activity
20232026
most citedITA: An Energy-Efficient Attention and Softmax Accelerator for Quantized Transformers

24 citations · 72 across the 11 of their papers we have counts for

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Showing cs.ARShow all

10 papers · 1 filter

cs.AR2026★ 1 cited

EPAC: The Last Dance

Filippo Mantovani, Fabio Banchelli, Pablo Vizcaino +36

This paper presents EPAC, a RISC-V-based accelerator chip developed within the European Processor Initiative (EPI) as part of a multi-year, multi-partner effort to build a European…

cs.AR2026

A Lightweight High-Throughput Collective-Capable NoC for Large-Scale ML Accelerators

Luca Colagrande, Lorenzo Leone, Chen Wu +3

The exponential increase in Machine Learning (ML) model size and complexity has driven unprecedented demand for high-performance acceleration systems. As technology scaling enables…

cs.AR2025

Toward Open-Source Chiplets for HPC and AI: Occamy and Beyond

Paul Scheffler, Thomas Benz, Tim Fischer +3

We present a roadmap for open-source chiplet-based RISC-V systems targeting high-performance computing and artificial intelligence, aiming to close the performance gap to proprieta…

cs.AR2025★ 7 cited

AraXL: A Physically Scalable, Ultra-Wide RISC-V Vector Processor Design for Fast and Efficient Computation on Long Vectors

Navaneeth Kunhi Purayil, Matteo Perotti, Tim Fischer +1

The ever-growing scale of data parallelism in today's HPC and ML applications presents a big challenge for computing architectures' energy efficiency and performance. Vector proces…

cs.AR2025★ 13 cited

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

Paul Scheffler, Thomas Benz, Viviane Potocnik +12

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…

cs.AR2024

ControlPULPlet: A Flexible Real-time Multi-core RISC-V Controller for 2.5D Systems-in-package

Alessandro Ottaviano, Robert Balas, Tim Fischer +3

The growing complexity of real-time control algorithms with increasing performance demands, along with the shift to 2.5D technology, drive the need for scalable controllers to mana…

cs.AR2024★ 16 cited

FlooNoC: A 645 Gbps/link 0.15 pJ/B/hop Open-Source NoC with Wide Physical Links and End-to-End AXI4 Parallel Multi-Stream Support

Tim Fischer, Michael Rogenmoser, Thomas Benz +2

The new generation of domain-specific AI accelerators is characterized by rapidly increasing demands for bulk data transfers, as opposed to small, latency-critical cache line trans…

cs.AR2024

Occamy: A 432-Core 28.1 DP-GFLOP/s/W 83% FPU Utilization Dual-Chiplet, Dual-HBM2E RISC-V-based Accelerator for Stencil and Sparse Linear Algebra Computations with 8-to-64-bit Floating-Point Support in 12nm FinFET

Gianna Paulin, Paul Scheffler, Thomas Benz +11

We present Occamy, a 432-core RISC-V dual-chiplet 2.5D system for efficient sparse linear algebra and stencil computations on FP64 and narrow (32-, 16-, 8-bit) SIMD FP data. Occamy…

cs.AR2023★ 24 cited

ITA: An Energy-Efficient Attention and Softmax Accelerator for Quantized Transformers

Gamze İslamoğlu, Moritz Scherer, Gianna Paulin +4

Transformer networks have emerged as the state-of-the-art approach for natural language processing tasks and are gaining popularity in other domains such as computer vision and aud…

cs.AR2023★ 11 cited

FlooNoC: A Multi-Tbps Wide NoC for Heterogeneous AXI4 Traffic

Tim Fischer, Michael Rogenmoser, Matheus Cavalcante +2

Meeting the staggering bandwidth requirements of today's applications challenges the traditional narrow and serialized NoCs, which hit hard bounds on the maximum operating frequenc…