English

ControlPULPlet: A Flexible Real-time Multi-core RISC-V Controller for 2.5D Systems-in-package

Hardware Architecture 2025-08-14 v2

Abstract

The growing complexity of real-time control algorithms with increasing performance demands, along with the shift to 2.5D technology, drive the need for scalable controllers to manage chiplets' coupled operation in 2.5D systems-in-package. These controllers must offer real-time computing capabilities, as well as System-in-package (SiP) compatible IO interfaces for communicating with the controlled dies. Due to real-time constraints, a key challenge is minimizing the performance penalty of die-to-die communication with respect to native on-chip control interfaces. We address this challenge with ControlPULPlet, an open-source, real-time multi-core RISC-V controller designed specifically for SiP integration. ControlPULPlet features a 32-bit CV32RT core for fast interrupt handling and a specialized direct memory access engine to automate periodic sensor readout. A tightly-coupled programmable multi-core cluster for acceleration of advanced control algorithms is integrated through a dedicated AXI4 port. A flexible AXI4-compatible die-to-die (D2D) link enables efficient communication in 2.5D SiPs. We implemented and fabricated ControlPULPlet as a silicon demonstrator called Kairos in TSMC's 65nm CMOS. Kairos runs model predictive control algorithms at up to 290 MHz in a 30 mW power envelope. The D2D link attains a peak duplex transfer rate of 51 Gbit/s at 200 MHz, at the minimal costs of just 7.6 kGE in PHY area per channel, adding just 2.9% to the total system area.

Keywords

Cite

@article{arxiv.2410.15985,
  title  = {ControlPULPlet: A Flexible Real-time Multi-core RISC-V Controller for 2.5D Systems-in-package},
  author = {Alessandro Ottaviano and Robert Balas and Tim Fischer and Thomas Benz and Andrea Bartolini and Luca Benini},
  journal= {arXiv preprint arXiv:2410.15985},
  year   = {2025}
}

Comments

14 pages, 17 figures, 2 tables; accepted for publication in the IEEE Transactions on Very Large Scale Integration Systems (TVLSI)

R2 v1 2026-06-28T19:29:39.523Z