Energy-Efficient Low-Latency Signed Multiplier for FPGA-Based Hardware Accelerators.

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Abstract

Multiplication is one of the most extensively used arithmetic operations in a wide range of applications, such as multimedia processing and artificial neural networks. For such applications, multiplier is one of the major contributors to energy consumption, critical path delay, and resource utilization. These effects get more pronounced in field-programmable gate array (FPGA)-based designs. However, most of the state-of-the-art designs are done for ASIC-based systems. Furthermore, a few field-programmable gate array (FPGA)-based designs that exist are largely limited to unsigned numbers, which require extra circuits to support signed operations. To overcome these limitations for the FPGA-based implementations of applications utilizing signed numbers, this letter presents an area-optimized, low-latency, and energy-efficient architecture for an accurate signed multiplier. Compared to the Vivado area-optimized multiplier IP, our implementations offer up to 40.0%, 43.0%, and 70.0% reduction in terms of area, latency, and energy, respectively. The RTL implementations of our designs will be released as an open-source library at https://cfaed.tu-dresden.de/pd-downloads.

Details

OriginalspracheEnglisch
Aufsatznummer9094238
Seiten (von - bis)41-44
Seitenumfang4
FachzeitschriftIEEE Embed. Syst. Lett.
Jahrgang13
Ausgabenummer2
PublikationsstatusVeröffentlicht - Juni 2021
Peer-Review-StatusJa

Externe IDs

Scopus 85107056481

Schlagworte

Forschungsprofillinien der TU Dresden

Ziele für nachhaltige Entwicklung

Schlagwörter

  • Accelerator architectures, artificial neural networks (ANN), field-programmable gate arrays (FPGAs), fixed-point arithmetic, multiplying circuits