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p1esk 5 hours ago

A100 FP32 throughput “at its limit”: 19.5 TFLOP/s.

AMD EPYC 9965 FP32 throughput “at its limit”: 41.2 TFLOP/s (192 cores x 64 FP32 FLOP/cycle/core x 3.35GHz).

zzzoom 14 minutes ago | parent | next [-]

EPYC 9965: 614GBps of 12-channel DDR5-6400

A100: 1935GBps of HBM2e

Most of those FLOPS are constrained by memory bandwidth.

an hour ago | parent | prev | next [-]

[deleted]

tosh 5 hours ago | parent | prev [-]

A100: 312 TFLOP/s for FP16

but it is very impressive how far modern CPUs get as well (also in smart phones!)

p1esk 4 hours ago | parent [-]

Intel Xeon 6980P: 128 cores x 1024 FP16 FLOP/cycle/core x 3.2 GHz: 419 TFLOP/s

tosh 3 hours ago | parent [-]

I'm not saying "GPU more brrt than CPU"

I found the comparison interesting

on Intel Xeon 690P with 419 TFLOP/s it is still (maybe even more?) interesting to ask:

how much throughput can you reach with Python, Python with lib x, y, z, with C++ like this, with C++ like that etc etc and why?

no?

	▲	p1esk 3 hours ago \| parent [-]
		No one in their right mind would use pure Python to do matrix multiplication. It’s like using a screwdriver to hammer nails into wood. But this discussion is even more bizarre than comparing a screwdriver to a hammer, it’s like comparing a screwdriver to a nail.