[2606.02333] O-POPE: High-Frequency Pipelined Outer Product based GEMM acceleration with minimal buffering overhead

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Computer Science > Hardware Architecture

arXiv:2606.02333 (cs)

[Submitted on 1 Jun 2026]

Title:O-POPE: High-Frequency Pipelined Outer Product based GEMM acceleration with minimal buffering overhead

Authors:Danilo Cammarata, Angelo Garofalo, Luca Benini<br>View a PDF of the paper titled O-POPE: High-Frequency Pipelined Outer Product based GEMM acceleration with minimal buffering overhead, by Danilo Cammarata and 2 other authors

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Abstract:General matrix multiply (GEMM) dominates both execution time and energy consumption of modern machine learning (ML) workloads, placing increasing pressure on hardware efficiency. While quantization mitigates computational and data movement costs, accuracy-sensitive tasks such as training still require higher-precision floating-point formats. Existing floating-point GEMM accelerators face trade-offs between operating frequency, arithmetic utilization, and buffering overhead. This work presents O-POPE, a scalable outer-product engine that achieves concurrently high utilization, low overhead, and a fast operating frequency by repurposing floating-point unit (FPU) pipeline registers as buffers. This solution leverages the data-reuse advantages of output-stationary outer-product execution and enables 1 GHz (0.72 V) operation in 12 nm FINFET technology with less than 2% buffer area for a 2048-MACs configuration. Our evaluation shows that O-POPE achieves up to 99.97% FPU utilization and improves performance (1.33x), performance density by 9%, and energy efficiency by 8%, compared to state-of-the-art floating-point GEMM accelerators.

Comments:<br>To be published in 2026 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)

Subjects:

Hardware Architecture (cs.AR)

Cite as:<br>arXiv:2606.02333 [cs.AR]

(or<br>arXiv:2606.02333v1 [cs.AR] for this version)

https://doi.org/10.48550/arXiv.2606.02333

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arXiv-issued DOI via DataCite (pending registration)

Submission history<br>From: Danilo Cammarata Mr. [view email]<br>[v1]<br>Mon, 1 Jun 2026 14:44:05 UTC (2,252 KB)

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