Esteban is a Real-Time Analytics Researcher at Dynatrace currently working on algorithms and technologies for the optimization of log pattern matching, clustering and template extraction.
He received his master's degree in Software Engineering and Artificial Intelligence in 2017 and completed his PhD titled "High Performance Computing for Genomics" at the University of Malaga in 2023. His research focused on the design of algorithms applied to different computer architectures (such as multiprocessor systems and GPUs) to accelerate large-scale biological sequence comparison.
Authored publications
A Comprehensive Benchmarking Analysis of Fault Recovery in Stream Processing Frameworks
Nowadays, several software systems rely on stream processing architectures to deliver scalable performance and handle large volumes of data in near real time. Stream processing frameworks facilitate scalable computing by distributing the application's execution across multiple machines. Despite performance being extensively studied, the measurement...
Adriano Vogel, Sören Henning, Esteban Perez-Wohlfeil, Otmar Ertl, Rick Rabiser
| 18th ACM International Conference on Distributed and Event-Based Systems (DEBS'24) | 2024
High-level Stream Processing: A Complementary Analysis of Fault Recovery
Parallel computing is very important to accelerate the performance of software systems. Additionally, considering that a recurring challenge is to process high data volumes continuously, stream processing emerged as a paradigm and software architectural style. Several software systems rely on stream processing to deliver scalable performance, where...
Adriano Vogel, Sören Henning, Esteban Perez-Wohlfeil, Otmar Ertl, Rick Rabiser
| Distributed, Parallel, and Cluster Computing, arXiv:2405.07917 | 2024
Irregular alignment of arbitrarily long DNA sequences on GPU
The use of Graphics Processing Units to accelerate computational applications is increasingly being adopted due to its affordability, flexibility and performance. However, achieving top performance comes at the price of restricted data-parallelism models. In the case of sequence alignment, most GPU-based approaches focus on accelerating the Smith-W...
Esteban Perez-Wohlfeil, Oswaldo Trelles, Nicolás Guil
| The Journal of Supercomputing | 2022
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