Gohil, VarunVarunGohilWalia, SumitSumitWaliaMekie, JoyceeJoyceeMekieAwasthi, ManuManuAwasthi2025-08-312025-08-312021-10-0110.1109/TCSII.2021.30722172-s2.0-85104200016https://d8.irins.org/handle/IITG2025/25260Today, almost all computer systems use IEEE-754 floating point to represent real numbers. Recently, posit was proposed as an alternative to IEEE-754 floating point as it has better accuracy and a larger dynamic range. The configurable nature of posit, with varying number of regime and exponent bits, has acted as a deterrent to its adoption. To overcome this shortcoming, we propose fixed-posit representation where the number of regime and exponent bits are fixed, and present the design of a fixed-posit multiplier. We evaluate the fixed-posit multiplier on error-resilient applications of AxBench and OpenBLAS benchmarks as well as neural networks. The proposed fixed-posit multiplier has 47%, 38.5%, 22% savings for power, area and delay respectively when compared to posit multipliers and up to 70%, 66%, 26% savings in power, area and delay respectively when compared to 32-bit IEEE-754 multiplier. These savings are accompanied with minimal output quality loss (1.2% average relative error) across OpenBLAS and AxBench workloads. Further, for neural networks like ResNet-18 on ImageNet we observe a negligible accuracy loss (0.12%) on using the fixed-posit multiplier.falseIEEE-754 floating point | intel pin | multipliers | Posit | power and error analysisArticle155837913341-3345October 202121arJournal12WOS:000698857900034