Compute, power, cooling, and floor space are all being squeezed, and technology leaders must rethink the data center from the silicon upwards.

A prominent exhibitor at ISC was xFusion, a company at the HPC-AI intersection whose computing infrastructure technologies ...

As a result, energy-intensive infrastructures that try to maximize the use of renewable energy sources (RES), such as ...

Photonic systems are already quite advanced and often allow parallel processing and connection to established systems such as the optical fiber-based world-wide internet.

Distributed computing is a model where interconnected computers, or nodes, work together to solve complex problems by breaking tasks into smaller subtasks. Each node operates independently but ...

The images are of lower quality and cost half of what regular images do. One of the most exciting new features for our new V7 model is something we call “Draft Mode”.

Wafer-scale computing is almost the opposite of a distributed supercomputer. Because of its monolithic and highly parallel design, wafer-scale is most useful for workloads that involve doing one ...

It would be nice if this was built into the OS for sure, but I speak as someone who has in the past used distributed rendering, such as multiple Macs 3D rendering a single image (e.g. CrowdRender ...

Dask. From the outside, Dask looks a lot like Ray. It, too, is a library for distributed parallel computing in Python, with a built-in task scheduling system, awareness of Python data frameworks ...

Scaling AI Isn't A Computing Problem... Dedicated hardware, like GPUs (graphics processing units) and TPUs (tensor processing units), has become essential for training AI models.

In recent years, the widespread adoption of parallel computing, especially in multi-core processors and high-performance computing environments, ushered in a new era of efficiency and speed. This ...