A Protocol for creating Multiagent Systems in Ensemble with Pure Data. - Pedro Bruel; Marcelo Queiroz (ICMC, 2014)

OpenMP is Not as Easy as It Appears. - Rogério Aparecido Gonçalves; Marcos Amaris; Thiago Kenji Okada; Pedro Bruel; Alfredo Goldman (HICSS, 2016)

Generalize or Die: Operating Systems Support for Memristor-Based Accelerators. - 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 (ICRC, 2017)

Autotuning high-level synthesis for FPGAs using OpenTuner and LegUp. - Pedro Bruel; Alfredo Goldman; Sai Rahul Chalamalasetti; Dejan S. Milojicic (ReConFig, 2017)

Autotuning CUDA compiler parameters for heterogeneous applications using the OpenTuner framework. - Pedro Bruel; Marcos Amaris; Alfredo Goldman (Concurr. Comput. Pract. Exp., 2017)

Autotuning Under Tight Budget Constraints: A Transparent Design of Experiments Approach. - Pedro Bruel; Steven Quinito Masnada; Brice Videau; Arnaud Legrand; Jean-Marc Vincent; Alfredo Goldman (CCGRID, 2019)

Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators. - 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; et al. (ASP-DAC, 2021)

Toward transparent and parsimonious methods for automatic performance tuning. (Vers des méthodes transparentes et parcimonieuses pour l'optimisation automatique des performances). - Pedro Bruel (2021)

Fine-Grained Heterogeneous Execution Framework with Energy Aware Scheduling. - Gourav Rattihalli; Ninad Hogade; Aditya Dhakal; Eitan Frachtenberg; Rolando P. Hong Enriquez; Pedro Bruel; Alok Mishra 002; Dejan S. Milojicic (CLOUD, 2023)

Revisiting Performance Evaluation in the Age of Uncertainty. - Pedro Bruel; Viyom Mittal; Dejan S. Milojicic; Michalis Faloutsos; Eitan Frachtenberg (HiPCW, 2023)

Adaptive Stopping Rule for Performance Measurements. - Viyom Mittal; Pedro Bruel; Dejan S. Milojicic; Eitan Frachtenberg (SC Workshops, 2023)

X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs. - Giacomo Pedretti; John Moon; Pedro Bruel; Sergey Serebryakov; Ron M. Roth; Luca Buonanno; Tobias Ziegler 006; Cong Xu; Martin Foltin; Paolo Faraboschi; Jim Ignowski; Catherine E. Graves (CoRR, 2023)

CAMSHAP: Accelerating Machine Learning Model Explainability with Analog CAM. - John Moon; Giacomo Pedretti; Pedro Bruel; Sergey Serebryakov; Omar Eldash; Luca Buonanno; Catherine E. Graves; Paolo Faraboschi; Jim Ignowski (ICCAD, 2024)

SHARP: A Distribution-Based Framework for Reproducible Performance Evaluation. - Viyom Mittal; Pedro Bruel; Michalis Faloutsos; Dejan S. Milojicic; Eitan Frachtenberg (IISWC, 2024)

DyTwin: Federated Adaptive Digital Twins for Data Centers - Visualization and Anomaly Detection. - Ebad Taheri; Pedro Bruel; Pavana Prakash; Gourav Rattihalli; Ninad Hogade; Aditya Dhakal; Rolando P. Hong Enriquez; Torsten Wilde; Leo Popokh; Dejan S. Milojicic; Cullen E. Bash (SC Workshops, 2024)

Predicting Heterogeneity and Serverless Principles of Converged High-Performance Computing, Artificial Intelligence, and Workflows. - Pedro Bruel; Sai Rahul Chalamalasetti; Aditya Dhakal; Eitan Frachtenberg; Ninad Hogade; Rolando Pablo Hong Enriquez; Alok Mishra 002; Dejan S. Milojicic; Pavana Prakash; Gourav Rattihalli (Computer, 2024)

The Distribution Is the Performance. - Eitan Frachtenberg; Viyom Mittal; Pedro Bruel; Michalis Faloutsos; Dejan S. Milojicic (Computer, 2024)

Quantum optimization algorithms: Energetic implications. - Rolando P. Hong Enriquez; Rosa M. Badia; Barbara M. Chapman; Kirk Bresniker; Scott Pakin; Alok Mishra 002; Pedro Bruel; Aditya Dhakal; Gourav Rattihalli; Ninad Hogade; Eitan Frachtenberg; Dejan S. Milojicic (Concurr. Comput. Pract. Exp., 2024)

Predicting Performance Variability. - Mohammed Baydoun; Mohammad Sonji; Pedro Bruel; Dejan S. Milojicic; Eitan Frachtenberg; Izzat El Hajj (IPDPS (Workshops), 2025)