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AMD Alveo V70 AI inference accelerator card

xilinx.com

11–20 of 94 posts

Re: AMD Alveo V70 AI inference accelerator card

#11
AMD XDNA – Versal AI Core / 2nd-gen AIE-ML tiles

Are these programmable by the end-user? The "software programmability" section describes "Vitis AI" frameworks supported. But can we write our own software on these?

Is this card FPGA-based?

EDIT: [1] more info on the AI-engine tiles: scalar cores + "adaptable hardware (FPGA?)" + {AI+DSP}.

[1] https://www.xilinx.com/products/technology/ai-engine.html

Re: AMD Alveo V70 AI inference accelerator card

#12

AMD XDNA – Versal AI Core / 2nd-gen AIE-ML tiles Are these programmable by the end-user? The "software programmability" section describes "Vitis AI" frameworks supported. But can we write our own software on these? Is this card FPGA-based? EDIT: [1] more info on the AI-engine tiles: scalar cores + "adaptable hardware (FPGA?)" + {AI+DSP}. [1] https://www.xilinx.com/products/technology/ai-engine.html

Says RDNA based which is AMD's GPU tech.

Re: AMD Alveo V70 AI inference accelerator card

#15
post #5

What TOPS means exactly in "... TOPS*|(INT8) 404 ..." ?

TOPS - Trillions of Operations Per Second, used as a benchmark to figure out the performance of the accelerator. In my experience, mostly a marketing number, higher TOPS doesn't actually mean it'll be faster than something with a lower TOPS. As always, you need to do your own benchmarks with your use case in mind.

What kind of operations is not clear. Wether it's a simple logic operation or a FMA is big difference.

Re: AMD Alveo V70 AI inference accelerator card

#16

AMD XDNA – Versal AI Core / 2nd-gen AIE-ML tiles Are these programmable by the end-user? The "software programmability" section describes "Vitis AI" frameworks supported. But can we write our own software on these? Is this card FPGA-based? EDIT: [1] more info on the AI-engine tiles: scalar cores + "adaptable hardware (FPGA?)" + {AI+DSP}. [1] https://www.xilinx.com/products/technology/ai-engine.html

It's very likely FPGA-based; Xilinx is an FPGA company. This is being pitched as an "AI accelerator", but "Alveo" as a product line existed before AMD's acquisition of Xilinx, and other "Alveo" products exist (https://www.xilinx.com/products/boards-and-kits/alveo.html) that are marketed for other purposes, while really just being Xilinx FPGAs pre-programmed to perform specific other tasks, with some domain-specific DSPs + interconnects around the edges.

It's possible that AMD could have reworked an existing Xilinx design to incorporate RDNA chiplets in place of some of the FPGA-gate-grid chiplets, creating a heterogeneous mesh; but I find it just as likely that AMD just took their VLSI for an RDNA core and loaded it onto the existing FPGA.

Re: AMD Alveo V70 AI inference accelerator card

#17
post #12

AMD XDNA – Versal AI Core / 2nd-gen AIE-ML tiles Are these programmable by the end-user? The "software programmability" section describes "Vitis AI" frameworks supported. But can we write our own software on these? Is this card FPGA-based? EDIT: [1] more info on the AI-engine tiles: scalar cores + "adaptable hardware (FPGA?)" + {AI+DSP}. [1] https://www.xilinx.com/products/technology/ai-engine.html

Says RDNA based which is AMD's GPU tech.

No, it says XDNA.

Re: AMD Alveo V70 AI inference accelerator card

#18
post #13

> High-Density Video Decoder**: 96 channels of 1920x1080p > [...] > **: @10 fps, H.264/H.265 Is 10 fps a standard measure for this kind of thing?

10 fps should be fast enough to provide input tensors for real time inference with small scale transformers / convolutional nets.

Re: AMD Alveo V70 AI inference accelerator card

#19

Douglas Adams said we'd have robots to watch TV for us. That seems to be the designed use case for this. 16gb RAM / 96 video channels ... I haven't done any of that work but it feels like they expect that "96" not to be fully used in practice.

I have no problem imagining a security camera application needing to monitor quite a few video channels.

Re: AMD Alveo V70 AI inference accelerator card

#20

AMD XDNA – Versal AI Core / 2nd-gen AIE-ML tiles Are these programmable by the end-user? The "software programmability" section describes "Vitis AI" frameworks supported. But can we write our own software on these? Is this card FPGA-based? EDIT: [1] more info on the AI-engine tiles: scalar cores + "adaptable hardware (FPGA?)" + {AI+DSP}. [1] https://www.xilinx.com/products/technology/ai-engine.html

Interesting. It seems then that the xdna architecture in the Ryzen 4070 is nothing more than a port of the existing Xilinx Versal cores (fpga+ai engine)
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