About Me
I am a software engineer working on Tech, Pathfinding and Innovation at Intel.
I was a postdoctoral scholar in Computer Science at Stanford University, and worked with Professor Alex Aiken on scalable task-based programming systems.
I received my Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 2020, advised by Professors David Padua and William Gropp. During the Ph.D., I developed Locus, a new system, and a language for optimizing complex, long-lived applications for different platforms. It can ameliorate the difficulty of optimizing applications using a methodology based on optimization programming and automated empirical search. The Locus language allows the definition of a search space combined with the programming of optimization sequences separated from the application’s reference code. Based on a Locus program, the system automatically selects, generates, and executes candidate implementations to find the one with the best performance. I was also part of the XPACC project.
During the summer of 2017, I headed off to Seattle, where I joined the Programming Systems and Applications Research Group at Nvidia Research. At Nvidia, I worked on a code optimizer for deep neural networks.
In 2015, I spent the summer at the Lawrence Livermore National Laboratory. My research mostly focused on understanding how to use machine learning to explore the space of code optimizations efficiently.
I have also spent some good years researching and developing parallel geophysical algorithms at Petrobras. I have been part of the Geophysical Technology research group and, in 2009, helped to successfully deploy in production one of the first heterogeneous clusters with GPUs for seismic processing.
All the journey started off at UFMG in Brazil, where I have received my BSc and MSc in Computer Science advised by Professor Wagner Meira. There, I have had the opportunity to join the Speed Lab and develop efficient parallel runtime systems for data mining algorithms, also mentored by Professors Dorgival Guedes, Renato Ferreira.Awards
Bronze Medal in the ACM Student Research Competition at PACT 2017.
Best Master's Thesis Award in 2011 selected by the Commission of Computer Architecture and High Performance Computing of Brazilian Computer Society.
Top Ten Best Master's Thesis of 2010 selected by the Brazilian Computer Society.
Second place on Second Marathon of Parallel Programming at SBAC-PAD'07.
WSCAD'05 Best paper award.
Selected Publications
Automated Mapping of Task-Based Programs onto Distributed and Heterogeneous Machines. Thiago S. F. X. Teixeira, Alexandra Henzinger, Rohan Yadav, Alex Aiken. Supercomputing, 2023. PDF file PDF file Paper Link
A task-based parallel framework for ensemble simulations of rocket ignition: Verification and performance assessment. K Maeda, C Laurent, T Teixeira, M Di Renzo, G Iaccarino. Bulletin of the American Physical Society, 2022.
Task-based framework for physics-based ensemble simulation and in situ data processing. K Maeda, T Teixeira. Center for Turbulence Research Annual Research Briefs, 2022
A multiblock compressible Navier-Stokes solver in the Legion environment. A Voci, M Di Renzo, K Maeda, T Teixeira, G Iaccarino. Bulletin of the American Physical Society, 2021.
Online Multimedia Retrieval on CPU-GPU Platforms with Adaptive Work Partition. Rafael Souza, André Fernandes, Thiago S. F. X. Teixeira, George Teodoro, Renato Ferreira. JPDC, 2021. Paper Link
A Language and a System for Program Optimization. Thiago S. F. X. Teixeira. Ph.D. Dissertation, 2020. Paper Link
Managing code transformations for better performance portability. Thiago S. F. X. Teixeira, William Gropp, David Padua. IJHPCA, 2019. PDF file Paper Link
Locus: A System and a Language for Program Optimization. Thiago S. F. X. Teixeira, Corinne Ancourt, David Padua, William Gropp. CGO, 2019, Washington DC, USA. PDF file PDF file PDF file Paper Link
A DSL for Performance Orchestration (short paper). Thiago S. F. X. Teixeira, David Padua, William Gropp. 26th PACT, 2017, Portland, OR, USA.
Large-Scale Distributed Locality-Sensitive Hashing for General Metric Data. E. Silva, T. Teixeira, G. Teodoro, E. Valle. 7th SISAP, 2014, Los Cabos, Mexico.
Reverse Time Migration with Manycore Coprocessors. T. Teixeira, P. Souza, L. Borges, A. Neto, T. Philippe, C. Andreolli. 76th EAGE Conference And Exhibition, 2014, Amsterdam, Netherlands.
Accelerating Time and Depth Seismic Migration by CPU and GPU Cooperation. J. Panneta, T. S. F. X. Teixeira, P. Souza, et al. IJPP, 2011.
A Scalable Parallel Deduplication Algorithm. W. Santos, T. Teixeira, C. Machado, W. Meira Jr., et al. 19th SBAC-PAD, 2007, Gramado, RS, Brazil. PDF file Paper Link