Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6872907 | Future Generation Computer Systems | 2018 | 19 Pages |
Abstract
Implementing such kind of algorithms may be a complex task, due to low-level interactions with the underlying hardware and to non-intrusive and low-overhead monitoring of the applications. For these reasons, in this paper we propose Nornir, a C++-based framework, which can be used to enforce performance and power consumption constraints on parallel applications running on shared memory multicores. The framework can be easily customized by algorithm designers to implement new self-adaptive policies. By instrumenting the applications in the PARSEC benchmark, we provide to strategy designers a wide set of applications already interfaced to Nornir. In addition to this, to prove its flexibility, we implemented and compared several state-of-the-art existing policies, showing that Nornir can also be used to easily analyze different algorithms and to provide useful insights on them.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Daniele De Sensi, Tiziano De Matteis, Marco Danelutto,