Posts Tagged ‘low energy algorithms


Lately there is much talk about power efficiency of various mining algorithms and with the summer here people with GPU mining rigs are looking for algorithms that use less power and thus the video cards run cooler and quieter. We are starting a series of tests with GeForce GTX 750 Ti GPU first and then we are also going to move to other popular video cards for mining crypto currencies such as the Radeon R9 280X for example.


On the photo above you can see the power usage of the GTX 750 Ti video card in idle as well as the idle power usage of the whole system we are using for testing; below you can find the specifications of the hardware. Note that one of the power meters measures only the power usage of the video card (the power meter is attached to the power line going to the card directly and all power going to it passes through the meter, so it does not take into account the PSU power efficiency) and the other one is for the whole system measured at the wall (the actual full power consumption) taking into account the efficiency of the power supply (extra power wasted as heat during the conversion).

The systems we are using for the tests include:
– Palit GeForce GTX 750 Ti StormX OC 2GB video card
– Intel i3-4130 dual-core CPU at 3.4 GHz
– Asus H81M-A Motherboard
– 2x 4GB A-DATA DDR3 1600 MHz Memory
– 1TB Seagate 7200 RPM Hard drive
– 500W Cooler Master Power Supply


We have used ccMiner for our tests, the latest fork with Fresh algorithm support and we have measured the power usage of the GPU only as well as of the whole system with all of the supported algorithms by that particular version of ccMiner. Do note that if mining for Scrypt for example you will be getting higher power usage, but this is already pretty pointless to be done with GPUs with so many Scrypt ASIC miners already deployed. The results we’ve seen on the GTX 750 Ti are pretty interesting; it seems that the most power efficient algorithms are Fugue256 and HEFTY1 with the new Fresh algorithm following close by with the same power usage as Qubit. The worst performing crypto algorithms on GTX 750 Ti are the Groestl-based ones and the X-ones are pretty much in the middle. Do note however that these are the results measured on GTX 750 Ti, the situation with AMD with the same algorithms may differ significantly and we do plan to run some tests to check the situation there as well, so stay tuned for more very soon, probably tomorrow.


Since there were some questions and people doubting our measurements, we have repeated the tests with another power meter connected to measure the power going only to the video card and the results are pretty much the same as with the previous meter in terms of power usage as you can see on the photo above. Do note that the Palit GeForce GTX 750 Ti video card that we have used for testing does not have an external PCI-E power connector available, so all of the power going to the video card is from the PCI-E slot. So in order to measure the exact power used by the video card we have used a powered PCI Express x1-x16 USB 3.0 Extender. This extender does not use USB 3.0 interface, just a USB 3.0 data cable for the transmission of data between the PCI-E slot on the motherboard and the video card (no power is transmitted over that cable). Instead the power provided to the video card all goes through the 4-pin Molex power connector on the extender’s board. Also do note that the power measured is coming directly from the power supply, so this measurement for the power usage of the GPU does not take into account the power efficiency of the power supply (loses of power during the conversion from 110V/220V to 12V) and depending on the power supply there will be about 10-20% of extra power lost as heat during the conversion. This power is measured by the second power meter that does measure the full system’s power consumption at the power socket however.