[HTML][HTML] Design-time methodology for optimizing mixed-precision CPU architectures on FPGA
Approximate computing can significantly reduce the energy consumption of computing
systems. Mixed-precision hardware architectures and precision-tuning tools for software …
systems. Mixed-precision hardware architectures and precision-tuning tools for software …
Cost-effective fixed-point hardware support for RISC-V embedded systems
D Zoni, A Galimberti - Journal of Systems Architecture, 2022 - Elsevier
With the ever-increasing energy-efficiency requirements for the computing platforms at the
edge, precision tuning techniques highlight the possibility of improving the efficiency of …
edge, precision tuning techniques highlight the possibility of improving the efficiency of …
Towards extreme scale technologies and accelerators for eurohpc hw/sw supercomputing applications for exascale: the textarossa approach
In the near future, Exascale systems will need to bridge three technology gaps to achieve
high performance while remaining under tight power constraints: energy efficiency and …
high performance while remaining under tight power constraints: energy efficiency and …
A low-power transprecision floating-point cluster for efficient near-sensor data analytics
Recent applications in low-power (1-20 mW) near-sensor computing require the adoption of
floating-point arithmetic to reconcile high precision results with a wide dynamic range. In this …
floating-point arithmetic to reconcile high precision results with a wide dynamic range. In this …
Hardware and software support for mixed precision computing: a roadmap for embedded and hpc systems
Mixed precision is an approximate computing technique that can be used to trade-off
computation accuracy for performance and/or energy. It can be applied to many error …
computation accuracy for performance and/or energy. It can be applied to many error …
Adaptive R-peak detection on wearable ECG sensors for high-intensity exercise
Objective: Continuous monitoring of biosignals via wearable sensors has quickly expanded
in the medical and wellness fields. At rest, automatic detection of vital parameters is …
in the medical and wellness fields. At rest, automatic detection of vital parameters is …
Optimization of the fixed-point representation of measurement data for intelligent measurement systems
The development of intelligent measurement systems by implementing AI (artificial
intelligence) algorithms on edge sensor nodes is very topical. Due to very limited hardware …
intelligence) algorithms on edge sensor nodes is very topical. Due to very limited hardware …
An efficient multi-format low-precision floating-point multiplier
HA Kermani, AAE Zarandi - Sustainable Computing: Informatics and …, 2024 - Elsevier
Low-precision computing has emerged as a promising technology to enhance performance
in modern applications like deep neural network training and scientific computing. However …
in modern applications like deep neural network training and scientific computing. However …
Textarossa: Towards extreme scale technologies and accelerators for eurohpc hw/sw supercomputing applications for exascale
To achieve high performance and high energy efficiency on near-future exascale computing
systems, three key technology gaps needs to be bridged. These gaps include: energy …
systems, three key technology gaps needs to be bridged. These gaps include: energy …
Analysis of 32-bit Fixed Point Quantizer in the Wide Variance Range for the Laplacian Source
Z Perić, A Jovanović, M Dinčić, M Savić… - … and Services in …, 2021 - ieeexplore.ieee.org
The main goal of this paper is to examine the possibility of using the 32-bit fixed-point format
to represent the weights of neural networks (NN) instead of the standardly used 32-bit …
to represent the weights of neural networks (NN) instead of the standardly used 32-bit …