110 citations · 132 across the 4 of their papers we have counts for
6 papers
MiniFloat-NN and ExSdotp: An ISA Extension and a Modular Open Hardware Unit for Low-Precision Training on RISC-V cores
Luca Bertaccini, Gianna Paulin, Tim Fischer +2
Low-precision formats have recently driven major breakthroughs in neural network (NN) training and inference by reducing the memory footprint of the NN models and improving the ene…
Vega: A 10-Core SoC for IoT End-Nodes with DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode
Davide Rossi, Francesco Conti, Manuel Eggimann +9
The Internet-of-Things requires end-nodes with ultra-low-power always-on capability for a long battery lifetime, as well as high performance, energy efficiency, and extreme flexibi…
A transprecision floating-point cluster for efficient near-sensor data analytics
Fabio Montagna, Stefan Mach, Simone Benatti +5
Recent applications in the domain of near-sensor computing require the adoption of floating-point arithmetic to reconcile high precision results with a wide dynamic range. In this…
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…
An 826 MOPS, 210 uW/MHz Unum ALU in 65 nm
Florian Glaser, Stefan Mach, Abbas Rahimi +3
To overcome the limitations of conventional floating-point number formats, an interval arithmetic and variable-width storage format called universal number (unum) has been recently…
A Transprecision Floating-Point Platform for Ultra-Low Power Computing
Giuseppe Tagliavini, Stefan Mach, Davide Rossi +2
In modern low-power embedded platforms, floating-point (FP) operations emerge as a major contributor to the energy consumption of compute-intensive applications with large dynamic…