TeraNoC: A Multi-Channel 32-bit Fine-Grained, Hybrid Mesh-Crossbar NoC for Efficient Scale-up of 1000+ Core Shared-L1-Memory Clusters

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Main Authors: Zhang, Yichao, Fu, Zexin, Fischer, Tim, Li, Yinrong, Bertuletti, Marco, Benini, Luca
Format: Preprint
Published: 2025
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author Zhang, Yichao
Fu, Zexin
Fischer, Tim
Li, Yinrong
Bertuletti, Marco
Benini, Luca
author_facet Zhang, Yichao
Fu, Zexin
Fischer, Tim
Li, Yinrong
Bertuletti, Marco
Benini, Luca
contents A key challenge in on-chip interconnect design is to scale up bandwidth while maintaining low latency and high area efficiency. 2D-meshes scale with low wiring area and congestion overhead; however, their end-to-end latency increases with the number of hops, making them unsuitable for latency-sensitive core-to-L1-memory access. On the other hand, crossbars offer low latency, but their routing complexity grows quadratically with the number of I/Os, requiring large physical routing resources and limiting area-efficient scalability. This two-sided interconnect bottleneck hinders the scale-up of many-core, low-latency, tightly coupled shared-memory clusters, pushing designers toward instantiating many smaller and loosely coupled clusters, at the cost of hardware and software overheads. We present TeraNoC, an open-source, hybrid mesh-crossbar on-chip interconnect that offers both scalability and low latency, while maintaining very low routing overhead. The topology, built on 32bit word-width multi-channel 2D-meshes and crossbars, enables the area-efficient scale-up of shared-memory clusters. A router remapper is designed to balance traffic load across interconnect channels. Using TeraNoC, we build a cluster with 1024 single-stage, single-issue cores that share a 4096-banked L1 memory, implemented in 12nm technology. The low interconnect stalls enable high compute utilization of up to 0.85 IPC in compute-intensive, data-parallel key GenAI kernels. TeraNoC only consumes 7.6\% of the total cluster power in kernels dominated by crossbar accesses, and 22.7\% in kernels with high 2D-mesh traffic. Compared to a hierarchical crossbar-only cluster, TeraNoC reduces die area by 37.8\% and improves area efficiency (GFLOP/s/mm2) by up to 98.7\%, while occupying only 10.9\% of the logic area.
format Preprint
id arxiv_https___arxiv_org_abs_2508_02446
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle TeraNoC: A Multi-Channel 32-bit Fine-Grained, Hybrid Mesh-Crossbar NoC for Efficient Scale-up of 1000+ Core Shared-L1-Memory Clusters
Zhang, Yichao
Fu, Zexin
Fischer, Tim
Li, Yinrong
Bertuletti, Marco
Benini, Luca
Distributed, Parallel, and Cluster Computing
A key challenge in on-chip interconnect design is to scale up bandwidth while maintaining low latency and high area efficiency. 2D-meshes scale with low wiring area and congestion overhead; however, their end-to-end latency increases with the number of hops, making them unsuitable for latency-sensitive core-to-L1-memory access. On the other hand, crossbars offer low latency, but their routing complexity grows quadratically with the number of I/Os, requiring large physical routing resources and limiting area-efficient scalability. This two-sided interconnect bottleneck hinders the scale-up of many-core, low-latency, tightly coupled shared-memory clusters, pushing designers toward instantiating many smaller and loosely coupled clusters, at the cost of hardware and software overheads. We present TeraNoC, an open-source, hybrid mesh-crossbar on-chip interconnect that offers both scalability and low latency, while maintaining very low routing overhead. The topology, built on 32bit word-width multi-channel 2D-meshes and crossbars, enables the area-efficient scale-up of shared-memory clusters. A router remapper is designed to balance traffic load across interconnect channels. Using TeraNoC, we build a cluster with 1024 single-stage, single-issue cores that share a 4096-banked L1 memory, implemented in 12nm technology. The low interconnect stalls enable high compute utilization of up to 0.85 IPC in compute-intensive, data-parallel key GenAI kernels. TeraNoC only consumes 7.6\% of the total cluster power in kernels dominated by crossbar accesses, and 22.7\% in kernels with high 2D-mesh traffic. Compared to a hierarchical crossbar-only cluster, TeraNoC reduces die area by 37.8\% and improves area efficiency (GFLOP/s/mm2) by up to 98.7\%, while occupying only 10.9\% of the logic area.
title TeraNoC: A Multi-Channel 32-bit Fine-Grained, Hybrid Mesh-Crossbar NoC for Efficient Scale-up of 1000+ Core Shared-L1-Memory Clusters
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2508.02446