Dustin: A 16-Cores Parallel Ultra-Low-Power Cluster With 2b-to-32b Fully Flexible Bit-Precision and Vector Lockstep Execution Mode

Computationally intensive algorithms such as Deep Neural Networks (DNNs) are becoming killer applications for edge devices. Porting heavily data-parallel algorithms on resource-constrained and battery-powered devices while retaining the flexibility granted by instruction processor-based architecture...

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Veröffentlicht in:IEEE transactions on circuits and systems. I, Regular papers Regular papers, 2023-06, Vol.70 (6), p.1-14
Hauptverfasser: Ottavi, Gianmarco, Garofalo, Angelo, Tagliavini, Giuseppe, Conti, Francesco, Mauro, Alfio Di, Benini, Luca, Rossi, Davide
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Sprache:eng
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Zusammenfassung:Computationally intensive algorithms such as Deep Neural Networks (DNNs) are becoming killer applications for edge devices. Porting heavily data-parallel algorithms on resource-constrained and battery-powered devices while retaining the flexibility granted by instruction processor-based architectures poses several challenges related to memory footprint, computational throughput, and energy efficiency. Low-bitwidth and mixed-precision arithmetic have been proven to be valid strategies for tackling these problems. We present Dustin, a fully programmable compute cluster integrating 16 RISC-V cores capable of 2-to 32-bit arithmetic and all possible mixed-precision combinations. In addition to a conventional Multiple-Instruction Multiple-Data (MIMD) processing paradigm, Dustin introduces a Vector Lockstep Execution Mode (VLEM) to minimize power consumption in highly data-parallel kernels. In VLEM, a single leader core fetches instructions and broadcasts them to the 15 follower cores. Clock gating Instruction Fetch (IF) stages and private caches of the follower cores leads to 38% power reduction. The cluster, implemented in 65 nm CMOS technology, achieves a peak performance of 58 GOPS and a peak efficiency of 1.15 TOPS/W.
ISSN:1549-8328
1558-0806
DOI:10.1109/TCSI.2023.3254810