Gone are the days when the sole function for a graphics chip were, graphics. Let's explore how the GPU evolved from a modest pixel pusher into a blazing powerhouse of floating-point computation.
Gone are the days when the sole function for a graphics chip were, graphics. Let's explore how the GPU evolved from a modest pixel pusher into a blazing powerhouse of floating-point computation.
AMD's CDNA 2-powered MI250X offers just under 48 TFLOPS of FP64 throughput and 128 GB of High Bandwidth Memory (HBM2e), whereas Nvidia's GH100 chip, using its Hopper architecture, uses its 80 billion transistors to provide up to 4000 TFLOPS of INT8 tensor calculations.
The figures were chosen simply to show how the MI250X, GH100, and Ponte Vecchio have specifications that are far beyond anything one would normally experience in an everyday computer.One metric used is deliberately producing lower numbers for ....reasons.. but anyways.
So are you telling me that FP64 numbers are the same as INT8?The figures were chosen simply to show how the MI250X, GH100, and Ponte Vecchio have specifications that are far beyond anything one would normally experience in an everyday computer.
Fair enough, and I don't think this was some kind of deliberate dig at AMD, but the use of the word "whereas" in the original sentence implies it's a direct comparison of "this one does this much, but this other one does THIS much" when in reality FP64 is worlds apart from INT8 as a form of workload. I think a full stop or semicolon followed by a "meanwhile" for the nVidia and Intel mentions would have been better, since that reads more like a non-comparative statement of each of the three architectures' outputs in their intended niche.The figures were chosen simply to show how the MI250X, GH100, and Ponte Vecchio have specifications that are far beyond anything one would normally experience in an everyday computer.
Thanks for the feedback. I've updated the text slightly.I think a full stop or semicolon followed by a "meanwhile" for the nVidia and Intel mentions would have been better, since that reads more like a non-comparative statement of each of the three architectures' outputs in their intended niche.
I wonder if there will be an AI that would actually work much better on CPUs. Could something take advantage if doing different things and be more helpful than the things current AI apps doObvious. GPU's are excellent at one thing, where a X86 or X64 CPU is good at many things. When you can use all that computational power in a different way, GPU's will excel even the best CPU's.
Because GPUs do parallel processing and CPUs don't. Best analogy I read is if you took a book and gave it to a CPU, it would read each page individually.Fast forward to today, and the GPU has become one of the most dominant chips in the industry.
It's difficult to tell if your choice of sobriquet is the usual hypocritically inchoate anti-capitalist rant, or simply an assault on NVidia for besting AMD in the marketplace. Could you clarify?Its refreshing to read a balanced article instead of the typical ones that seems to come directly from Ngreedias Marketing Dept.
CPUs do parallel processing as well, and -- in extremely general terms -- in the same manner as GPUs: by adding more cores. But while a CPU may have 6, 8, or even 32 cores, the GPU in the 4090 has 16,384 cores.I don't know alot about CPU architecture , but I'm wondering what are the limitations that prevent chip design to do full on parallel processing like GPUs. My guess is has something to do with binary ?
You are looking for this:A decent read for nostalgia, but I would have liked to have seen some more detail on the section about 3DFX Voodoo. The story mentions the Voodoo5, but by then, 3dfx was about to be exited from the market as Nvidia got their act together. Voodoo 1 and 2 were kings and that was the peak for them. Voodoo 3 had some time but then it was downhill.