Abstract: The demand for high-speed matrix multiplication continues to grow due to recent developments in images processing, graphics processing, digital signal processing and communication via ...
Abstract: Graph convolutional networks (GCNs) are emerging neural network models designed to process graph-structured data. Due to massively parallel computations using irregular data structures by ...
Nvidia challenger D-Matrix is entering full production of an AI chip it says is 10 times faster than a GPU and bypasses the memory shortage.
This project investigates how different multithreaded matrix multiplication strategies affect performance. The objective was to implement parallel matrix multiplication to explore how thread count, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results