Demand for computing power—fueled largely by artificial intelligence (AI)—shows no signs of abating. Yet, as AI becomes a ...

Quantum computing will not deliver truly useful business results overnight, but the pace of progress is no longer linear; ...

The rapid advancements in Artificial Intelligence (AI) are closely intertwined with the evolution of Graphics Processing Units (GPUs). However, with ...

GPU-based sorting algorithms have emerged as a crucial area of research due to their ability to harness the immense parallel processing power inherent in modern graphics processing units.

The strategic advantage of QML continues to expand its presence in industries that deal with complex, high-dimensional data.

The PD-General framework improved computational speed by up to 800 times on a consumer-grade Nvidia RTX 4070 compared to traditional serial processing methods.

By using hand-tuned algorithms, the native rendering is halfed by resolution and then upscaled with AI to achieve higher framerates compared to what could be done natively.

In this article we’ll discuss the porting and optimization challenges of GPU computing as well as a future in which those challenges are more effectively addressed. Software-Hardware Mismatch: ...

A high-performance algorithm that could solve complicated material design problems on consumer GPUs has been developed by Chinese researchers, achieving a groundbreaking 800-fold increase in speed ...

Although quantum computing is a nascent field, there are plenty of key moments that defined it over the last few decades as scientists strive to create machines that can solve impossible problems.