78 citations · 225 across the 19 of their papers we have counts for
4 papers · 1 filter
Spatzformer: An Efficient Reconfigurable Dual-Core RISC-V V Cluster for Mixed Scalar-Vector Workloads
Matteo Perotti, Michele Raeber, Mattia Sinigaglia +3
Multi-core vector processor architectures excel in handling computationally intensive vectorizable tasks but struggle to achieve optimal resource utilization when facing sequential…
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…
TeraPool-SDR: An 1.89TOPS 1024 RV-Cores 4MiB Shared-L1 Cluster for Next-Generation Open-Source Software-Defined Radios
Yichao Zhang, Marco Bertuletti, Samuel Riedel +3
Radio Access Networks (RAN) workloads are rapidly scaling up in data processing intensity and throughput as the 5G (and beyond) standards grow in number of antennas and sub-carrier…
MX: Enhancing RISC-V's Vector ISA for Ultra-Low Overhead, Energy-Efficient Matrix Multiplication
Matteo Perotti, Yichao Zhang, Matheus Cavalcante +2
Dense Matrix Multiplication (MatMul) is arguably one of the most ubiquitous compute-intensive kernels, spanning linear algebra, DSP, graphics, and machine learning applications. Th…