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Pietro Bonfà

dblp:222/2798 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0001-6358-3037ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Energy-efficient computing · 61% High-performance computing · 30% Parallel and multicore computing · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Energy-efficient computing › power management
dynamic power management
0.512021
COUNTDOWN: A Run-Time Library for Performance-Neutral Energy Saving in MPI Applications · IEEE Trans. Computers 2021
High-performance computing › supercomputing
energy-efficient HPC
0.512021
COUNTDOWN: A Run-Time Library for Performance-Neutral Energy Saving in MPI Applications · IEEE Trans. Computers 2021
Energy-efficient computing
power management
0.512021
COUNTDOWN: A Run-Time Library for Performance-Neutral Energy Saving in MPI Applications · IEEE Trans. Computers 2021
Parallel and multicore computing › parallel programming models › message passing
MPI communication
0.112021
COUNTDOWN: A Run-Time Library for Performance-Neutral Energy Saving in MPI Applications · IEEE Trans. Computers 2021

Methods — techniques the papers use, named apart from their topics

runtime library · 0.5power state transition · 0.5
YearPublicationVenuePosition
2021 COUNTDOWN: A Run-Time Library for Performance-Neutral Energy Saving in MPI Applications
abstract
Power and energy consumption are becoming key challenges for the supercomputers' exascale race. HPC systems' processors waist active power during communication and synchronization among the MPI processes in large-scale HPC applications. However, due to the time scale at which communication happens, transitioning into low-power states while waiting for the completion of each communication may introduce unacceptable overhead. In this article, we present COUNTDOWN, a run-time library for identifying and automatically reducing the power consumption of the CPUs during communication and synchronization. COUNTDOWN saves energy without penalizing the time-to-completion by lowering CPUs power consumption only during idle times for which power state transition overhead is negligible. This is done transparently to the user, without requiring labor-intensive and error-prone application code modifications, nor requiring recompilation of the application. We test our methodology on a production Tier-1 system. For the NAS benchmarks, COUNTDOWN saves between 6 and 50 percent energy, with a time-to-solution penalty lower than 5 percent. In a complete production-Quantum ESPRESSO-for a 3.5K cores run, COUNTDOWN saves 22.36 percent energy, with a performance penalty below 3 percent. Energy saving increases to 37 percent with a performance penalty of 6.38 percent, if the application is executed without communication tuning.
Daniele Cesarini, Andrea Bartolini, Pietro Bonfà, Carlo Cavazzoni, Luca Benini
IEEE Trans. Computers3