A new computing era arrives with the breakthrough in how computers can sort information. This vital function, at the heart of ...

Two former Google DeepMind researchers who worked on the company’s Nobel Prize-winning AlphaFold protein structure prediction AI as well as its AlphaEvolve code generation system have launched a new ...

FuriosaAI founder and CEO June Paik said his startup’s architecture can reshape an industry dominated by Nvidia (NASDAQ: NVDA ...

This project demonstrates the use of the MapReduce framework to solve the matrix multiplication problem. Matrix multiplication is a common computational task in fields like scientific computing, ...

When you create an algorithm, you need to include precise, step-by-step instructions. This means you will need to break down the task or problem into smaller steps. We call this process decomposition.

Abstract: Algorithms in cryptosystem such as RSA and Diffie-Hellman require the large integer multiplication. This paper introduces classical Knuth multiplication, Karatsuba multiplication and their ...

Abstract: The Travelling Salesman Problem (TSP) is a well known method for the optimisation problem that asks you to find the shortest route that visits each city in a set exactly once and then goes ...

The goal of this assignment is to implement high-performance CUDA kernels for tensor operations and integrate them with the MiniTorch framework. You will implement low-level operators in CUDA C++ and ...