TCP: thread contention predictor for parallel programs

With proliferation of chip multicores (CMPs) on desktops and embedded platforms, multi-threaded programs have become ubiquitous. Existence of multiple threads may cause resource contention, such as, in on-chip shared cache and interconnects, depending upon how they access resources. Hence, we propose a tool - Thread Contention Predictor (TCP) to help quantify the number of threads sharing data and their sharing pattern. We demonstrate its use to predict a more profitable shared, last level on-chip cache (LLC) access policy on CMPs. Our cache configuration predictor is 2.2 times faster compared to the cycle-accurate simulations. We also demonstrate its use for identifying hot data structures in a program which may cause performance degradation due to false data sharing. We fix layout of such data structures and show up-to 10% and 18% improvement in execution time and energy-delay product (EDP), respectively.

STAT-1 expression is regulated by IGFBP-3 in malignant glioma cells and is a strong predictor of poor survival in patients with glioblastoma Laboratory investigation

Object. Insulin-like growth factor binding proteins (IGEBPs) have been implicated in the pathogenesis of glioma. In a previous study the authors demonstrated that IGFBP-3 is a novel glioblastoma biomarker associated with poor survival. Since signal transducer and activator of transcription 1 (STAT-1) has been shown to be regulated by IGFBP-3 during chondrogenesis and is a prosurvival and radioresistant molecule in different tumors, the aim in the present study was to explore the functional significance of IGFBP-3 in malignant glioma cells, to determine if STAT-1 is indeed regulated by IGFBP-3, and to study the potential of STAT-1 as a biomarker in glioblastoma. Methods. The functional significance of IGFBP-3 was investigated using the short hairpin (sh)RNA gene knockdown approach on U251MG cells. STAT-1 regulation by IGFBP-3 was tested on U251MG and U87MG cells by shRNA gene knockdown and exogenous treatment with recombinant IGFBP-3 protein. Subsequently, the expression of STAT-1 was analyzed with real-time reverse transcription polymerase chain reaction (RT-PCR) and immunohistochemistry (IHC) in glioblastoma and control brain tissues. Survival analyses were done on a uniformly treated prospective cohort of adults with newly diagnosed glioblastoma (136 patients) using Kaplan-Meier and Cox regression models. Results. IGFBP-3 knockdown significantly impaired proliferation, motility, migration, and invasive capacity of U251MG cells in vitro (p < 0.005). Exogenous overexpression of IGFBP-3 in U251MG and U87MG cells demonstrated STAT-1 regulation. The mean transcript levels (by real-time RT-PCR) and the mean labeling index of STAT-1 (by IHC) were significantly higher in glioblastoma than in control brain tissues (p = 0.0239 and p < 0.001, respectively). Multivariate survival analysis revealed that STAT-1 protein expression (HR 1.015, p = 0.033, 95% CI 1.001-1.029) along with patient age (HR 1.025, p = 0.005, 95% CI 1.008-1.042) were significant predictors of shorter survival in patients with glioblastoma. Conclusions. IGFBP-3 influences tumor cell proliferation, migration, and invasion and regulates STAT-1 expression in malignant glioma cells. STAT-1 is overexpressed in human glioblastoma tissues and emerges as a novel prognostic biomarker.

Consumption to biomass (Q/B) ratio and estimates of Q/B-predictor parameters for Caribbean fishes

Estimates of the Q/B ratio and parameters of equations to 'predict' Q/B values for 116 fish stocks in the Gulf of Salamanca, Colombia are presented. A compilation of these estimates available for Caribbean Sea fishes (264 stocks) is also provided for comparison purposes. General trends in the value of Q/B resulting from differences in the equation and parameter values used are briefly discussed.

On the use of predictor-corrector method for coupled Monte Carlo burnup codes

This paper investigates the effect of the burnup coupling scheme on the numerical stability and accuracy of coupled Monte-Carlo depletion calculations. We show that in some cases, even the Predictor Corrector method with relatively short time steps can be numerically unstable. In addition, we present two possible extensions to the Euler predictor-corrector (PC) method, which is typically used in coupled burnup calculations. These modifications allow using longer time steps, while maintaining numerical stability and accuracy. © 2013 Elsevier Ltd. All rights reserved.

Numerical stability of the predictor-corrector method in Monte Carlo burnup calculations of critical reactors

Monte Carlo burnup codes use various schemes to solve the coupled criticality and burnup equations. Previous studies have shown that the simplest methods, such as the beginning-of-step and middle-of-step constant flux approximations, are numerically unstable in fuel cycle calculations of critical reactors. Here we show that even the predictor-corrector methods that are implemented in established Monte Carlo burnup codes can be numerically unstable in cycle calculations of large systems. © 2013 Elsevier Ltd. All rights reserved.

A HYBRID METHOD OF FRACTIONAL STEPS WITH PREDICTOR-CORRECTOR DIFFERENCE-PSEUDOSPECTRUM FOR NUMERICAL-SOLUTION OF THE CONVECTION-DOMINATED FLOW PROBLEMS

A fractional-step method of predictor-corrector difference-pseudospectrum with unconditional L(2)-stability and exponential convergence is presented. The stability and convergence of this method is strictly proved mathematically for a nonlinear convection-dominated flow. The error estimation is given and the superiority of this method is verified by numerical test.

Urinary lipoarabinomannan as predictor for the tuberculosis immune reconstitution inflammatory syndrome

info:eu-repo/semantics/published

Patient expectation is the most important predictor of discharge destination after primary total joint arthroplasty.

The purpose of this study was to identify preoperative predictors of discharge destination after total joint arthroplasty. A retrospective study of three hundred and seventy-two consecutive patients who underwent primary total hip and knee arthroplasty was performed. The mean length of stay was 2.9 days and 29.0% of patients were discharged to extended care facilities. Age, caregiver support at home, and patient expectation of discharge destination were the only significant multivariable predictors regardless of the type of surgery (total knee versus total hip arthroplasty). Among those variables, patient expectation was the most important predictor (P < 0.001; OR 169.53). The study was adequately powered to analyze the variables in the multivariable logistic regression model, which had a high concordance index of 0.969.

Virtex FPGA Implementation of a Pipelined Adaptive LMS Predictor for Electronic Support Measures Receivers

High-speed field-programmable gate array (FPGA) implementations of an adaptive least mean square (LMS) filter with application in an electronic support measures (ESM) digital receiver, are presented. They employ "fine-grained" pipelining, i.e., pipelining within the processor and result in an increased output latency when used in the LMS recursive system. Therefore, the major challenge is to maintain a low latency output whilst increasing the pipeline stage in the filter for higher speeds. Using the delayed LMS (DLMS) algorithm, fine-grained pipelined FPGA implementations using both the direct form (DF) and the transposed form (TF) are considered and compared. It is shown that the direct form LMS filter utilizes the FPGA resources more efficiently thereby allowing a 120 MHz sampling rate.