The Roads To Zettascale And Quantum Computing Are Long And Winding
In the United States, the first step on the road to exascale HPC systems began with a series of workshops in 2007. …
In the United States, the first step on the road to exascale HPC systems began with a series of workshops in 2007. …
Variety is not only the spice of life, it is also the way to drive innovation and to mitigate risk. …
Large language models, also known as AI foundation models and part of a broader category of AI transformer models, have been growing at an exponential pace in terms of the number of parameters they can process and the amount of compute and memory bandwidth capacity they require. …
It has been becoming increasingly clear – anecdotally at least – just how expensive it is to train large language models and recommender systems, which are arguably the two most important workloads driving AI into the enterprise. …
Changing the compute paradigm in the datacenter, or even extending it or augmenting it in some fashion, is no easy task. …
When we last focused on Untether AI in 2021, the AI inferencing hardware startup had just secured $125 million in funding, which came a year after the company officially launched with its first-generation runAI200 devices and its unique at-memory inferencing approach. …
In March, Nvidia introduced its GH100, the first GPU based on the new “Hopper” architecture, which is aimed at both HPC and AI workloads, and importantly for the latter, supports an eight-bit FP8 floating point processing format. …
When it comes to building any platform, the hardware is the easiest part and, for many of us, the fun part. …
UPDATED* Perhaps Janet Jackson should be the official spokesperson of the supercomputing industry. …
We have been excited about the possibilities of adding tiers of memory to systems, particularly persistent memories that are less expensive than DRAM but offer similar-enough performance and functionality to be useful. …
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