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GTX 1070 is 5.25GH/s on XVC (Blake-256 8 round), pulling 150W - this gives it a MH/s/W value of 35MH/s/W.

I'd like to stress that it's 14nm. With my full-custom design on one of my 28nm FPGAs, I get 2.1GH/s at 24W - this gives it an MH/s/W value of 87.5MH/s/W.

As it is, this fight is one-sided. If they had been manufactured on the same node, it wouldn't be a fight - it would be an execution.

well not fair to compare a gpu with fpga, fpga can do well one thing at time, then you need to reprogram it, gpu can do multiple things

it will consume more energy because of that, if gpu were specialized only on mining, they would be just asic, so yes it's not all about nm productive process

Yeah, but my point was, from a mining perspective, a GPU and an FPGA can both mine many algos. The FPGA may be somewhat more restricted in selection, but it can still switch. So comparing raw hash/watt as a measure of merit is faulty, unless what I pointed out holds as well.

FPGAs are in a completely different class... You could lump ASICs into that comparison too. They also can mine multiple algos... They just have to be built from the ground up each and every time. To that extent, so do miners for GPUs (depending on how different the algo is from other ones already made), but the time requirement is quite a bit different.

ASICs can't mine multiple algos unless they're made to from the start. You can buy an FPGA ONCE and reprogram it - a GPU is closer to this. You don't have to get a new GPU every algo.

Sure, but often times you have to completely reprogram the thing from the ground up. They're both in a different class of products from GPUs.

You do realize GPUs are pretty much the same, except they expose an instruction set, correct?

Something about memory, horsepower too (computational units), instruction sets they support, and operating environment. Even if you can do one thing really well with a FPGA (much like a ASIC), that doesn't mean it'll do everything else pretty much equally as ewll. There is a reason FPGAs have always been the stepping stone to ASICs. Because if you're going to take enough time to program for a FPGA, you can just take that one step further and start designing the chip too, which adds a lot more flexibility when it comes to efficiency and raw horsepower (more of whatever you need to produce a certain amount of hashrate, less of whatever isn't being used) and allows your clientele to easily implement them (a box you plug in). The level of expertise you need for each of those goes up quite a bit hoping from GPU > FPGA > ASIC.

Like I said, there is pretty much three classes, GPUs, ASICs, and FPGAs. FPGAs are like the experimentation ground for ASICs. There are CPUs too, but GPUs can do almost everything CPUs can better, especially when it comes to cryptos.

Of course it won't do everything equally as well. You're totally missing the point - you don't need to buy another GPU for an algo, you don't need to buy another FPGA for an algo, you DO need another ASIC for one. FPGAs have memory, plenty more horsepower depending on the task, and if you makes you happy, you can make them accept instructions to perform tasks, as well.

Yeah, and I'm taking it one step further and looking at the software side as well as hardware.

Lets say a new algo comes out. Is it just as easy to update a FPGA as it is ccminer to mine it? The answer is no. If it were, everyone would be using FPGAs instead of GPUs.

And yes, sometimes your FPGA can't handle a algo so you need a different make or model that has the assets you need (like memory).

It's not JUST AS EASY - it's a different skillset. Again, you assume because you can't do something, it's a rare talent. And not if you put memory onboard. You can do this, you know.

...it is a rare talent. Hence why FPGAs aren't everywhere... XD Heart surgeon is just another skillset. 'Just because you can't do it, doesn't mean it's rare talent.'

Yeah, you can just add memory to your FPGA? Throw some GDDR5 chips or HBM on there for fun? You mean buy one with it already on it or build one from the ground up (which is no different from just building a ASIC).

Curiously could someone confirm the 'actual' rate from yiimp? It seems unlikely it's earning about 30% more per MH for Lbry then coinmine/mnpool/suprnova, basically every other pool.

Buy an FPGA with 4GB of memory - simple. Then it doesn't need replacing. Your same argument applies if an algo needs 16GB and the GPU has 8 - oh, you need to buy another GPU!

Can you recommend a pci-e card that's useful for learning/understanding FPGA? Not too expensive, but not too small that I can't do anything serious with it.

PCI-E? Not really - since I haven't used any, and those tend to be more on the expensive side. I have a Nexys 4 DDR, Nexys Video, and Genesys 2 from Digilent, though - the Nexys Video might best suit your needs.

You realize DDR isn't the same thing as GDDR right?

You realize they both store data, right?

Yeah and because of that they're equal or are you arguing semantics, where because you can purchase a FPGA with memory it'll work perfectly fine for memory hard algos?

Curiously how is your Ethereum FPGA working out? Oh? No? Okay...

Like I said, they're just like ASICs in that you can't use them for every algo, they're somewhat more flexible then ASICs, but at the end of the day you still can't use them for everything.

YOU are arguing semantics - the point was that they can do it.

Also, just because Eth is better on GPU than most FPGA doesn't mean shit - it CAN be done on FPGA, it's just not as good. It's better for some things, not for others.

They can do it if they're capable of actually doing it. That was the whole point of what we're talking about, you're taking a position that a FPGA is just a better GPU. I took the position that a FPGA is somewhere in between a GPU and a ASIC, in that it can do more then a ASIC, but not nearly as much as a GPU (hence a different class they represent and why you can't actively compared a FPGA to a GPU).

Literally just proved the point by showing that FPGAs can't do everything a GPU can do, you said it's semantics.

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FPGAs are in a completely different class... You could lump ASICs into that comparison too. They also can mine multiple algos... They just have to be built from the ground up each and every time. To that extent, so do miners for GPUs (depending on how different the algo is from other ones already made), but the time requirement is quite a bit different.

The whole memory bit was about needing to buy different FPGAs for different algos, much like ASICs, because depending on what you're mining, a FPGA can't always do it. You don't need a new FPGA for every algo, but you do for others... Still once again somewhere in between GPUs and ASICs.