activity
20182021
most citedFPnew: An Open-Source Multi-Format Floating-Point Unit Architecture for Energy-Proportional Transprecision Computing

1 citations · 1 across the 4 of their papers we have counts for

collaborators

9 papers

cs.DC2021

Implementing CNN Layers on the Manticore Cluster-Based Many-Core Architecture

Andreas Kurth, Fabian Schuiki, Luca Benini

This document presents implementations of fundamental convolutional neural network (CNN) layers on the Manticore cluster-based many-core architecture and discusses their characteri…

cs.AR2020

Indirection Stream Semantic Register Architecture for Efficient Sparse-Dense Linear Algebra

Paul Scheffler, Florian Zaruba, Fabian Schuiki +2

Sparse-dense linear algebra is crucial in many domains, but challenging to handle efficiently on CPUs, GPUs, and accelerators alike; multiplications with sparse formats like CSR an…

cs.AR2020

Manticore: A 4096-core RISC-V Chiplet Architecture for Ultra-efficient Floating-point Computing

Florian Zaruba, Fabian Schuiki, Luca Benini

Data-parallel problems demand ever growing floating-point (FP) operations per second under tight area- and energy-efficiency constraints. In this work, we present Manticore, a gene…

cs.AR20201 cited

FPnew: An Open-Source Multi-Format Floating-Point Unit Architecture for Energy-Proportional Transprecision Computing

Stefan Mach, Fabian Schuiki, Florian Zaruba +1

The slowdown of Moore's law and the power wall necessitates a shift towards finely tunable precision (a.k.a. transprecision) computing to reduce energy footprint. Hence, we need ci…

cs.PL2020

LLHD: A Multi-level Intermediate Representation for Hardware Description Languages

Fabian Schuiki, Andreas Kurth, Tobias Grosser +1

Modern Hardware Description Languages (HDLs) such as SystemVerilog or VHDL are, due to their sheer complexity, insufficient to transport designs through modern circuit design flows…

cs.AR2020

Snitch: A tiny Pseudo Dual-Issue Processor for Area and Energy Efficient Execution of Floating-Point Intensive Workloads

Florian Zaruba, Fabian Schuiki, Torsten Hoefler +1

Data-parallel applications, such as data analytics, machine learning, and scientific computing, are placing an ever-growing demand on floating-point operations per second on emergi…