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 ...

AMD and Intel have teamed up to create a shared AI computing standard that could make future PCs and laptops faster at ...

A supercomputer in Shenzhen was declared the world’s fastest. It uses only standard microprocessors and not the ...

For years, DIY enthusiasts viewed the sub-seven-hundred-dollar desktop as the ultimate gateway into PC gaming. You could carefully select an entry-level processor, pair it with an affordable graphics ...

This project investigates how different multithreaded matrix multiplication strategies affect performance. The objective was to implement parallel matrix multiplication to explore how thread count, ...

D-Matrix says its chips can run inference workloads 10 times faster and using five times less energy than a standalone graphics processing unit from Nvidia. Like Cerebras, D-Matrix is trying to prove ...