Rocío Carratalá-Sáez

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• PhD in Computer Science
• Assistant Professor at University of Valencia

With the growing popularity of FPGA-based accelerators in HPC applications, new challenges have emerged, particularly in terms of programming and portability. This paper provides an overview of the current state of FPGA tools and their limitations. This study evaluates the performance and portability of two frameworks, SYCL and OpenCL, for developi...

As the interest in FPGA-based accelerators for HPC applications increases, new challenges also arise, especially concerning different programming and portability issues. This paper aims to provide a snapshot of the current state of the FPGA tooling and its problems. To do so, we evaluate the performance portability of two frameworks for developing...

Slides of the conference paper "Challenging Portability Paradigms: FPGA Acceleration Using SYCL and OpenCL", presented at Heteropar 2024 (Euro-Par workshop), in Madrid, aug 2024.

As Field Programmable Gate Arrays (FPGAs) computing capabilities continue to grow, also does the interest on building scientific accelerators around them. Tools like Xilinx's High-Level Synthesis (HLS) help to bridge the gap between traditional high-level languages such as C and C++, and low-level hardware description languages such as VHDL and Ver...

There are many works devoted to improving the matrix product computation, as it is used in a wide variety of scientific applications arising from many different fields. In this work, we propose alternative data distribution policies and communication patterns to reduce the elapsed time when computing triangular matrix products in distributed memory...

This research explores for the first time the application of machine learning to detect emotional responses in video game streaming channels, specifically on Twitch, the most widely used platform for broadcasting content. Analyzing sentiment in gaming contexts is difficult due to the brevity of messages, the lack of context, and the use of informal...

Matrix multiplication is one of the most costly linear algebra operations, very often present in scientific computational applications. Current generic linear algebra libraries, such as ScaLAPACK and its recent evolution SLATE, include functionalities for generic and triangular matrix multiplication. They generally rely on block-cyclic partitioning...

Computational platforms for high-performance scientific applications are becoming more heterogenous, including hardware accelerators such as multiple GPUs. Applications in a wide variety of scientific fields require an efcient and careful management of the computational resources of this type of hardware to obtain the best possible performance. How...

The determination of Lagrangian Coherent Structures (LCS) is becoming very important in several disciplines, including cardiovascular engineering, aerodynamics, and geophysical fluid dynamics. From the computational point of view, the extraction of LCS consists of two main steps: The flowmap computation and the resolution of Finite Time Lyapunov Ex...

La extracción de Estructuras Coherentes Lagrangianas (LCS) es común en diversos campos de dinámica de fluidos, centrados en estudiar el comportamiento de las partículas que integran determinados flujos presentes en la naturaleza, los cuerpos humanos y animales, determinados fluidos artificiales, etc. En concreto, en el proceso de extracción de LCS...

In this work we present an extension of our previous experience with the course “Build your own supercomputer with Raspberry Pi”, presented in [1]. It is offered as a non-mandatory workshop with the purpose of bringing High Performance Computing (HPC) closer to bachelor students of Jaume I University (UJI, Spain). The intention of the course is two...

We address the parallelization of the LU factorization of hierarchical matrices ($\mathcal{H}$-matrices) arising from boundary element methods. Our approach exploits task-parallelism via the OmpSs programming model and runtime, which discovers the data-flow parallelism intrinsic to the operation at execution time, via the analysis of data dependenc...

We address the parallelization of the LU factorization of hierarchical matrices (-matrices) arising from boundary element methods. Our approach exploits task-parallelism via the OmpSs programming model and runtime, which discovers the data-flow parallelism intrinsic to the operation at execution time, via the analysis of data dependencies based on...

We investigate the introduction of look-ahead in two-stage algorithms for the singular value decomposition (SVD). Our approach relies on a specialized reduction for the first stage that produces a band matrix with the same upper and lower bandwidth instead of the conventional upper triangular-band matrix. In the case of a CPU-GPU server, this alter...

We present a prototype task-parallel algorithm for the solution of hierarchical symmetric positive definite linear systems via the ℋ -Cholesky factorization that builds upon the parallel programming standards and associated runtimes for OpenMP and OmpSs. In contrast with previous efforts, our proposal decouples the numerical aspects of the linear a...