Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

PREDICTION OF NETILMICIN DISPOSITION IN NEONATES

Multiple regression analyses of data from 33 neonates who received netilmicin therapy showed that concurrent treatment with other drugs (Drg), creatinine clearance (CL(cr)), gestational age (GA), and an apgar score of less than 6 at 1 min (Agl') were significant determinants of netilmicin clearance. Apparent volume of distribution was significantly affected by postnatal age (PNA), gender, the presence of ascites and/or oedema (A/O), and whether or not the neonate was small for gestational age (SGA). The following formulae were obtained: CL (ml min-1 kg-1) = -0.108 - 0.210 (Drg) + 0.152(CL(cr)) + 0.019(GA) -0.128(Agl') (multiple R = 0.725, p

Low pressure carbon dioxide solubility in pure electrolyte solvents for lithium-ion batteries as a function of temperature. Measurement and prediction

Experimental values for the carbon dioxide solubility in eight pure electrolyte solvents for lithium ion batteries – such as ethylene carbonate (EC), propylene carbonate (PC), dimethyl carbonate (DMC), ethyl methyl carbonate (EMC), diethyl carbonate (DEC), ?-butyrolactone (?BL), ethyl acetate (EA) and methyl propionate (MP) – are reported as a function of temperature from (283 to 353) K and atmospheric pressure. Based on experimental solubility data, the Henry’s law constant of the carbon dioxide in these solvents was then deduced and compared with reported values from the literature, as well as with those predicted by using COSMO-RS methodology within COSMOthermX software and those calculated by the Peng–Robinson equation of state implemented into Aspen plus. From this work, it appears that the CO2 solubility is higher in linear carbonates (such as DMC, EMC, DEC) than in cyclic ones (EC, PC, ?BL). Furthermore, the highest CO2 solubility was obtained in MP and EA solvents, which are comparable to the solubility values reported in classical ionicliquids. The precision and accuracy of the experimental values, considered as the per cent of the relative average absolute deviations of the Henry’s law constants from appropriate smoothing equations and from literature values, are close to (1% and 15%), respectively. From the variation of the Henry’s law constants with temperature, the partial molar thermodynamic functions of dissolution such as the standard Gibbs free energy, the enthalpy, and the entropy are calculated, as well as the mixing enthalpy of the solvent with CO2 in its hypothetical liquid state.

Serum eosinophilic cationic protein and blood eosinophil counts for the prediction of the presence of airways inflammation in children with wheezing

Background Serum eosinophilic cationic protein (ECP) concentrations may be useful noninvasive markers of airways inflammation in atopic asthma. However, the usefulness of serum ECP measurement for the prediction of airways inflammation in children with a history of wheezing is unknown.