tag: algorithm

An Empirical Comparison Of Optimizers For Quantum Machine Learning With SPSA-Based Gradients
By Fraunhofer IIS/EAS - 14 Feb, 2024 - Comments: 0

Variational quantum algorithms (VQAs) have attracted a lot of attention from the quantum computing community for the last few years. Their hybrid quantum-classical nature with relatively shallow quantum circuits makes them a promising platform for demonstrating the capabilities of noisy intermediate scale quantum (NISQ) devices. Although the classical machine learning community focuses on gradi... » read more

Digital Neuromorphic Processor: Algorithm-HW Co-design (imec / KU Leuven)
By Technical Paper Link - 11 Apr, 2023 - Comments: 0

A technical paper titled "Open the box of digital neuromorphic processor: Towards effective algorithm-hardware co-design" was published by researchers at imec and KU Leuven. "In this work, we open the black box of the digital neuromorphic processor for algorithm designers by presenting the neuron processing instruction set and detailed energy consumption of the SENeCA neuromorphic architect... » read more

Accelerate The Algorithm To Silicon Development With Stratus HLS
By Cadence - 21 Dec, 2022 - Comments: 0

Growth in demand for artificial intelligence (AI) and digital signal processing (DSP) applications, coupled with advances in semiconductor process technology, drives increasingly denser SoCs. These complex SoCs further challenge the design team’s ability to meet performance, power, and area (PPA) goals within tight time-to-market windows. We need automated and targeted solutions that efficien... » read more

Communication Algorithm-Architecture Co-Design for Distributed Deep Learning
By Technical Paper Link - 14 Jun, 2021 - Comments: 0

"Abstract—Large-scale distributed deep learning training has enabled developments of more complex deep neural network models to learn from larger datasets for sophisticated tasks. In particular, distributed stochastic gradient descent intensively invokes all-reduce operations for gradient update, which dominates communication time during iterative training epochs. In this work, we identify th... » read more

Are Better Machine Training Approaches Ahead?
By Bryon Moyer - 01 Jul, 2020 - Comments: 1

We live in a time of unparalleled use of machine learning (ML), but it relies on one approach to training the models that are implemented in artificial neural networks (ANNs) — so named because they’re not neuromorphic. But other training approaches, some of which are more biomimetic than others, are being developed. The big question remains whether any of them will become commercially viab... » read more

Using Machine Learning To Break Down Silos
By Ed Sperling - 13 Nov, 2019 - Comments: 0

Jeff David, vice president of AI solutions at PDF Solutions, talks with Semiconductor Engineering about where machine learning can be applied into semiconductor manufacturing, how it can be used to break down silos around different process steps, how active learning works with human input to tune algorithms, and why it’s important to be able to choose different different algorithms for differ... » read more

Even good bots fight: The case of Wikipedia (Oxford & Alan Turing Institute)
By Technical Paper Link - 06 Mar, 2017 - Comments: 0

Source: University Of Oxford published via PLOS ONE, Milena Tsvetkova, Ruth García-Gavilanes, Luciano Floridi, Taha Yasseri "The research paper, published in PLOS ONE, concludes that bots are more like humans than you might expect as they appear to behave differently in culturally distinct online environments. The paper says the findings are a warning to those using artificial intelligence ... » read more

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