Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Enhancing Resource Management through Prediction-based Policies   Task-based programming models are emerging as a promising alternative to make
the most of multi-/many-core systems. These programming models rely on runtime
systems, and their goal is to improve application performance by properly
scheduling application tasks to cores. Additionally, these runtime systems
offer policies to cope with application phases that lack in parallelism to fill
all cores. However, these policies are usually static and favor either
performance or energy efficiency. In this paper, we have extended a task-based
runtime system with a lightweight monitoring and prediction infrastructure that
dynamically predicts the optimal number of cores required for each application
phase, thus improving both performance and energy efficiency. Through the
execution of several benchmarks in multi-/many-core systems, we show that our
prediction-based policies have competitive performance while improving energy
efficiency when compared to state of the art policies.

15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
17
The categories of this paper are: q-fin
3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom