FPGA-based accelerators have recently evolved as strong competitors to the traditional GPU-based accelerators in modern high-performance computing systems. They offer both high computational capabilities and considerably lower energy consumption. High-level synthesis (HLS) can be used to overcome the main hurdle in the mainstream usage of the FPGA-based accelerators, i.e., the complexity of their design flow. HLS enables the designers to program an FPGA directly by using high-level languages, e.g., C, C++, SystemC, and OpenCL. This paper presents an HLS-based FPGA implementation of several algorithms from a variety of application domains. A performance comparison in terms of execution time, energy, and power consumption with some high-end GPUs is performed as well. The algorithms have been modeled in OpenCL for both GPU and FPGA implementation. We conclude that FPGAs are much more energy-efficient than GPUs in all the test cases that we considered. Moreover, FPGAs can sometimes be faster than GPUs by using an FPGA-specific OpenCL programming style and utilizing a variety of appropriate HLS directives.
Efficient FPGA Implementation of OpenCL High-Performance Computing Applications via High-Level Synthesis / Muslim, Fahad Bin; Ma, Liang; Roozmeh, Mehdi; Lavagno, Luciano. - In: IEEE ACCESS. - ISSN 2169-3536. - ELETTRONICO. - 5:(2017), pp. 2747-2762. [10.1109/ACCESS.2017.2671881]
Efficient FPGA Implementation of OpenCL High-Performance Computing Applications via High-Level Synthesis
MA, LIANG;ROOZMEH, MEHDI;LAVAGNO, Luciano
2017
Abstract
FPGA-based accelerators have recently evolved as strong competitors to the traditional GPU-based accelerators in modern high-performance computing systems. They offer both high computational capabilities and considerably lower energy consumption. High-level synthesis (HLS) can be used to overcome the main hurdle in the mainstream usage of the FPGA-based accelerators, i.e., the complexity of their design flow. HLS enables the designers to program an FPGA directly by using high-level languages, e.g., C, C++, SystemC, and OpenCL. This paper presents an HLS-based FPGA implementation of several algorithms from a variety of application domains. A performance comparison in terms of execution time, energy, and power consumption with some high-end GPUs is performed as well. The algorithms have been modeled in OpenCL for both GPU and FPGA implementation. We conclude that FPGAs are much more energy-efficient than GPUs in all the test cases that we considered. Moreover, FPGAs can sometimes be faster than GPUs by using an FPGA-specific OpenCL programming style and utilizing a variety of appropriate HLS directives.File | Dimensione | Formato | |
---|---|---|---|
07859319.pdf
accesso aperto
Descrizione: Articolo principale
Tipologia:
2. Post-print / Author's Accepted Manuscript
Licenza:
PUBBLICO - Tutti i diritti riservati
Dimensione
5.05 MB
Formato
Adobe PDF
|
5.05 MB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2669854
Attenzione
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo