Measurement, Modeling, and Characterization for Power-Aware Computing

Society’s increasing dependence on information technology has resulted in the deployment of vast compute resources. The energy costs of operating these resources coupled with environmental concerns have made power-aware computingone of the primary challenges for the IT sector. Making energy-efficient computing a rule rather than an exception requires that researchers and system designers use the right set of techniques and tools. These involve measuring,modeling, and characterizing the energy consumption of computers at varying degrees of granularity.In this thesis, we present techniques to measure power consumption of computer systems at various levels. We compare them for accuracy and sensitivityand discuss their effectiveness. We test Intel’s hardware power model for estimation accuracy and show that it is fairly accurate for estimating energy consumption when sampled at the temporal granularity of more than tens ofmilliseconds.We present a methodology to estimate per-core processor power consumption using performance counter and temperature-based power modeling and validate it across multiple platforms. We show our model exhibits negligible computationoverhead, and the median estimation errors ranges from 0.3% to 10.1% for applications from SPEC2006, SPEC-OMP and NAS benchmarks. We test the usefulness of the model in a meta-scheduler to enforce power constraint on a system.Finally, we perform a detailed performance and energy characterization of Intel’s Restricted Transactional Memory (RTM). We use TinySTM software transactional memory (STM) system to benchmark RTM’s performance against competing STM alternatives. We use microbenchmarks and STAMP benchmarksuite to compare RTM versus STM performance and energy behavior. We quantify the RTM hardware limitations that affect its success rate. We show that RTM performs better than TinySTM when working-set fits inside the cache and that RTM is better at handling high contention workloads

Measurement, Modeling, and Characterization for Energy-Efficient Computing

The ever-increasing ecological footprint of Information Technology (IT) sector coupled with adverse effects of high power consumption on electronic circuits has increased the significance of energy-efficient computing in the last decade. Making energy-efficient computing a norm rather than an exception requires that system designers and programmers understand the energy implications of their design and implementation choices. This necessitates a detailed view of system’s energy expenditure and/or power consumption. We explore this aspect of energy-efficient computing in this thesis through power measurement, power modeling, and energy characterization.First, we present a quantitative comparison between power measurement data collected for computer systems using four techniques: a power meter at wall outlet, currenttransducers at ATX power rails, CPU voltage regulator’s current monitor, and Intel’s proprietary RAPL (Running Average Power Limit) interface. We compare them for accuracy, sensitivity and accessibility.Second, we present two different methodologies to model processor power consumption. The first model estimates power consumption at the granularity of individualcores using per-core performance events and temperature sensors. We validate the methodology on six different platforms and show that our model estimates power consumption with high accuracy across all platforms consistently. To understand the energy expenditure trends across different frequencies and different degrees of parallelism, we need to model power at a much finer granularity. The second power model addresses this issue by estimating static and dynamic power consumption for individual cores and the uncore. We validate this model on Intel’s Haswell platform for single-threaded and multi-threaded benchmarks. We use this power model to characterize energy efficiency of frequency scaling on Haswell microarchitecture and use the insights to implementa low overhead DVFS scheduler. We also characterize the energy efficiency of thread scaling using the power model and demonstrate how different communication parametersand microarchitectural traits affect application’s energy when it scales.Finally, we perform detailed performance and energy characterization of Intel’s RestrictedTransactional Memory (RTM).We use TinySTM software transactional memory(STM) system to benchmark RTM’s performance against competing STM alternatives.We use microbenchmarks and STAMP benchmark suite to compare RTM an STM performanceand energy behavior. We quantify the RTM hardware limitations and identifyconditions required for RTM to outperform STM

Identification of causative pathogen and its antibiotic sensitivity in cases of preterm premature rupture of membranes

Background: Pre-labor rupture of membranes is defined as amniotic membrane rupture before the onset of labor contractions, and if it happens before 37 weeks, it is called preterm premature rupture of membranes (PPROM). Several organisms commonly present in the vaginal tract are E.coli, Group-B streptococci, staphylococcus aureus, chlamydia trachomatis, Gardnerella vaginalis and Enterococcus faecalis which secrete proteases that degrade collagen thereby weakening  the fetal membranes leading to PPROM. Appropriate antibiotic therapy has a significant role in the prevention and treatment of maternal and neonatal complications.Methods: This was a prospective observational study done in the department of obstetrics and gynaecology, Narayana medical college, Nellore. Selectively 100 patients with complaint of PPROM admitted to labor room were included in the study. Diagnosis of membrane rupture was established by speculum examination, and high vaginal swabs are taken and sent to laboratory for identifying bacteria using gram staining and cultured in aerobic and anaerobic methods. Antimicrobial susceptibility testing of the organisms was performed by disk diffusion method by Kirby and Bauer.Results: Out of 100, high vaginal swabs had growth in 82 patients, and 18 were sterile. The repeatedly isolated organism in patients with PPROM is E.coli amounting 32%, followed by candidal species 20%. Staphylococci are scoring 11% and enterococci 8%. However, organisms like gardenella vaginalis and Group B streptococcus are least common with a score of 6% and 5% respectively. In this study, E.coli is highly sensitive to tigecycline, colistin 100% each and highly resistant to gentamycin and amikacin.Conclusions: In this study, E.coli is related to the maximum number of cases with preterm premature rupture of membranes. Appropriate use of antibiotics significantly lowers maternal morbidity and neonatal mortality

Artificial Intelligence in Maxillofacial Radiology by Leaps and Bounds

Artificial intelligence (AI) is a branch of computer science concerned with building smart software or machines capable of performing tasks that typically require human intelligence. AI is capable of mimicking human brain. Recent advances in machine learning have produced algorithms that allow automated and accurate detection, imaging, diagnosis, as well as other specialties of dentistry, which reduces stressful work and manpower. The AI plays a major role in Dental imaging by diagnosing the conditions based on the Radiographic or optical images. AI technology in dentistry could reduce cost, time, human expertise and medical error.AI in everyday life are growing by leaps and bounds. By no means there exists a doubt in the ascendancy of integrating AI into practice

GC-312 GTRI IT Service Desk System

This overarching project would be web development, which would entail coding both the back end and the front end. The use of libraries is encouraged, but we must be cautious about licensing and ensure that this project remains as open-source as possible (a good open-source license ensures people can use, modify, redistribute, and sell without worry). This is a free and open-source project

Concurrent emergence of exotic whitefly incursions on arecanut (Areca catechu L.) in India

Field incidence of exotic whitefly complex comprising two Neotropical nesting whiteflies viz., Paraleyrodes bondari Peracchi and Paraleyrodes minei Iaccarino, in association with invasive rugose spiralling whitefly Aleurodicus rugioperculatus Martin and native areca whitefly, Aleurocanthus arecae David & Manjunatha, on arecanut was reported from Karnataka, India during 2020. These arecanut palms were previously infested by A. arecae which was earlier reported from Karnataka during 2003. To our knowledge, this is the first report on the infestation of P. bondari and P. minei on arecanut as highlighted in this current investigation. Morphological identification based on pupal taxonomy and male genitalia as well as molecular characterization of the mitochondrial cytochrome oxidase I (COI) gene confirmed the identity of nesting whiteflies. The Bondar’s nesting whitefly, P. bondari is the most predominant whitefly species with 87.5 per cent active colonies followed by the nesting whitefly, P. minei (13.64%) and the rugose spiralling whitefly, A. rugioperculatus (6.25%). Co-occurrence of these three non-native whitefly species on arecanut in synergy with the native A. arecae indicates a kind of competitive regulation of one species over the other upsetting biodiversity. Due to the polyphagous nature of the pest coupled with increased trade and transport in a climate change scenario, this whitefly complex may become a serious threat to arecanut production in India and elsewhere. This requires strict quarantine protocols to avert its spread to other arecanut growing areas

A retrospective study of antimicrobial usage in wound healing

Background: Chronic wounds are responsible for increase in burden to healthcare systems. The evidence concerning effectiveness of antibiotic therapy or optimal regimens is insufficient. Patients with chronic wounds receive significantly more systemic and topical antibiotics. Current guidelines for antibiotic prescribing for such wounds are often based on expert opinion rather than scientific fact. As there is increasing prevalence of antibiotic resistance, the relationships between antibiotic resistance and rationales for antibiotic therapy have to be determined. Current practice of antibiotic usage for chronic wounds and postoperative wounds in a tertiary care setting should be studied.Methods: Retrospective study was conducted from February 2017 to February 2018 using medical records of patients with wound admitted in surgical departments in HIMS, Hassan, Karnataka. The inpatient records were analysed, which includes duration of stay in the hospital, number of drugs/products per person, percentage of antibiotics prescribed, percentage of antibiotic injection prescribed, and other modalities used to treat wounds.Results: In present study, amongst 100 antimicrobial prescriptions, 26 females and 74 males. The most commonly prescribed parenteral antibiotic was ceftriaxone (58%), followed by metronidazole (56%). The average number of antibiotics per prescription was 2.8. The mean duration parenteral antibiotics given was 4.26 days during their hospital stay oral antibiotics were 5.18 days after the discharge from the hospital.Conclusions: The information generated shall be used to decide the policies to govern the prescription of antibiotics in the management of chronic wounds and post-operative wounds

Prescribing pattern of antibiotics in pediatric department of a tertiary care teaching hospital

Background: Prescription is an order from doctor for medicine. Rational use of medicines requires that "patients receive medications appropriate to their clinical needs, in doses that meet their own individual requirements, for an adequate period of time, and at the lowest cost to them and their community". Irrational use of medicines is a major problem worldwide. This leads to serious morbidity and mortality also leads to reduction in the quality of treatment due to antibiotic resistance. Evaluation of prescribing pattern will help in minimizing adverse drug reactions, resistance among children. Also help to know the attitude of the physicians towards prescribing. Aim of the present study was to evaluate the prescription pattern of antibiotics in paediatric inpatients of Hassan institute of Medical Sciences.Methods: A prospective study, conducted among 110 patients below the age of 18 years and being treated with antibiotics were included in our study. The results were analyzed using descriptive statistics.Results: Out of 110 patients, female (58) and male (52) are enrolled in the study from inpatient paediatrics department, majority of patients belonged to age group of 0-5 years (74%), respiratory tract infections 29 (35%) , gastrointestinal infections 26 (22%) and central nervous system in 9 (11%). Out of 227 antimicrobial agent, about 83.48% were cephalosporins, followed by ciprofloxicin (33.94%), amoxicillin (32.11%), and amikacin (6.42%).Conclusions: Cephalosporins (ceftriaxone) were most commonly used antibiotic, which covers gram positive, gram negative and anaerobic organism

Encoding information onto the charge and spin state of a paramagnetic atom using MgO tunnelling spintronics

An electrical current that flows across individual atoms or molecules can generate exotic quantum-based behavior, from memristive effects to Coulomb blockade and the promotion of quantum excited states. These fundamental effects typically appear one at a time in model junctions built using atomic tip or lateral techniques. So far, however, a viable industrial pathway for such discrete state devices has been lacking. Here, we demonstrate that a commercialized device platform can serve as this industrial pathway for quantum technologies. We have studied magnetic tunnel junctions with a MgO barrier containing C atoms. The paramagnetic localized electrons due to individual C atoms generate parallel nanotransport paths across the micronic device as deduced from magnetotransport experiments. Coulomb blockade effects linked to tunnelling magnetoresistance peaks can be electrically controlled, leading to a persistent memory effect. Our results position MgO tunneling spintronics as a promising platform to industrially implement quantum technologies