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SnackNoC: Processing in the Communication Layer
Conference proceeding

SnackNoC: Processing in the Communication Layer

Karthik Sangaiah, Michael Lui, Ragh Kuttappa, Baris Taskin, Mark Hempstead and IEEE
2020 IEEE INTERNATIONAL SYMPOSIUM ON HIGH PERFORMANCE COMPUTER ARCHITECTURE (HPCA 2020), pp 461-473
01 Jan 2020
DOI: https://doi.org/10.1109/HPCA47549.2020.00045

Abstract

Computer Science Computer Science, Hardware & Architecture Science & Technology Technology
In this work, we propose and evaluate a Network-on-Chip (NoC) augmented with light-weight processing elements to provide a lean dataflow-style system. We show that contemporary NoC routers can frequently experience long periods of idle time, with less than 10% link utilization in HPC applications. By repurposing the temporal and spatial slack of the NoC, the proposed platform, SnackNoC, is able to compute linear algebra kernels efficiently within the communication layer with minimal additional resource costs. SnackNoC 'Snack' application kernels are programmed with a producer-consumer data model that uses the NoC slack to store and transmit intermediate data between processing elements. SnackNoC is demonstrated in a multi-program environment that continually executes linear algebra kernels on the NoC simultaneously with chip multiprocessor (CMP) applications on the processor cores. Linear algebra kernels are computed up to 6.15x faster on SnackNoC compared to an Intel Haswell EPx86 processing core. The cost of executing 'snack' kernels in parallel to the CMP applications is a minimal runtime impact of 0.01% to 0.83% due to higher link utilization, and an uncore area overhead of 1.1%.

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7 citations in Web of Science
11 citations in Scopus

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Collaboration types
Domestic collaboration
Web of Science research areas
Computer Science, Hardware & Architecture
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