Demo Data from EDBT 2026 / reviewers in the wild / expert
Pietro Bonfà
dblp:222/2798
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Energy-efficient computing › power management
dynamic power management |
0.5 | 1 | 2021 | COUNTDOWN: A Run-Time Library for Performance-Neutral Energy Saving in MPI Applications · IEEE Trans. Computers 2021 |
High-performance computing › supercomputing
energy-efficient HPC |
0.5 | 1 | 2021 | COUNTDOWN: A Run-Time Library for Performance-Neutral Energy Saving in MPI Applications · IEEE Trans. Computers 2021 |
Energy-efficient computing
power management |
0.5 | 1 | 2021 | 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 |
0.1 | 1 | 2021 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | COUNTDOWN: A Run-Time Library for Performance-Neutral Energy Saving in MPI ApplicationsabstractPower 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. Computers | 3 |