(source)On January 1, Eric Driver wrote: I just released the new app version for Linux Nvidia Cuda.
I tested it on 100 WUs and it averaged about 33% faster over the previous Cuda version.
I am now making these same improvements to the openCL versions. If all goes well, I should have new apps for Windows and AMD cards within a week.
I started testing for performance-per-Watt.
Code: Select all
power draw GetDecics
computer at the wall throughput efficiency
------------------------------------------------------------------
dual Epyc 7452 @155W 320 W 360,000 PPD 1,125 PPD/W
dual E5-2696 v4 @2.8 GHz 400 W 180,000 PPD 450 PPD/W
------------------------------------------------------------------
dual GTX 1080Ti @180W ¹ 267 W 64,800 PPD 240 PPD/W
dual GTX 1080Ti @180W ² 280 W 79,300 PPD 280 PPD/W
Operating system is Linux on all computers.
The EPYCs ran at their default package power tracking limit, and ended up using a core clock of circa 2.7 GHz. The Xeons were locked in to their all-core turbo clock.
The Nvidia GTXs were fed by an i7-7700K, with turbo boost disabled in the BIOS, nothing else but an idle Cinnamon desktop active. The CPU typically clocked at 3.4 GHz. In the 1st GPU test, some cores occasionally clock down to ~1 GHz. Note that GTX 1080Ti's default board power target is 250 W, but I configured it down to 180 W here.
The difference between the two GPU tests:
¹) ran one task at a time per GPU, which resulted in ~85 % shader utilization and < 110 W GPU power usage
²) ran two tasks at a time per GPU, 100 % shader utilization, < 115 W GPU power
app_config.xml for running two tasks at once per GPU:
Code: Select all
<app_config>
<app>
<name>GetDecics</name>
<gpu_versions>
<gpu_usage>0.5</gpu_usage>
<cpu_usage>0.01</cpu_usage>
</gpu_versions>
</app>
</app_config>