Inside The Massive GPU Buildout At Meta Platforms
If you handle hundreds of trillions of AI model executions per day, and are going to change that by one or two orders of magnitude as GenAI goes mainstream, you are going to need GPUs. …
If you handle hundreds of trillions of AI model executions per day, and are going to change that by one or two orders of magnitude as GenAI goes mainstream, you are going to need GPUs. …
For a lot of state universities in the United States, and their equivalent political organizations of regions or provinces in other nations across the globe, it is a lot easier to find extremely interested undergraduate and graduate students who want to contribute to the font of knowledge in high performance computing than it is to find the budget to build a top-notch supercomputer of reasonable scale. …
Riding high on the AI hype cycle, Lambda – formerly known as Lambda Labs and well known to readers of The Next Platform – has received a $320 million cash infusion to expand its GPU cloud to support training clusters spanning thousands of Nvidia’s top specced accelerators. …
The melding of low and high precision mathematics to accelerate the pace of scientific discovery has been a topic of discussion for some time now. …
We have five decades of very fine-grained analysis of CPU compute engines in the datacenter, and changes come at a steady but glacial pace when it comes to CPU serving. …
Since the advent of distributed computing, there has been a tension between the tight coherency of memory and its compute within a node – the base level of a unit of compute – and the looser coherency over the network across those nodes. …
It has been two and a half decades since we have seen a rapidly expanding universe of a new kind of compute that rivals the current generative AI boom. …
Timing is a funny thing. The summer of 2006 when AMD bought GPU maker ATI Technologies for $5.6 billion and took on both Intel in CPUs and Nvidia in GPUs was the same summer when researchers first started figuring out how to offload single-precision floating point math operations from CPUs to Nvidia GPUs to try to accelerate HPC simulation and modeling workloads. …
Heaven forbid that we take a few days of downtime. When we were not looking – and forcing ourselves to not look at any IT news because we have other things going on – that is the moment when Nvidia decides to put out a financial presentation that embeds a new product roadmap within it. …
The history of computing teaches us that software always and necessarily lags hardware, and unfortunately that lag can stretch for many years when it comes to wringing the best performance out of iron by tweaking algorithms. …
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