Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...

Abstract: Sparse-sparse matrix multiplication (SpGEMM) is a well-studied problem on CPUs, GPUs, accelerators (e.g. FPGAs), and distributed systems. The main computational bottleneck in SpGEMM is the ...

This repository contains efficient implementations of distributed matrix operations and an item-item collaborative filtering engine using Apache Spark (RDD API) and Scala. The project demonstrates ...

Using a grid, the system designs a set of rectangular silicon structures filled with tiny pores. The system continually adjusts each pixel in the grid until it arrives at the desired mathematical ...

1. Pick your players: Search our Opta-powered database for the players or teams you want to compare by clicking the blank player cards above. You can select up to five. 2. ‘Total’ or ‘Per90’? Toggle ...

Unified Relative Representations Entities and relations are contextualised—embeddings are computed on-the-fly from the hypergraph structure, not stored in lookup tables. Hypergraph Layer Custom ...