Advanced search
Start date
Betweenand
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Smart resource allocation of concurrent execution of parallel applications

Full text
Author(s):
da Silva, Vinicius S. [1] ; Nogueira, Angelo G. D. [1] ; de Lima, Everton Camargo [1] ; Rocha, Hiago M. G. de A. [2] ; Serpa, Matheus S. [2] ; Luizelli, Marcelo C. [1] ; Rossi, Fabio D. [3] ; Navaux, Philippe O. A. [2] ; Beck, Antonio Carlos S. [2] ; Lorenzon, Arthur Francisco [1]
Total Authors: 10
Affiliation:
[1] Fed Univ Pampa, Optimizat Syst Lab, Campus Alegrete, Alegrete - Brazil
[2] Univ Fed Rio Grande do Sul, Inst Informat, Porto Alegre, RS - Brazil
[3] Fed Inst Farroupilha, Optimizat Syst Lab, Alegrete - Brazil
Total Affiliations: 3
Document type: Journal article
Source: CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE; SEP 2021.
Web of Science Citations: 0
Abstract

Thread-level parallelism (TLP) has been widely exploited to optimize computational resource usage in high-performance systems. However, as many applications do not scale as the number of threads increase, resources will be wasted when the application executes with the maximum possible number of threads (i.e., the default execution) rather than fewer threads (thread throttling) that may use the resources more efficiently. Hence, instead of executing only one application with as many threads as possible, one can run more applications simultaneously by applying thread throttling to each one. The primary outcome of this strategy is a significant reduction in the total execution time and energy consumption when the system needs to execute a list of applications. Given that, we propose a smart resource allocation (SRA) for concurrent parallel application execution. It automatically finds the ideal degree of TLP for each application and guides the simultaneous parallel applications execution. When running 25 well-known benchmarks on three multicore systems and comparing SRA to state-of-the-art strategies (e.g., Batch, Equal policy, and Scalability), SRA improves the EDP by 87.4% over the Batch strategy; 75.5% over the Equal policy; and 38.8% over the scalability strategy. (AU)

FAPESP's process: 20/05115-4 - Probing planning for In-band network telemetry
Grantee:Fábio Diniz Rossi
Support Opportunities: Regular Research Grants
FAPESP's process: 18/23092-1 - Telemetry orchestration in programmable data planes
Grantee:Marcelo Caggiani Luizelli
Support Opportunities: Regular Research Grants