Fine Grain 3D Integration for Microarchitecture Design Through Cube Packing Exploration
Yongxiang Liu, Yuchun Ma, Eren Kurshan, Glenn Reinman, Jason Cong

TL;DR
This paper introduces a novel cube packing engine for fine grain 3D integration in microarchitecture design, enabling optimized physical and architectural exploration for improved performance, power, and thermal management.
Contribution
It presents a new cube packing approach that allows multi-layer logical blocks, enhancing 3D IC design exploration with integrated physical and architectural optimization tools.
Findings
36% performance improvement over 2D designs
14% performance gain over single-layer 3D designs
Up to 30% power reduction with multi-layer blocks
Abstract
Most previous 3D IC research focused on stacking traditional 2D silicon layers, so the interconnect reduction is limited to inter-block delays. In this paper, we propose techniques that enable efficient exploration of the 3D design space where each logical block can span more than one silicon layers. Although further power and performance improvement is achievable through fine grain 3D integration, the necessary modeling and tool infrastructure has been mostly missing. We develop a cube packing engine which can simultaneously optimize physical and architectural design for effective utilization of 3D in terms of performance, area and temperature. Our experimental results using a design driver show 36% performance improvement (in BIPS) over 2D and 14% over 3D with single layer blocks. Additionally multi-layer blocks can provide up to 30% reduction in power dissipation compared to the…
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