Unified perception-prediction model for context aware text recognition on a heterogeneous many-core platform

2011 ◽  
Author(s):  
Qinru Qiu ◽  
Qing Wu ◽  
Richard Linderman
Keyword(s):  
Prediction Model ◽  
Text Recognition ◽  
Context Aware ◽  
Many Core

scholarly journals Energy-Efficient Thread Mapping for Heterogeneous Many-Core Systems via Dynamically Adjusting the Thread Count

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1346 ◽  
Author(s):  
Tao Ju ◽  
Yan Zhang ◽  
Xuejun Zhang ◽  
Xiaogang Du ◽  
Xiaoshe Dong
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Prediction Model ◽  
Phase Changes ◽  
Core System ◽  
Computing Performance ◽  
Many Core ◽  
Thread Mapping ◽  
Intel Mic ◽  
Thread Count

Improving computing performance and reducing energy consumption are a major concern in heterogeneous many-core systems. The thread count directly influences the computing performance and energy consumption for a multithread application running on a heterogeneous many-core system. For this work, we studied the interrelation between the thread count and the performance of applications to improve total energy efficiency. A prediction model of the optimum thread count, hereafter the thread count prediction model (TCPM), was designed by using regression analysis based on the program running behaviors and heterogeneous many-core architecture feature. Subsequently, a dynamic predictive thread mapping (DPTM) framework was proposed. DPTM uses the prediction model to estimate the optimum thread count and dynamically adjusts the number of active hardware threads according to the phase changes of the running program in order to achieve the optimal energy efficiency. Experimental results show that DPTM obtains a nearly 49% improvement in performance and a 59% reduction in energy consumption on average. Moreover, DPTM introduces about 2% additional overhead compared with traditional thread mapping for PARSEC(The Princeton Application Repository for Shared-Memory Computers) benchmark programs running on an Intel MIC (Many integrated core)heterogeneous many-core system.

1575: External Validation of Outcome Prediction Model for Ureteral/Renal Calculi

2005 ◽  
Vol 173 (4S) ◽  
pp. 427-427
Author(s):  
Sijo J. Parekattil ◽  
Udaya Kumar ◽  
Nicholas J. Hegarty ◽  
Clay Williams ◽  
Tara Allen ◽  
...  
Keyword(s):  
Prediction Model ◽  
Outcome Prediction ◽  
External Validation ◽  
Renal Calculi

Development of a headlamp dimming request prediction model

1975 ◽  
Author(s):  
Vivek D. Bhise ◽  
Thomas F. Swigart ◽  
Eugene I. Farber
Keyword(s):  
Prediction Model

Short-Version YLS-CMI: An Alternative Prediction Model for Juvenile Offenders at Intake

2009 ◽  
Author(s):  
Christina Campbell ◽  
Eyitayo Onifade ◽  
William Davidson ◽  
Jodie Petersen
Keyword(s):  
Juvenile Offenders ◽  
Prediction Model ◽  
Short Version

Career Choice Prediction--Model

2019 ◽  
Author(s):  
Zool Hilmi Mohamed Ashari ◽  
Norzaini Azman ◽  
Mohamad Sattar Rasul
Keyword(s):  
Prediction Model ◽  
Career Choice
Sign in / Sign up

Export Citation Format

Share Document