This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

Abstract: The advancements in computational techniques regarding parallel computing and machine learning are revolutionizing stock market prediction, This study explores the effectiveness of parallel ...

Not only do professionals and students need to manipulate and process data, but they also need to communicate with hardware such as smart thermostats, doorbell cameras, smart lighting, and more.

PyPRS is a Python software package specifically developed to solve large-scale ranking and selection (R&S) problems in parallel computing environments. The underlying parallel computing framework is ...

Google DeepMind recently released GenAI Processors, a lightweight, open-source Python library built to simplify the orchestration of generative AI workflows—especially those involving real-time ...

Figure 1. Ultra-high parallel optical computing integrated chip - "Liuxing-I". High-detail view of an ultra-high parallelism optical computing integrated chip – “Liuxing-I”, showcasing the packaged ...

Python is a high-level programming language known for its simplicity, readability, and flexibility. Created by Guido van Rossum and first released in 1991, Python has since become one of the most ...

Parallel computing with CUDA to implement the heat spreading equation in 2 dimensions in the case of a metal plate starting with a circular hotspot in the middle of it. The programming language used ...

We introduce an open-source Python package for the analysis of large-scale electrophysiological data, named SyNCoPy, which stands for Systems Neuroscience Computing in Python. The package includes ...

In this study, we delve into the realm of efficient Big Data Engineering and Extract, Transform, Load (ETL) processes within the healthcare sector, leveraging the robust foundation provided by the ...