Energy-Performance Tradeoffs in Software Transactional Memory. - Alexandro Baldassin; Joao P. L. de Carvalho; Leonardo A. G. Garcia; Rodolfo Azevedo (SBAC-PAD, 2012)

Revisiting phased transactional memory. - Joao P. L. de Carvalho; Guido Araujo; Alexandro Baldassin (ICS, 2017)

DOACROSS Parallelization Based on Component Annotation and Loop-Carried Probability. - Luis Mattos; Divino Cesar S. Lucas; Juan Salamanca 001; Joao P. L. de Carvalho; Márcio Machado Pereira; Guido Araujo (SBAC-PAD, 2018)

On the Efficiency of Transactional Code Generation: A GCC Case Study. - Bruno Chinelato Honorio; João P. L. de Carvalho; Alexandro José Baldassin (WSCAD, 2018)

The Case for Phase-Based Transactional Memory. - Joao P. L. de Carvalho; Guido Araujo; Alexandro Baldassin (IEEE Trans. Parallel Distributed Syst., 2019)

NV-PhTM: An Efficient Phase-Based Transactional System for Non-volatile Memory. - Alexandro Baldassin; Rafael Murari; João P. L. de Carvalho; Guido Araujo; Daniel Castro 004; João Barreto 001; Paolo Romano 002 (Euro-Par, 2020)

Improving Transactional Code Generation via Variable Annotation and Barrier Elision. - João P. L. de Carvalho; Bruno C. Honorio; Alexandro Baldassin; Guido Araujo (IPDPS, 2020)

Using OpenMP to Detect and Speculate Dynamic DOALL Loops. - Bruno Chinelato Honorio; João P. L. de Carvalho; Munir S. Skaf; Guido Araujo (IWOMP, 2020)

Acceleration Opportunities in Linear Algebra Applications via Idiom Recognition. - João P. L. de Carvalho; Braedy Kuzma; Guido Araujo (ICPE Companion, 2020)

An efficient parallel implementation for training supervised optimum-path forest classifiers. - Aldo Culquicondor; Alexandro Baldassin; César Castelo-Fernández; João P. L. de Carvalho; João Paulo Papa (Neurocomputing, 2020)

Accelerating Graph Applications Using Phased Transactional Memory. - Catalina Munoz Morales; Rafael Murari; Joao P. L. de Carvalho; Bruno Chinelato Honorio; Alexandro Baldassin; Guido Araujo (Euro-Par, 2021)

Pooling Acceleration in the DaVinci Architecture Using Im2col and Col2im Instructions. - Caio S. Rohwedder; João P. L. de Carvalho; José Nelson Amaral; Guido Araújo; Giancarlo Colmenares; Kai-Ting Amy Wang (IPDPS Workshops, 2021)

KernelFaRer: Replacing Native-Code Idioms with High-Performance Library Calls. - João P. L. de Carvalho; Braedy Kuzma; Ivan Korostelev; José Nelson Amaral; Christopher Barton; José E. Moreira; Guido Araujo (ACM Trans. Archit. Code Optim., 2021)

Improving Convolution via Cache Hierarchy Tiling and Reduced Packing. - Victor Ferrari; Rafael C. F. Sousa; Márcio Machado Pereira; João P. L. de Carvalho; José Nelson Amaral; Guido Araujo (PACT, 2022)

Compiling for the IBM Matrix Engine for Enterprise Workloads. - João P. L. de Carvalho; José E. Moreira; José Nelson Amaral (IEEE Micro, 2022)

Using Barrier Elision to Improve Transactional Code Generation. - Bruno Chinelato Honorio; João P. L. de Carvalho; Catalina Munoz Morales; Alexandro Baldassin; Guido Araujo (ACM Trans. Archit. Code Optim., 2022)

Vectorizing divergent control flow with active-lane consolidation on long-vector architectures. - Wyatt Praharenka; David Pankratz; João P. L. de Carvalho; Ehsan Amiri; José Nelson Amaral (J. Supercomput., 2022)

Stub Folding: Retaining Type Specialization to Increase the Efficiency of Highly Polymorphic Inline Caches. - Nathan Henderson; Iain Ireland; Matthew Gaudet; João P. L. de Carvalho; José Nelson Amaral (CASCON, 2023)

Efficient Auto-Vectorization for Control-flow Dependent Loops through Data Permutation. - Rouzbeh Paktinatkeleshteri; João P. L. de Carvalho; Ehsan Amiri; José Nelson Amaral (CASCON, 2023)

To Pack or Not to Pack: A Generalized Packing Analysis and Transformation. - Caio Salvador Rohwedder; Nathan Henderson; João P. L. de Carvalho; Yufei Chen; José Nelson Amaral (CGO, 2023)

DASS: Dynamic Adaptive Sub-Target Specialization. - Tyler Gobran; João P. L. de Carvalho; Christopher Barton (SBAC-PADW, 2023)

On the impact of mode transition on phased transactional memory performance. - Catalina Munoz Morales; Bruno C. Honorio; Joao P. L. de Carvalho; Alexandro Baldassin; Guido Araujo (J. Parallel Distributed Comput., 2023)

YaConv: Convolution with Low Cache Footprint. - Ivan Korostelev; Joao P. L. de Carvalho; José E. Moreira; José Nelson Amaral (ACM Trans. Archit. Code Optim., 2023)

Fast matrix multiplication via compiler-only layered data reorganization and intrinsic lowering. - Braedy Kuzma; Ivan Korostelev; João P. L. de Carvalho; José E. Moreira; Christopher Barton; Guido Araujo; José Nelson Amaral (Softw. Pract. Exp., 2023)

Advancing Direct Convolution Using Convolution Slicing Optimization and ISA Extensions. - Victor Ferrari; Rafael Cardoso Fernandes Sousa; Márcio Machado Pereira; Joao P. L. de Carvalho; José Nelson Amaral; José E. Moreira; Guido Araujo (ACM Trans. Archit. Code Optim., 2023)

Region-Based Data Layout via Data Reuse Analysis. - Caio Salvador Rohwedder; João P. L. de Carvalho; José Nelson Amaral (CC, 2024)

Scalar Interpolation: A Better Balance between Vector and Scalar Execution for SuperScalar Architectures. - Reza Ghanbari; Henry Kao; João P. L. de Carvalho; Ehsan Amiri; José Nelson Amaral (CGO, 2025)