Here are more PABLO results for your database, ServicEnginIC-

My GTX 1650 on ASUS Prime:
44,027.23sec = 12.23hrs
https://www.gpugrid.net/workunit.php?wuid=1949562

My GTX 1060 3GB on ASUS Prime
37556.23sec = 10.43hrs
https://www.gpugrid.net/workunit.php?wuid=19495626

1 PABLO task still running.

Here are more PABLO results for your database, ServicEnginIC-

My GTX 1650 on ASUS Prime:
44,027.23sec = 12.23hrs
https://www.gpugrid.net/workunit.php?wuid=1949562

My GTX 1060 3GB on ASUS Prime
37556.23sec = 10.43hrs
https://www.gpugrid.net/workunit.php?wuid=19495626

1 PABLO task still running.

ServicEnginIC, I botched the above info. please ignore it.
Here is what's correct:

My GTX 1650 on ASUS Prime:
44,027.23sec = 12.23hrs
https://www.gpugrid.net/workunit.php?wuid=19495626

My GTX 1060 3GB on ASUS Prime
37,177.73sec = 10.32hrs
https://www.gpugrid.net/workunit.php?wuid=19422730


New entries below:

My GTX 750ti 2GB on Optiplex 980
116,121.21sec = 32.25hrs
https://www.gpugrid.net/workunit.php?wuid=19730833
(a tortoise)

Found more PABLOs...

My GTX 1650 4GB on Optiplex 980
45,518.61sec = 12.64hrs
https://www.gpugrid.net/workunit.php?wuid=19740597

MyGTX 1060 3GB on ASUS Prime
37,556.23sec = 10.43hrs
https://www.gpugrid.net/workunit.php?wuid=19755484

My GTX 1650 4GB on ASUS Prime
44,103.76sec = 12.25hrs
https://www.gpugrid.net/workunit.php?wuid=19436206

That's all for now.

I'll try to throw a new comparative table on this Sunday April 26th...

I'm waiting to pick up data for better complete my original table.
Today I catched a new PABLO WU, and it is running now in a GT1030.
I still miss data for my GTX950 and GTX1050Ti...
I've got from you data for GTX750Ti and GTX1650, among several other models. Thank you!

I'll try to throw a new comparative table on this Sunday April 26th...

I'm waiting to pick up data for better complete my original table.
Today I catched a new PABLO WU, and it is running now in a GT1030.
I still miss data for my GTX950 and GTX1050Ti...
I've got from you data for GTX750Ti and GTX1650, among several other models. Thank you!

Here's one more PABLO run on my i7-7700K ASUS Prime:
GTX 1650 4GB.
4,4092.20sec = 12.25hrs.
http://www.gpugrid.net/workunit.php?wuid=19859216

Getting consistent results from these Alienware cards. Run pretty quiet for a single fan cooler at ~80% fan and a steady 59-60C @ ~24C room temp. (fan ctrl by MSI Afterburner) They run ~97% usage and ~90% power consumption running ACEMD tasks. They are factory overclocked +200MHz so I'd like to see results from a different make of card for comparison.
I think this might be the most GPU compute power per watt that NVIDIA has made so far. 🚀

I stumbled on this result while tracing a WU error history.

https://www.gpugrid.net/workunit.php?wuid=19660936

RTX 2080ti/Threadripper 3970X 🛸
13,616.88sec = 3.78hrs

For comparison against low power/low heat setups. Would like to see a Titan RTX result also...

I stumbled on this result while tracing a WU error history.

https://www.gpugrid.net/workunit.php?wuid=19660936

RTX 2080ti/Threadripper 3970X 🛸
13,616.88sec = 3.78hrs

For comparison against low power/low heat setups. Would like to see a Titan RTX result also...

Also see these results for a PABLO task on a GTX 1660S

https://www.gpugrid.net/workunit.php?wuid=19883994

GTX 1660S/ i5-9600KF/ Linux
26,123.87sec = 7.26hrs

e8s30_e2s69p4f100-PABLO_UCB_NMR_KIX_CMYB_5-0-5-RND3175

RTX 2080ti/Threadripper 3970X 🛸
13,616.88sec = 3.78hrs = 3h 46m 56.88s

This CPU is probably overcommitted, hindering the GPU's performance.

e6s59_e2s143p4f450-PABLO_UCB_NMR_KIX_CMYB_5-2-5-RND0707_0
11,969.48 sec = 3.33hrs = 3h 19m 29.48s RTX 2080Ti / i3-4160

e15s66_e5s54p0f140-PABLO_UCB_NMR_KIX_CMYB_5-0-5-RND6536_0
10,091.61 sec = 2.80hrs = 2h 48m 11.61s RTX 2080Ti / i3-4160

e7s4_e2s94p3f30-PABLO_UCB_NMR_KIX_CMYB_5-1-5-RND1904_0
9,501.28 sec = 2.64hrs = 2h 38m 21.28s RTX 2080Ti / i5-7500 (This GPU has higher clocks then the previous)

My latest Pablo on one of my RTX 2080's

https://www.gpugrid.net/workunit.php?wuid=19871635

Run time CPU time
13,218.66 13,202.01
3.67 hours

Helps if you don't over commit your cpu.

For future reference,
The OP requested a GPU TDP of 120W, but if he raised the TDP requirements by only 5 more watts, in Linux, this could include many of the RTX series.

A 2060 does the same 7Tflops at 125W, as stock, while a GTX 1660Ti does only 5.4 Tflops at 120W.
A GTX 1660Ti can be brought lower in power, and increase overclock; resulting in the same performance at (an estimated) 85W. Saves you about $40 a year on electricity.

See post here:
http://www.gpugrid.net/forum_thread.php?id=5113

A GTX 1660Ti can be brought lower in power, and increase overclock; resulting in the same performance at (an estimated) 85W. Saves you about $40 a year on electricity.

Thank you for your tip.
I add it to my list of "things to test"...

A GTX 1660Ti can be brought lower in power, and increase overclock; resulting in the same performance at (an estimated) 85W. Saves you about $40 a year on electricity.

Thank you for your tip.
I add it to my list of "things to test"...

I agree with ProDigit. I have used the same principle on my GPUs and experienced similar results.

I run GPUs power limited and have also overclocked with a power limit on both ACEMD2 and ACEMD3 work units with positive results.

Caveat
Have not tested power draw at the wall, I find it odd that greater performance can be derived by both overclocking and power limiting. Testing at the wall should be the next test to validate this method of output increase.

I've read your post, with exhaustive tests, at ProDigit's Guide: RTX (also GTX), increasing efficiency in Linux thread.
Good job!

When last ACEMD3 WUs outage arrived, I thoght it would last longer.
So, I searched for new projects in order to maintain active my GPUs, and I joined PrimeGrid.
Also, as I concluded on a previous post, I had decided to retire of production a Pascal GTX 950 GPU based graphics card, replacing it by a more efficient Turing GTX 1650 one.
I had tested four different graphics cards based on the same GTX 1650 GPU, and one dilemma arose: What would be the most convenient model for me to repeat?
- Model #1: PNY VCG16504SFPPB-O
- Model #2: ASUS TUF-GTX1650-4G-GAMING
- Model #3: ASUS DUAL-GTX1650-O4G
- Model #4: ASUS ROG-STRIX-GTX1650-O4G-GAMING

Finally, I chose a second second card of Model #4:
I've already given my reasons on [AF>Libristes] hermes Question for new gtx / rtx thread.

And as a complementary information (in close contact with this "Low power GPUs performance comparative" thread), I built a comparative table between the four tested models.
The main data for this comparative come from PrimeGrid's "Generalized Fermat Prime Search (n=20)" CUDA tasks execution.
Theese tasks are very similar in the amount of calculations required, thus being their execution times a good base for GPU's performance comparative.



Conclusions:
- Model #1: is the (negative) winner for the hottest card... But the (possitive) winner for being the most power efficient one (the least energy consumed per WU).
- Model #2: is the least factory overclocked, and therefore it is the lowest performance one, but it is rocky stable and easy to maintain cool.
- Model #3: is probably penalized for being mounted in a PCIE rev. 2.0 - DDR3 motherboard. Its boost clock is higher than the Model #1: one, but the performance for this last is higher (PCIE Rev. 3.0 - DDR4 motherboard).
- Model #4: power efficiency is penalized due to a factory TDP increase, in order to achieve higher boost clocks. But because of this, it is the winner for the highest performance (the lowest execution time).

Nice analysis of your gtx1650 GPUs. Always enjoy your technical hardware posts.

An alternate conclusion on the data presented:
For Low Power GPUs, Model #1 can be the winner if you have the time or inclination to adjust the Fan speeds of the GPU, and optimise the air flow in the Host chassis.
Model #4 offers a 2% gain in speed, but at a penalty of 11% gain in power consumption.
Considering you are comparing a "VW Polo" (PNY) to a "Ferrari" (ASUS ROG) of the GPU world, the "VW Polo" did pretty well.

It gets down to personal choice as to whether cost, raw speed, power efficiency or a combination of these factors is the goal.