Research team proposed new data placement algorithms for scratch-pad memory (SPM) in embedded systems. Their fine-grained and ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

The core concept of MicroAlgo's multi-simulator collaborative subgraph isomorphism algorithm is to decompose large quantum circuits into multiple smaller sub-circuits, leveraging parallel and ...

At present, there are two main types of multi-constraint graph pattern matching algorithms. One is composed of two core modules, that is, the matching of pattern edges and the connection of matching ...

This algorithm delves into some of the most important primitives in graph algorithms: iterative convergence to solutions, graph partitioning, and multi-source shortest path ... vertices in topological ...

Parallel computing continues to advance, addressing the demands of high-performance tasks such as deep learning, scientific simulations, and data-intensive computations. A fundamental operation within ...

However, most of distributed and parallel graph algorithms in the MPC model are designed for static graphs. Dynamic graph algorithms can deal with graph changes more efficiently than the ...

The flowchart of the hierarchical forward-backward sweep power flow algorithm based on the distribution ... The BSP computation model is the core technology for parallel computation in graph databases ...

multi-level API to enable both high-level pipeline-style use and more advanced use where efficient parallel ... substitution algorithms (LU, Cholesky, SVD, QR), FFT etc. As you can see, many of the ...