GPU wallet/core - yes it would be really, really, really fast

[jl777]

if you want really fast speed, you can make a CUDA/OpenSSL version of iguana and use a dedicated core per bundle, among other optimizations.

With most all the data being read only, the biggest challenge of GPU coding (out of sync data between cores) is already solved.

It might take a few GPU cards to store all the dataset, but then all RPC, even ones that need to scan the entire blockchain happens in milliseconds

using the CPU for the latest bundle can create a system that keeps up with new blocks.

Who said there was a scaling problem with bitcoin?

James

 

[sickpig]

@jl777

your talking about leveraging graphic devices to validate txs, scanning the block chain data, etc. etc. right?

 

[jl777]

I am talking about stuffing the entire iguana dataset of 200 parallel files into N GPU's
Then make the bitcoin RPC layer query all of them in parallel along with the main CPU process for the current blocks.

So this would be after the dataset is created. The need to scan 200 bundles takes on the order of a millisecond, which in some cases is too slow. Using 8 cores you can get it to 100 microseconds, but that still might be too slow in some cases.

Using a multi-GPU setup, the overhead to start a new task will dominate the time, but using a pipeline of tasks to get the throughput maximized, I think time per RPC can get to the order of 10 microseconds or even 1 microsecond.

Basically the entire blockchain becomes a paralleldataflow piece of hardware. And by "per RPC", I mean RPC like listunspent for any address, even multisig

Since normal iguana on a decent hardware will be plenty fast, there is no need for the above, but I like to always have some ideas ready made to make things faster, smaller, more secure, etc

 

[Chronos]

From what I can tell, the general goal of scaling purists is to allow the average consumer the ability to run a full node at home.

It might take a few GPU cards to store all the dataset

Since the average person don't own "a few" GPU cards, an argument could be made that this isn't really an acceptable level of scaling.

I still think it's a pretty cool idea.

 

[jl777]

then 2.5 millisecond performance must be accepted for importprivkey and listunspents

as that is what the iguana is getting on low end laptop. the codebase is portable C and as such it can exist in many different hardware configs, from no hardware at all in a virtualized JS sandbox, to multi-GPU

 

[Chronos]

Considering that I can't even blink in 2.5 milliseconds, that seems fast enough my importprivkey needs.

 

[jl777]

it really isnt doing anything with importprivkey as all addresses are in the dataset, but yes the vanilla iguana is plenty fast

 

[jhon14]

Thank you jl777 !
when you say: "and use a dedicated core per bundle, among other optimizations.", what other optimizations you mean?

 

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