in the group which received 3 doses of Sinovac. Conclusion Effective vaccinations decreased COVID-19-related hospitalizations. The efficacy after two doses of Sinovac may decrease over time; however, it may be enhanced by adding a booster dose. Moreover, unvaccinated patients may be persuaded to undergo vaccination

Lung cancer from suspicion to treatment: An indicator of healthcare access in Turkey

Background: Lung cancer is the leading cause of cancer-related deaths worldwide. Before beginning lung cancer treatment, it is necessary to complete procedures such as suspecting lung cancer, obtaining a pathologic diagnosis, and staging. This study aimed to investigate the processes from suspicion of lung cancer to diagnosis, staging, and treatment initiation. Methods: The study was designed as a multicenter and cross-sectional study. Patients with lung cancer from various health institutions located in all geographic regions of Turkey were included in the study. The sociodemographic and clinical characteristics of the patients, the characteristics of the health institutions and geographic regions, and other variables of the lung cancer process were recorded. The time from suspicion of lung cancer to pathologic diagnosis, radiologic staging, and treatment initiation, as well as influencing factors, were investigated. Results: The study included 1410 patients from 29 different medical centers. The mean time from the initial suspicion of lung cancer to the pathologic diagnosis was 48.0 ± 52.6 days, 39.0 ± 52.7 days for radiologic staging, and 74.9 ± 65.5 days for treatment initiation. The residential areas with the most suspected lung cancer cases were highly developed socioeconomic zones. Primary healthcare services accounted for only 0.4% of patients with suspected lung cancer. The time to pathologic diagnosis was longer in the Marmara region, and the wait time for staging and treatment initiation was longer in Eastern and Southeastern Anatolia. Patients who presented to chest disease referral hospitals with peripheral lesions, those with early-stage disease, and those who were diagnosed surgically had significantly longer wait times. Conclusion: The time between pathologic diagnosis, staging, and treatment initiation in lung cancer was longer than expected. Increasing the role of primary healthcare services and distributing socioeconomic resources more equally will contribute to shortening the time to diagnosis and improve treatment processes for lung cancer