Sims

Damn you :-)

Didn’t know what uBlue was, so here: https://universal-blue.org/

"The Universal Blue project builds a diverse set of continuously delivered operating system images using bootc. That’s nerdspeak for the ultimate Linux client: the reliability of a Chromebook, but with the flexibility and power of a traditional Linux desktop.

These images represent what’s possible when a community focuses on sharing best practices via automation and collaboration. One common language between dev and ops, and it’s finally come to the desktop.

We also provide tools for users to build their own image using our templates and processes, which can be used to ship custom configurations to all of your machines, or finally make the Linux distribution you’ve long wished for, but never had the tools to create.

At long last, we’ve ascended."

You can argue that a 4090 is more of a ‘flagship’ model on the consumer market, but it could be just a typing error, and then you miss the point and the knowledge you could have learned:

“Their system, FlightVGM, recorded a 30 per cent performance boost and had an energy efficiency that was 4½ times greater than Nvidia’s flagship RTX 3090 GPU – all while running on the widely available V80 FPGA chip from Advanced Micro Devices (AMD), another leading US semiconductor firm.”

So they have found a way to use a ‘off-the-shelf’ FPGA and are using it for video inference, and to me it looks like it could match a 4090(?), but who cares. With this upgrade, these standard Fpga’s are cheaper(running 24/7)/better than any consumer Nvidia GPU up to at least 3090/4090.

And here from the paper:

"[problem] …sparse VGMs [video generating models] cannot fully exploit the effective throughput (i.e., TOPS) of GPUs. FPGAs are good candidates for accelerating sparse deep learning models. However, existing FPGA accelerators still face low throughput ( < 2TOPS) on VGMs due to the significant gap in peak computing performance (PCP) with GPUs ( > 21× ).

[solution] …we propose FlightVGM, the first FPGA accelerator for efficient VGM inference with activation sparsification and hybrid precision. […] Implemented on the AMD V80 FPGA, FlightVGM surpasses NVIDIA 3090 GPU by 1.30× in performance and 4.49× in energy efficiency on various sparse VGM workloads."

You’ll have to look up what that means yourself, but expect a throng of bitcrap miner cards to be converted to VLM accelerators, and maybe give new life for older/smaller/cheaper fpga’s ?

Pretty cool with China’s focus on efficiency in the AI stack. DeepSeek was the first eye-opener for how to re-think efficiency, but it appears to happen on all levels of the stack.

Fyi: article is paywalled, so block javascript on page with ublock…