Modern compute-heavy projects place demands on infrastructure that standard servers cannot satisfy. Artificial intelligence ...
With the ever-increasing demand for more computing performance, the HPC industry is moving towards a heterogeneous computing model, where GPUs and CPUs work together to perform general-purpose ...
Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...
Morning Overview on MSN
How CUDA turned NVIDIA into the unstoppable AI powerhouse
NVIDIA’s rise from graphics card specialist to the most closely watched company in artificial intelligence rests on a ...
For traditional HPC workloads, AMD’s MI250X is still a powerhouse when it comes to double precision floating point grunt. Toss some AI models its way, and AMD’s decision to prioritize HPC becomes ...
NVIDIA Corporation, the behemoth in the world of graphics processing units (GPUs), announced today that it had clocked the world's fastest training time for BERT-Large at 53 minutes and also trained ...
XDA Developers on MSN
Docker Model Runner makes running local LLMs easier than setting up a Minecraft server
On Docker Desktop, open Settings, go to AI, and enable Docker Model Runner. If you are on Windows with a supported NVIDIA GPU ...
GPUs, long a sideshow for CPUs, are suddenly the rising stars of the processor world. They are a first choice in everything from artificial intelligence systems to automotive ADAS applications and ...
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