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2020 – today
- 2024
[j4]Pedro Bruel
, Sai Rahul Chalamalasetti, Aditya Dhakal, Eitan Frachtenberg, Ninad Hogade, Rolando Pablo Hong Enriquez, Alok Mishra, Dejan S. Milojicic, Pavana Prakash, Gourav Rattihalli:
Predicting Heterogeneity and Serverless Principles of Converged High-Performance Computing, Artificial Intelligence, and Workflows. Computer 57(1): 136-144 (2024)- [j3]Eitan Frachtenberg, Viyom Mittal, Pedro Bruel, Michalis Faloutsos, Dejan S. Milojicic:
The Distribution Is the Performance. Computer 57(4): 143-149 (2024) - [j2]Rolando P. Hong Enriquez, Rosa M. Badia, Barbara M. Chapman, Kirk Bresniker, Scott Pakin, Alok Mishra, Pedro Bruel, Aditya Dhakal, Gourav Rattihalli, Ninad Hogade, Eitan Frachtenberg, Dejan S. Milojicic:
Quantum optimization algorithms: Energetic implications. Concurr. Comput. Pract. Exp. 36(16) (2024) - 2023
- [c9]Gourav Rattihalli, Ninad Hogade, Aditya Dhakal, Eitan Frachtenberg, Rolando P. Hong Enriquez, Pedro Bruel, Alok Mishra, Dejan S. Milojicic:
Fine-Grained Heterogeneous Execution Framework with Energy Aware Scheduling. CLOUD 2023: 35-44 - [c8]Pedro Bruel, Viyom Mittal, Dejan S. Milojicic, Michalis Faloutsos, Eitan Frachtenberg:
Revisiting Performance Evaluation in the Age of Uncertainty. HiPCW 2023: 23-30 - [c7]Viyom Mittal, Pedro Bruel, Dejan S. Milojicic, Eitan Frachtenberg:
Adaptive Stopping Rule for Performance Measurements. SC Workshops 2023: 1288-1297 - [i1]Giacomo Pedretti, John Moon, Pedro Bruel, Sergey Serebryakov, Ron M. Roth, Luca Buonanno, Tobias Ziegler, Cong Xu, Martin Foltin, Paolo Faraboschi, Jim Ignowski, Catherine E. Graves:
X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs. CoRR abs/2304.01285 (2023) - 2021
- [b1]Pedro Bruel:
Toward transparent and parsimonious methods for automatic performance tuning. (Vers des méthodes transparentes et parcimonieuses pour l'optimisation automatique des performances). University of Sao Paulo, Brazil, 2021 - [c6]Sitao Huang, Aayush Ankit, Plínio Silveira, Rodrigo Antunes, Sai Rahul Chalamalasetti, Izzat El Hajj, Dong Eun Kim, Glaucimar Aguiar, Pedro Bruel, Sergey Serebryakov, Cong Xu, Can Li, Paolo Faraboschi, John Paul Strachan, Deming Chen, Kaushik Roy, Wen-Mei W. Hwu, Dejan S. Milojicic:
Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators. ASP-DAC 2021: 372-377
2010 – 2019
- 2019
- [c5]Pedro Bruel, Steven Quinito Masnada, Brice Videau, Arnaud Legrand, Jean-Marc Vincent, Alfredo Goldman:
Autotuning Under Tight Budget Constraints: A Transparent Design of Experiments Approach. CCGRID 2019: 147-156 - 2017
- [j1]Pedro Bruel, Marcos Amaris, Alfredo Goldman:
Autotuning CUDA compiler parameters for heterogeneous applications using the OpenTuner framework. Concurr. Comput. Pract. Exp. 29(22) (2017) - [c4]Pedro Bruel, Sai Rahul Chalamalasetti, Chris I. Dalton, Izzat El Hajj, Alfredo Goldman, Catherine Graves, Wen-Mei W. Hwu, Phil Laplante, Dejan S. Milojicic, Geoffrey Ndu, John Paul Strachan:
Generalize or Die: Operating Systems Support for Memristor-Based Accelerators. ICRC 2017: 1-8 - [c3]Pedro Bruel, Alfredo Goldman, Sai Rahul Chalamalasetti, Dejan S. Milojicic:
Autotuning high-level synthesis for FPGAs using OpenTuner and LegUp. ReConFig 2017: 1-6 - 2016
- [c2]Rogério Aparecido Gonçalves, Marcos Amaris, Thiago Kenji Okada, Pedro Bruel, Alfredo Goldman:
OpenMP is Not as Easy as It Appears. HICSS 2016: 5742-5751 - 2014
- [c1]Pedro Bruel, Marcelo Queiroz:
A Protocol for creating Multiagent Systems in Ensemble with Pure Data. ICMC 2014
Coauthor Index
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