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João P. L. de Carvalho
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2020 – today
- 2024
- [c16]Caio Salvador Rohwedder
, João P. L. de Carvalho
, José Nelson Amaral
:
Region-Based Data Layout via Data Reuse Analysis. CC 2024: 49-59 - 2023
- [j10]Catalina Munoz Morales, Bruno C. Honorio, Joao P. L. de Carvalho
, Alexandro Baldassin, Guido Araujo:
On the impact of mode transition on phased transactional memory performance. J. Parallel Distributed Comput. 173: 126-139 (2023) - [j9]Braedy Kuzma, Ivan Korostelev, João P. L. de Carvalho
, José E. Moreira, Christopher Barton, Guido Araujo, José Nelson Amaral:
Fast matrix multiplication via compiler-only layered data reorganization and intrinsic lowering. Softw. Pract. Exp. 53(9): 1793-1814 (2023) - [j8]Ivan Korostelev
, Joao P. L. de Carvalho
, José E. Moreira
, José Nelson Amaral
:
YaConv: Convolution with Low Cache Footprint. ACM Trans. Archit. Code Optim. 20(1): 18:1-18:18 (2023) - [j7]Victor Ferrari
, Rafael Cardoso Fernandes Sousa
, Márcio Machado Pereira, Joao P. L. de Carvalho
, José Nelson Amaral
, José E. Moreira
, Guido Araujo
:
Advancing Direct Convolution Using Convolution Slicing Optimization and ISA Extensions. ACM Trans. Archit. Code Optim. 20(4): 54:1-54:26 (2023) - [c15]Rouzbeh Paktinatkeleshteri, João P. L. de Carvalho, Ehsan Amiri, José Nelson Amaral:
Efficient Auto-Vectorization for Control-flow Dependent Loops through Data Permutation. CASCON 2023: 74-83 - [c14]Nathan Henderson, Iain Ireland, Matthew Gaudet, João P. L. de Carvalho, José Nelson Amaral:
Stub Folding: Retaining Type Specialization to Increase the Efficiency of Highly Polymorphic Inline Caches. CASCON 2023: 113-122 - [c13]Caio Salvador Rohwedder
, Nathan Henderson
, João P. L. de Carvalho, Yufei Chen, José Nelson Amaral:
To Pack or Not to Pack: A Generalized Packing Analysis and Transformation. CGO 2023: 14-27 - [c12]Tyler Gobran, João P. L. de Carvalho, Christopher Barton:
DASS: Dynamic Adaptive Sub-Target Specialization. SBAC-PADW 2023: 36-45 - [i2]Victor Ferrari, Rafael C. F. Sousa, Márcio Machado Pereira, João P. L. de Carvalho, José Nelson Amaral, José E. Moreira, Guido Araujo:
Advancing Direct Convolution using Convolution Slicing Optimization and ISA Extensions. CoRR abs/2303.04739 (2023) - [i1]Braedy Kuzma, Ivan Korostelev, João P. L. de Carvalho, José E. Moreira, Christopher Barton, Guido Araujo, José Nelson Amaral:
Fast Matrix Multiplication via Compiler-only Layered Data Reorganization and Intrinsic Lowering. CoRR abs/2305.18236 (2023) - 2022
- [j6]João P. L. de Carvalho
, José E. Moreira
, José Nelson Amaral
:
Compiling for the IBM Matrix Engine for Enterprise Workloads. IEEE Micro 42(5): 34-40 (2022) - [j5]Bruno Chinelato Honorio
, João P. L. de Carvalho
, Catalina Munoz Morales
, Alexandro Baldassin
, Guido Araujo
:
Using Barrier Elision to Improve Transactional Code Generation. ACM Trans. Archit. Code Optim. 19(3): 46:1-46:23 (2022) - [j4]Wyatt Praharenka
, David Pankratz, João P. L. de Carvalho
, Ehsan Amiri, José Nelson Amaral:
Vectorizing divergent control flow with active-lane consolidation on long-vector architectures. J. Supercomput. 78(10): 12553-12588 (2022) - [c11]Victor Ferrari
, Rafael C. F. Sousa, Márcio Machado Pereira, João P. L. de Carvalho, José Nelson Amaral, Guido Araujo:
Improving Convolution via Cache Hierarchy Tiling and Reduced Packing. PACT 2022: 538-539 - 2021
- [j3]João P. L. de Carvalho
, Braedy Kuzma
, Ivan Korostelev, José Nelson Amaral, Christopher Barton, José E. Moreira, Guido Araujo:
KernelFaRer: Replacing Native-Code Idioms with High-Performance Library Calls. ACM Trans. Archit. Code Optim. 18(3): 38:1-38:22 (2021) - [c10]Catalina Munoz Morales, Rafael Murari, Joao P. L. de Carvalho
, Bruno Chinelato Honorio, Alexandro Baldassin
, Guido Araujo:
Accelerating Graph Applications Using Phased Transactional Memory. Euro-Par 2021: 421-434 - [c9]Caio S. Rohwedder
, João P. L. de Carvalho
, José Nelson Amaral, Guido Araújo, Giancarlo Colmenares, Kai-Ting Amy Wang:
Pooling Acceleration in the DaVinci Architecture Using Im2col and Col2im Instructions. IPDPS Workshops 2021: 46-55 - 2020
- [j2]Aldo Culquicondor, Alexandro Baldassin
, César Castelo-Fernández, João P. L. de Carvalho
, João Paulo Papa
:
An efficient parallel implementation for training supervised optimum-path forest classifiers. Neurocomputing 393: 259-268 (2020) - [c8]Alexandro Baldassin
, Rafael Murari, João P. L. de Carvalho
, Guido Araujo, Daniel Castro
, João Barreto
, Paolo Romano
:
NV-PhTM: An Efficient Phase-Based Transactional System for Non-volatile Memory. Euro-Par 2020: 477-492 - [c7]João P. L. de Carvalho
, Bruno C. Honorio, Alexandro Baldassin
, Guido Araujo:
Improving Transactional Code Generation via Variable Annotation and Barrier Elision. IPDPS 2020: 1008-1017 - [c6]Bruno Chinelato Honorio
, João P. L. de Carvalho
, Munir S. Skaf
, Guido Araujo
:
Using OpenMP to Detect and Speculate Dynamic DOALL Loops. IWOMP 2020: 231-246 - [c5]João P. L. de Carvalho
, Braedy Kuzma
, Guido Araujo:
Acceleration Opportunities in Linear Algebra Applications via Idiom Recognition. ICPE Companion 2020: 34-35
2010 – 2019
- 2019
- [j1]Joao P. L. de Carvalho
, Guido Araujo
, Alexandro Baldassin
:
The Case for Phase-Based Transactional Memory. IEEE Trans. Parallel Distributed Syst. 30(2): 459-472 (2019) - 2018
- [c4]Luis Mattos, Divino Cesar S. Lucas, Juan Salamanca
, Joao P. L. de Carvalho
, Márcio Machado Pereira, Guido Araujo:
DOACROSS Parallelization Based on Component Annotation and Loop-Carried Probability. SBAC-PAD 2018: 29-32 - [c3]Bruno Chinelato Honorio, João P. L. de Carvalho
, Alexandro José Baldassin
:
On the Efficiency of Transactional Code Generation: A GCC Case Study. WSCAD 2018: 184-190 - 2017
- [c2]Joao P. L. de Carvalho
, Guido Araujo, Alexandro Baldassin
:
Revisiting phased transactional memory. ICS 2017: 25:1-25:10 - 2012
- [c1]Alexandro Baldassin
, Joao P. L. de Carvalho
, Leonardo A. G. Garcia, Rodolfo Azevedo
:
Energy-Performance Tradeoffs in Software Transactional Memory. SBAC-PAD 2012: 147-154
Coauthor Index
aka: Guido Araújo
aka: Alexandro José Baldassin
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last updated on 2024-06-10 21:22 CEST by the dblp team
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