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Like ML training and inference?

by sliken 4y ago

dotnet00 4y ago
The M1 sits near the bottom of NVIDIA's GPU lineup in terms of ML performance. Putting it just slightly ahead of the $200 1660ti. When doing a quick Google search on the topic, it turned out that several of the top results were blatantly misleading in that they limited the competing hardware to match the M1's limitations. For example, the top result, a wandb article [1] claims that the M1 is competitive with the V100, yet their own data shows that they aren't even fully utilizing the V100 and that when properly utilized it obviously totally outperforms the M1. https://wandb.ai/vanpelt/m1-benchmark/reports/Can-Apple-s-M1-Help-You-Train-Models-Faster-Cheaper-Than-NVIDIA-s-V100---VmlldzozNTkyMzg https://wandb.ai/vanpelt/m1-benchmark/reports/Can-Apple-s-M1... Similarly, Apple in its marketing for the M1 Ultra was extremely manipulative, bordering on outright lying, when it compared the chip to the 3090. It presented them on a "relative performance vs power" graph making it look like the chip matched the 3090 while consuming less than half the power, when what it was saying was that it's more efficient than the 3090 when you underutilize the 3090 to the point of matching the M1 Ultra's performance.
- sliken 4y ago
  Agreed on deceptive marketing. I dug around and found some M2 updates. Seems that generally, Nvidia laptops drop to a small fraction when on battery. Examples: 3dmark wild life. M2 max = 150 fps, 3080 ti 120 fps, 3080 Ti unplugged = 27fps. Blender 3d rendering: m2 max = 1:04 3080ti = :29 3080ti = 3:25 Lightroom: m2 max = :39 3080 Ti =:51 unplugged = 1:29 DR18 6k braw editing: m2 max = 0:55 3080 ti = 2:40 unplugged = 15 minutes For ML comparing 3070 vs M2 max, 3 batch sizes: CIFAR-10 m2 max = 242, 280, 327 RTX 3070 = 240, 283, 328 However for AI/ML duty the apple neural engine (ANE) looks pretty promising. On Densenet 121 the ANE on the M2 max is almost 7 times faster than the M2 Max GPU. Seems like the M2 max does pretty well compared to a plugged in RTX 3070 to 3080 Ti. The big bonuses is that you can use all ram (not limited to VRAM of 10-16gb) and you get the same performance even on battery.

Like ML training and inference?

by sliken 4y ago

Like ML training and inference?

The M1 sits near the bottom of NVIDIA's GPU lineup in terms of ML performance. Putting it just slightly ahead of the $200 1660ti. When doing a quick Google search on the topic, it turned out that several of the top results were blatantly misleading in that they limited the competing hardware to match the M1's limitations. For example, the top result, a wandb article [1] claims that the M1 is competitive with the V100, yet their own data shows that they aren't even fully utilizing the V100 and that when properly utilized it obviously totally outperforms the M1. https://wandb.ai/vanpelt/m1-benchmark/reports/Can-Apple-s-M1-Help-You-Train-Models-Faster-Cheaper-Than-NVIDIA-s-V100---VmlldzozNTkyMzg https://wandb.ai/vanpelt/m1-benchmark/reports/Can-Apple-s-M1... Similarly, Apple in its marketing for the M1 Ultra was extremely manipulative, bordering on outright lying, when it compared the chip to the 3090. It presented them on a "relative performance vs power" graph making it look like the chip matched the 3090 while consuming less than half the power, when what it was saying was that it's more efficient than the 3090 when you underutilize the 3090 to the point of matching the M1 Ultra's performance.

sliken 4y ago
Agreed on deceptive marketing. I dug around and found some M2 updates. Seems that generally, Nvidia laptops drop to a small fraction when on battery. Examples: 3dmark wild life. M2 max = 150 fps, 3080 ti 120 fps, 3080 Ti unplugged = 27fps. Blender 3d rendering: m2 max = 1:04 3080ti = :29 3080ti = 3:25 Lightroom: m2 max = :39 3080 Ti =:51 unplugged = 1:29 DR18 6k braw editing: m2 max = 0:55 3080 ti = 2:40 unplugged = 15 minutes For ML comparing 3070 vs M2 max, 3 batch sizes: CIFAR-10 m2 max = 242, 280, 327 RTX 3070 = 240, 283, 328 However for AI/ML duty the apple neural engine (ANE) looks pretty promising. On Densenet 121 the ANE on the M2 max is almost 7 times faster than the M2 Max GPU. Seems like the M2 max does pretty well compared to a plugged in RTX 3070 to 3080 Ti. The big bonuses is that you can use all ram (not limited to VRAM of 10-16gb) and you get the same performance even on battery.