cd /news/ai-research/closing-the-gap-between-float-and-po… · home topics ai-research article
[ARTICLE · art-138178] src=arxiv.org ↗ pub= topic=ai-research verified=true sentiment=↑ positive

Closing the Gap Between Float and Posit Hardware Efficiency

A March 2, 2026 arXiv paper by Aditya Anirudh Jonnalagadda proposes the b-posit, a bounded posit format that caps the regime field at 6 bits and reports 79 percent lower power consumption, 71 percent smaller area, and 60 percent reduced latency for 32-bit decoders versus standard posit decoders. The 32-bit b-posit encoder cuts power by 68 percent, area by 46 percent, and delay by 44 percent, with the design matching or exceeding IEEE-compliant 32-bit floating-point performance and scaling better at 64-bit. The author argues the b-posit should influence future revisions of the Posit Standard (2022).

read2 min views2 publishedSep 23, 2026
Closing the Gap Between Float and Posit Hardware Efficiency
Image: source
  [Submitted on 2 Mar 2026]


[View PDF](https://arxiv.org/pdf/2603.01615)

[HTML (experimental)](https://arxiv.org/html/2603.01615v1)

Abstract:The b-posit, or bounded posit, is a variation of the posit format designed for high performance computing (HPC) and AI applications. Unlike traditional floating-point formats (floats), posits use variable-length fields for exponent scaling and significand, providing better efficiency for the same bit width. However, this flexibility introduces high worst-case overhead in decode-encode logic, exceeding the cost of handling subnormals for floats. To address this, the b-posit restricts the regime field to a 6-bit limit, reducing variability in regime and fraction sizes. With an exponent size eS of 5 bits, the dynamic range is $2^{-192}$ to $2^{192}$ (about $10^{-58}$ to $10^{58}$) and the quire size is 800 bits, for any precision $n>12$. This constraint improves numerical properties and simplifies hardware implementation by allowing decode-encode operations with basic multiplexers. Our 32-bit b-posit decoder circuits achieve significant improvements: 79 percent less power consumption, 71 percent smaller area, and 60 percent reduced latency compared to standard posit decoders. The 32-bit b-posit encoder shows 68 percent lower power usage, 46 percent less area, and 44 percent shorter delay. The proposed b-posit hardware exhibits superior scalability with increasing bit widths, outperforming standard posit hardware at higher precisions, with even greater advantages at 64-bit. Notably, the b-posit decode-encode hardware matches or exceeds IEEE compliant 32-bit floating-point performance, offering faster and smaller area implementation, with slight increase in worst-case power due to higher speed. The b-posit hardware design provides the clean mathematical behavior and higher accuracy of posits versus IEEE floats without the power, area, or latency costs observed for the Posit Standard (2022). We believe the b-posit should influence future standard revisions.

Submission history #

From: Aditya Anirudh Jonnalagadda [
[view email](https://arxiv.org/show-email/a3f9fe4b/2603.01615)]

**[v1]** Mon, 2 Mar 2026 08:44:32 UTC (896 KB)

References & Citations

...

Bibliographic Explorer

(What is the Explorer?) Connected Papers

(What is Connected Papers?) Litmaps

(What is Litmaps?) scite Smart Citations

(What are Smart Citations?) alphaXiv

(What is alphaXiv?) CatalyzeX Code Finder for Papers

(What is CatalyzeX?) DagsHub

(What is DagsHub?) Gotit.pub

(What is GotitPub?) Hugging Face

(What is Huggingface?) ScienceCast

(What is ScienceCast?) Influence Flower

(What are Influence Flowers?) CORE Recommender

(What is CORE?) arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

── more in #ai-research 4 stories · sorted by recency
── more on @aditya anirudh jonnalagadda 3 stories trending now
sponsored brought to you by zahid.host 4,200+ EU-deployed projects
reading about agents? ship yours in a single git push.

Run your AI side-project on zahid.host

EU-based hosting, git-push deploys, automatic HTTPS, no cold starts. Free tier with a custom domain — perfect for shipping the agent you just read about.

$git push zahid main
Live at https://your-agent.zahid.host
Get free account → Pricing
from €0/mo · no card required
LIVE [news/closing-the-gap-betw…] indexed:0 read:2min 2026-09-23 ·