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MBus: an ultra-low power interconnect bus for next generation nanopower systems

Published: 13 June 2015 Publication History

Abstract

As we show in this paper, I/O has become the limiting factor in scaling down size and power toward the goal of invisible computing. Achieving this goal will require composing optimized and specialized---yet reusable---components with an interconnect that permits tiny, ultra-low power systems. In contrast to today's interconnects which are limited by power-hungry pull-ups or high-overhead chip-select lines, our approach provides a superset of common bus features but at lower power, with fixed area and pin count, using fully synthesizable logic, and with surprisingly low protocol overhead.
We present MBus, a new 4-pin, 22.6 pJ/bit/chip chip-to-chip interconnect made of two "shoot-through" rings. MBus facilitates ultra-low power system operation by implementing automatic power-gating of each chip in the system, easing the integration of active, inactive, and activating circuits on a single die. In addition, we introduce a new bus primitive: power oblivious communication, which guarantees message reception regardless of the recipient's power state when a message is sent. This disentangles power management from communication, greatly simplifying the creation of viable, modular, and heterogeneous systems that operate on the order of nanowatts.
To evaluate the viability, power, performance, overhead, and scalability of our design, we build both hardware and software implementations of MBus and show its seamless operation across two FPGAs and twelve custom chips from three different semiconductor processes. A three-chip, 2.2mm3 MBus system draws 8nW of total system standby power and uses only 22.6 pJ/bit/chip for communication. This is the lowest power for any system bus with MBus's feature set.

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        cover image ACM Conferences
        ISCA '15: Proceedings of the 42nd Annual International Symposium on Computer Architecture
        June 2015
        768 pages
        ISBN:9781450334020
        DOI:10.1145/2749469
        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Published: 13 June 2015

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        • (2022)Energy-Aware Adaptive Multi-Exit Neural Network Inference Implementation for a Millimeter-Scale Sensing SystemIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2022.317130830:7(849-859)Online publication date: Jul-2022
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