Extending Ginkgo to Manage Reconfigurable Hardware-Based Kernels
Although heterogeneous systems based on hardware accelerators are a trending topic in the HPC community, exploring the trade-offs of reconfigurable hardware-based ones in linear algebra libraries for high-performance systems, has not been deeply studied. Therefore, in this research, we aim to take...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidad Autónoma de Bucaramanga
2025-01-01
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| Series: | Revista Colombiana de Computación |
| Subjects: | |
| Online Access: | https://revistas.unab.edu.co/index.php/rcc/article/view/5276 |
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| Summary: | Although heterogeneous systems based on hardware accelerators are a trending topic in the HPC community, exploring the trade-offs of reconfigurable hardware-based ones in linear algebra libraries for high-performance systems, has not been deeply studied. Therefore, in this research, we aim to take advantage of FPGAs' reconfigurability, adaptability, and capacity to reduce power consumption to generate FPGA-based kernels in Ginkgo, a specialized high-performance linear algebra library for many-core systems. We generated 3 FPGA-based kernels for the CSR, SELLP, and SELL SpMV formats, and obtained speedups of at least 10x concerning CPU-based kernels. Furthermore, we demonstrated via a performance characterization study that FPGAs outperform general-purpose processors in terms of compute time.
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| ISSN: | 1657-2831 2539-2115 |