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» Online Prediction of the Running Time of Tasks
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IPPS
2003
IEEE
13 years 10 months ago
Improving Speculative Thread-Level Parallelism Through Module Run-Length Prediction
Exploiting speculative thread-level parallelism across modules, e.g., methods, procedures, or functions, have shown promise. However, misspeculations and task creation overhead ar...
Fredrik Warg, Per Stenström
ISPASS
2009
IEEE
13 years 11 months ago
Machine learning based online performance prediction for runtime parallelization and task scheduling
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
Jiangtian Li, Xiaosong Ma, Karan Singh, Martin Sch...
CHI
2005
ACM
14 years 5 months ago
Predicting task execution time on handheld devices using the keystroke-level model
The Keystroke-Level Model (KLM) has been shown to predict skilled use of desktop systems, but has not been validated on a handheld device that uses a stylus instead of a keyboard....
Lu Luo, Bonnie E. John
RTAS
2010
IEEE
13 years 3 months ago
DARTS: Techniques and Tools for Predictably Fast Memory Using Integrated Data Allocation and Real-Time Task Scheduling
—Hardware-managed caches introduce large amounts of timing variability, complicating real-time system design. One alternative is a memory system with scratchpad memories which im...
Sangyeol Kang, Alexander G. Dean
ICANN
2001
Springer
13 years 9 months ago
Online Symbolic-Sequence Prediction with Discrete-Time Recurrent Neural Networks
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
Juan Antonio Pérez-Ortiz, Jorge Calera-Rubi...