4 ms·
It is quite interesting than on FP16 RTX Titan kicks RTX3080 ass and on FP32 it's the opposite.
by tasubotadas 6y ago
It is quite interesting than on FP16 RTX Titan kicks RTX3080 ass and on FP32 it's the opposite.
- liuliu 6y agoThe number on RTX Titan for fp16 is actually a bit foreign to me (3.5x faster than fp32). Not sure what's going on (maybe they tweaked batch size to fit more in GPU memory?). Need to wait more comprehensive ones. (The older numbers looks more inline with what I remember and here is an alternative benchmark for RTX Titan showed similar: https://lambdalabs.com/blog/titan-rtx-tensorflow-benchmarks/ https://lambdalabs.com/blog/titan-rtx-tensorflow-benchmarks/)
- dr_zoidberg 6y agoYou're using half as much memory for something that is vaguely O(n^2), so there's your roughly 4x factor speedup. But since things aren't perfect, it ends up being a bit lower.
- EvgeniyZh 6y agoThey boosted FP32 performance but now FP16 is 1:1 to FP32 cuda cores