Abstract: Considering that Von Neumann architecture has bottlenecks in both speed and power consumption, in-memory computation is a promising solution. The in-memory computation needs to be carried ...

Microsoft has teamed up with Barclays on a novel approach to tackling artificial intelligence (AI) and optimisation problems based on a scalable analogue optical computer (AOC) architecture, designed ...

CLA is a simple toy library for basic vector/matrix operations in C. This project main goal is to learn the foundations of CUDA, and Python bindings, using ctypes as a wrapper, through simple Linear ...

Abstract: Structured sparsity has been proposed as an efficient way to prune the complexity of Machine Learning (ML) applications and to simplify the handling of sparse data in hardware. Accelerating ...

ABSTRACT: Introduction: Malaria control needs the development of complementary and/or alternative strategies such as biological controls. Despite, malaria’s current control efforts, the spread and the ...

I'm trying to restrict the problem, but for now it seems that with newer numpy versions on x64 certain complex products return different results depending on whether the operands are wrapped in a ...

Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in Python ...