Título:
Optimizing the performance of SPMV kernel in FPGA guided by the Roofline model
Otros títulos:
Coordinador:
Director:
Compilador:
Autor:
Favaro, Federico
Dufrechou, Ernesto
Oliver, Juan P.
Ezzatti, Pablo
Dufrechou, Ernesto
Oliver, Juan P.
Ezzatti, Pablo
Tutor:
Tipo de documento:
Preprint
Editor:
Palabras clave:
Sparse NLA
FPGA
Energy consumption
Performance modeling
FPGA
Energy consumption
Performance modeling
Descriptores:
Año de publicación:
2023
Contenido:
Resumen:
The widespread adoption of massively parallel processors over the past decade has fundamentally transformed the landscape of high-performance computing hardware. This revolution has recently driven the advancement of FPGAs, which are emerging as an attractive alternative to power-hungry many-core devices in a world increasingly concerned with energy consumption.
Consequently, numerous recent studies have focused on implementing efficient dense and sparse
numerical linear algebra (NLA) kernels on FPGAs. To maximize the efficiency of these kernels, a key
aspect is the exploration of analytical tools to comprehend the performance of the developments and
guide the optimization process. In this regard, the roofline model (RLM) is a well-known graphical
tool that facilitates the analysis of computational performance and identifies the primary bottlenecks
of a specific software when executed on a particular hardware platform. Our previous efforts advanced in developing efficient implementations of the sparse matrix–vector multiplication (SpMV) for
FPGAs, considering both speed and energy consumption. In this work, we propose an extension of
the RLM that enables optimizing runtime and energy consumption for NLA kernels based on sparse
blocked storage formats on FPGAs. To test the power of this tool, we use it to extend our previous
SpMV kernels by leveraging a block-sparse storage format that enables more efficient data access.
Descripción:
Publicado en Micromachines con el título: Optimizing the performance of the Sparse Matrix–Vector Multiplication Kernel in FPGA guided by the Roofline Model.
metadata.articulos.dc.description.uri:
Editorial:
EN:
Financiadores:
FCE_3_2022_1_172419 - MODELAR: Modelado del desempeñO de métoDos numÉricos en pLataformas de hArdware heteRogéneas
Citación:
Favaro, F., Dufrechou, E., Oliver, J. y otros. Optimizing the performance of the Sparse Matrix–Vector Multiplication Kernel in FPGA guided by the Roofline Model [Preprint] Publicado en : Micromachines 2023, 14(11), 2030; DOI : https://doi.org/10.3390/mi14112030. 14 p.
Citación:
metadata.articulos.cc.license.name:
ISBN:
e-ISBN:
ISSN:
ISMN:
Otros identificadores:
Cobertura geográfica:
Cobertura temporal:
Departamento académico:
Grupo de investigación:
Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| FDOE23.pdf | Preprint | 877.37 KB | Adobe PDF |