The technology uses predictive algorithms to identify frequently accessed data and move it between flash storage and high-speed memory in real time, reducing the amount of expensive DRAM a data center ...

Abstract: Neuromorphic chips with multi-core architecture are considered to be of great potential for the next generation of artificial intelligence (AI) chips because of the avoidance of the memory ...

Mt-KaHyPar is a shared-memory algorithm for partitioning graphs and hypergraphs. The balanced (hyper)graph partitioning problem asks for a partition of the node set of a (hyper)graph into k disjoint ...

Abstract: As the processing of large-scale graphs on a single device is infeasible without partitioning, graph partitioning algorithms are essential for various algorithms and distributed computing ...

The algorithm relies on the Kac-Ward formalism, a mathematical method that allows exact computation of partition functions for planar spin glass systems in polynomial time, making it possible to ...

We develop an algorithm that finds the consensus among many different clustering solutions of a graph. We formulate the problem as a median set partitioning problem and propose a greedy optimization ...

Instead of being classified under mature or non-mature estates, BTO flats will now be split into three groups. Prime and Plus flats are in better locations, such as being closer to MRT stations and ...

Quadtree stands out as a pivotal data structure, especially in 2D game development. It excels at spatial partitioning, efficiently organizing and searching for objects in a hierarchical tree structure ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

Sorting is a well-known algorithm that can be implemented in other algorithms to solve biological, scientific, engineering, and big data problems. The popular sorting algorithm is Quicksort 1. It is ...

Fiber clustering methods are typically used in brain research to study the organization of white matter bundles from large diffusion MRI tractography datasets. These methods enable exploratory bundle ...