Occamy: A 432-Core Dual-Chiplet Dual-HBM2E 768-DP-GFLOP/s RISC-V System for 8-to-64-bit Dense and Sparse Computing in 12nm FinFET

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Auteurs principaux: Scheffler, Paul, Benz, Thomas, Potocnik, Viviane, Fischer, Tim, Colagrande, Luca, Wistoff, Nils, Zhang, Yichao, Bertaccini, Luca, Ottavi, Gianmarco, Eggimann, Manuel, Cavalcante, Matheus, Paulin, Gianna, Gürkaynak, Frank K., Rossi, Davide, Benini, Luca
Format: Preprint
Publié: 2025
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author Scheffler, Paul
Benz, Thomas
Potocnik, Viviane
Fischer, Tim
Colagrande, Luca
Wistoff, Nils
Zhang, Yichao
Bertaccini, Luca
Ottavi, Gianmarco
Eggimann, Manuel
Cavalcante, Matheus
Paulin, Gianna
Gürkaynak, Frank K.
Rossi, Davide
Benini, Luca
author_facet Scheffler, Paul
Benz, Thomas
Potocnik, Viviane
Fischer, Tim
Colagrande, Luca
Wistoff, Nils
Zhang, Yichao
Bertaccini, Luca
Ottavi, Gianmarco
Eggimann, Manuel
Cavalcante, Matheus
Paulin, Gianna
Gürkaynak, Frank K.
Rossi, Davide
Benini, Luca
contents ML and HPC applications increasingly combine dense and sparse memory access computations to maximize storage efficiency. However, existing CPUs and GPUs struggle to flexibly handle these heterogeneous workloads with consistently high compute efficiency. We present Occamy, a 432-Core, 768-DP-GFLOP/s, dual-HBM2E, dual-chiplet RISC-V system with a latency-tolerant hierarchical interconnect and in-core streaming units (SUs) designed to accelerate dense and sparse FP8-to-FP64 ML and HPC workloads. We implement Occamy's compute chiplets in 12 nm FinFET, and its passive interposer, Hedwig, in a 65 nm node. On dense linear algebra (LA), Occamy achieves a competitive FPU utilization of 89%. On stencil codes, Occamy reaches an FPU utilization of 83% and a technology-node-normalized compute density of 11.1 DP-GFLOP/s/mm2,leading state-of-the-art (SoA) processors by 1.7x and 1.2x, respectively. On sparse-dense linear algebra (LA), it achieves 42% FPU utilization and a normalized compute density of 5.95 DP-GFLOP/s/mm2, surpassing the SoA by 5.2x and 11x, respectively. On, sparse-sparse LA, Occamy reaches a throughput of up to 187 GCOMP/s at 17.4 GCOMP/s/W and a compute density of 3.63 GCOMP/s/mm2. Finally, we reach up to 75% and 54% FPU utilization on and dense (LLM) and graph-sparse (GCN) ML inference workloads. Occamy's RTL is freely available under a permissive open-source license.
format Preprint
id arxiv_https___arxiv_org_abs_2501_07330
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Occamy: A 432-Core Dual-Chiplet Dual-HBM2E 768-DP-GFLOP/s RISC-V System for 8-to-64-bit Dense and Sparse Computing in 12nm FinFET
Scheffler, Paul
Benz, Thomas
Potocnik, Viviane
Fischer, Tim
Colagrande, Luca
Wistoff, Nils
Zhang, Yichao
Bertaccini, Luca
Ottavi, Gianmarco
Eggimann, Manuel
Cavalcante, Matheus
Paulin, Gianna
Gürkaynak, Frank K.
Rossi, Davide
Benini, Luca
Hardware Architecture
ML and HPC applications increasingly combine dense and sparse memory access computations to maximize storage efficiency. However, existing CPUs and GPUs struggle to flexibly handle these heterogeneous workloads with consistently high compute efficiency. We present Occamy, a 432-Core, 768-DP-GFLOP/s, dual-HBM2E, dual-chiplet RISC-V system with a latency-tolerant hierarchical interconnect and in-core streaming units (SUs) designed to accelerate dense and sparse FP8-to-FP64 ML and HPC workloads. We implement Occamy's compute chiplets in 12 nm FinFET, and its passive interposer, Hedwig, in a 65 nm node. On dense linear algebra (LA), Occamy achieves a competitive FPU utilization of 89%. On stencil codes, Occamy reaches an FPU utilization of 83% and a technology-node-normalized compute density of 11.1 DP-GFLOP/s/mm2,leading state-of-the-art (SoA) processors by 1.7x and 1.2x, respectively. On sparse-dense linear algebra (LA), it achieves 42% FPU utilization and a normalized compute density of 5.95 DP-GFLOP/s/mm2, surpassing the SoA by 5.2x and 11x, respectively. On, sparse-sparse LA, Occamy reaches a throughput of up to 187 GCOMP/s at 17.4 GCOMP/s/W and a compute density of 3.63 GCOMP/s/mm2. Finally, we reach up to 75% and 54% FPU utilization on and dense (LLM) and graph-sparse (GCN) ML inference workloads. Occamy's RTL is freely available under a permissive open-source license.
title Occamy: A 432-Core Dual-Chiplet Dual-HBM2E 768-DP-GFLOP/s RISC-V System for 8-to-64-bit Dense and Sparse Computing in 12nm FinFET
topic Hardware Architecture
url https://arxiv.org/abs/2501.07330