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Datum
2021Typ
- Conference Paper
ETH Bibliographie
yes
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Abstract
In the Internet-Of-Things (IoT) domain, microcontrollers (MCUs) are used to collect and process data coming from sensors and transmit them to the cloud. Applications that require the range and precision of floating-point (FP) arithmetic can be implemented using efficient hardware floating-point units (FPUs) or by using software emulation. FPUs optimize performance and code size, whilst software emulation minimizes the hardware cost. We present a new area-optimized, IEEE 754-compliant RISC-V FPU (Tiny-FPU), and we explore the area, code size, performance, power, and energy efficiency of three different implementations of the RISC-V Instruction Set Architecture double and single-precision FP extensions on an MCU-class processor. We show that Tiny-FPU, in its double and single-precision versions, is respectively 54% and 37% smaller than a double and single-precision FPU optimized for performance and energy efficiency. When coupling a RISC-V core with Tiny-FPU, we achieve up to 18.5x and 15.5x speedups with respect to the same core emulating FP operations via software. Mehr anzeigen
Publikationsstatus
publishedExterne Links
Buchtitel
2021 IEEE International Symposium on Circuits and Systems (ISCAS)Seiten / Artikelnummer
Verlag
IEEEKonferenz
Organisationseinheit
03996 - Benini, Luca / Benini, Luca
ETH Bibliographie
yes
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