Double geometric method: Hopping-proof, low-variance reward system - page 3.

Meni Rosenfeld

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Quote from: doublec on April 18, 2013, 09:19:30 AM

I'm a bit confused about the term "fixed fee" vs average total fee" mentioned in the OP and what they mean. Is the "average total fee" the average fee the pool operator receives over the long term? Or is 'f' the fee the pool operator expects to receive over the long term?

I ask because I notice, for example, a pool that states it has a 1% DGM fee but parameters "f=-0.25, c=0.2, o=0.8". This makes the "average total fee" 0 which makes me think that that isn't the fee the pool is expecting to get on average.

What the pool operator receives over the long term is the average total fee, f+c-fc.

A pool with f=-0.25, c=0.2 indeed has 0% fee. You might be talking about OzCoin; the parameters displayed might be a relic from the time it was 0-fee, I don't know what parameters they actually use now. It's possible they added an additional 1% fee on top of the method formula; that defeats the purpose of having a parameter f for that.

doublec

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I'm a bit confused about the term "fixed fee" vs average total fee" mentioned in the OP and what they mean. Is the "average total fee" the average fee the pool operator receives over the long term? Or is 'f' the fee the pool operator expects to receive over the long term?

I ask because I notice, for example, a pool that states it has a 1% DGM fee but parameters "f=-0.25, c=0.2, o=0.8". This makes the "average total fee" 0 which makes me think that that isn't the fee the pool is expecting to get on average.

Meni Rosenfeld

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Quote from: techwtf on April 14, 2013, 07:14:08 AM

(some code snippet...)

Code:

def share(user, diff=1):
  global worker, p, s, B
  my_r = Decimal(1.0) + p * diff * c_1 * o_1 / c
  score = p * diff * B * s
  s = s * my_r
  worker[user] = worker.get(user, Decimal(0.0)) + score

def estimate(user):
  global worker, r, f, p, s
  score = worker.get(user, Decimal(0.0))
  return score * (r - Decimal(1.0)) * (Decimal(1.0) - f) / (p * s)

Did I handle the var diff right? in linear model. p is always 1/D.

A small but important correction: The last line should be

Code:

return score * (r - Decimal(1.0)) * (Decimal(1.0) - f) / (diff * p * s)

(Extra diff in the denominator.)

In addition:

1. The function "estimate" seems to return the reward that should be given to the user for a block just founds, but the name seems to suggest something else.

2. Make sure the r used in the reward calculation is based on the current p.

techwtf

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(some code snippet...)

Code:

def share(user, diff=1):
global worker, p, s, B
my_r = Decimal(1.0) + p * diff * c_1 * o_1 / c
score = p * diff * B * s
s = s * my_r
worker[user] = worker.get(user, Decimal(0.0)) + score

def estimate(user):
global worker, r, f, p, s
score = worker.get(user, Decimal(0.0))
return score * (r - Decimal(1.0)) * (Decimal(1.0) - f) / (p * s)

Did I handle the var diff right? in linear model. p is always 1/D.

Bicknellski

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Meni Rosenfeld

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Quote from: Syloq on November 15, 2012, 12:09:52 PM

Quote from: Meni Rosenfeld on November 15, 2012, 11:14:22 AM

Quote from: Syloq on November 15, 2012, 11:01:22 AM

Quote from: Meni Rosenfeld on September 09, 2012, 09:22:12 AM

Quote from: doublec on September 09, 2012, 08:01:12 AM

What changes should be made to the DGM calculation in the presence of miners that are mining at different difficulty levels? For example, a pool that dynamically adjusts difficulty based on the users hashrate, or one that allows the user to select their own target value?

It's more or less the same, but instead of p=1/D you should use throughout p=d/D, where d is the difficulty of the current share submitted.

Pardon my ignorance to this issue but I was looking over your initial post and I was trying to understand why with a variable share difficulty that p would turn into d/D? Wouldn't it be 1/d? I guess I don't understand where D comes into play with variable share difficulty.

p is the probability that a share will be a block. If the global difficulty is D and the share difficulty is the standard 1 then p=1/D. If the share difficulty is d then p=d/D.

Ah, so it should have always been d/D? Where d was always 1 until now?

Exactly.

Syloq

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Quote from: Meni Rosenfeld on November 15, 2012, 11:14:22 AM

Quote from: Syloq on November 15, 2012, 11:01:22 AM

Quote from: Meni Rosenfeld on September 09, 2012, 09:22:12 AM

Quote from: doublec on September 09, 2012, 08:01:12 AM

What changes should be made to the DGM calculation in the presence of miners that are mining at different difficulty levels? For example, a pool that dynamically adjusts difficulty based on the users hashrate, or one that allows the user to select their own target value?

It's more or less the same, but instead of p=1/D you should use throughout p=d/D, where d is the difficulty of the current share submitted.

Pardon my ignorance to this issue but I was looking over your initial post and I was trying to understand why with a variable share difficulty that p would turn into d/D? Wouldn't it be 1/d? I guess I don't understand where D comes into play with variable share difficulty.

p is the probability that a share will be a block. If the global difficulty is D and the share difficulty is the standard 1 then p=1/D. If the share difficulty is d then p=d/D.

Ah, so it should have always been d/D? Where d was always 1 until now?

Meni Rosenfeld

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Quote from: Syloq on November 15, 2012, 11:01:22 AM

Quote from: Meni Rosenfeld on September 09, 2012, 09:22:12 AM

Quote from: doublec on September 09, 2012, 08:01:12 AM

What changes should be made to the DGM calculation in the presence of miners that are mining at different difficulty levels? For example, a pool that dynamically adjusts difficulty based on the users hashrate, or one that allows the user to select their own target value?

It's more or less the same, but instead of p=1/D you should use throughout p=d/D, where d is the difficulty of the current share submitted.

Pardon my ignorance to this issue but I was looking over your initial post and I was trying to understand why with a variable share difficulty that p would turn into d/D? Wouldn't it be 1/d? I guess I don't understand where D comes into play with variable share difficulty.

p is the probability that a share will be a block. If the global difficulty is D and the share difficulty is the standard 1 then p=1/D. If the share difficulty is d then p=d/D.

Syloq

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Quote from: Meni Rosenfeld on September 09, 2012, 09:22:12 AM

Quote from: doublec on September 09, 2012, 08:01:12 AM

What changes should be made to the DGM calculation in the presence of miners that are mining at different difficulty levels? For example, a pool that dynamically adjusts difficulty based on the users hashrate, or one that allows the user to select their own target value?

It's more or less the same, but instead of p=1/D you should use throughout p=d/D, where d is the difficulty of the current share submitted.

Pardon my ignorance to this issue but I was looking over your initial post and I was trying to understand why with a variable share difficulty that p would turn into d/D? Wouldn't it be 1/d? I guess I don't understand where D comes into play with variable share difficulty.

Meni Rosenfeld

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Quote from: doublec on September 09, 2012, 08:01:12 AM

What changes should be made to the DGM calculation in the presence of miners that are mining at different difficulty levels? For example, a pool that dynamically adjusts difficulty based on the users hashrate, or one that allows the user to select their own target value?

It's more or less the same, but instead of p=1/D you should use throughout p=d/D, where d is the difficulty of the current share submitted.

doublec

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What changes should be made to the DGM calculation in the presence of miners that are mining at different difficulty levels? For example, a pool that dynamically adjusts difficulty based on the users hashrate, or one that allows the user to select their own target value?

Graet

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Lots of miners moving around atm, questions on DGM being asked
time for a bump to make this thread easier to find Cheesy

Meni Rosenfeld

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Quote from: kano on May 11, 2012, 04:52:59 PM

Quote from: Meni Rosenfeld on March 18, 2012, 10:12:48 AM

...

Quote from: kano on March 18, 2012, 09:53:01 AM

As for bankruptcy payout - the main problem I'd see there from DGM vs PPS (or some of the different PPS) is that no one can probably work out the owed amount on DGM since there is a future component to that, that depends on the future also.
On PPS it's pretty simple.

You can calculate the expected future payment for a given score. (Actually, you can parametrize it so that the expected payout is the score). The operator should pay that out so that miners won't suffer (I'm assuming a deterministic payout is considered better than a variable payout of the same expectation). The total score of all miners is bounded, and the operator should have this as an additional reserve - he should declare bankruptcy before he becomes unable to offer a cashout.

Just thought I'd mention that you seem to be discussing exactly what I was referring to here ...

Expected payout is one thing, variance is another, maturity time is another. Expected payout is the most important and easiest to calculate, and it's safe to refer to it as the amount owed.

Quote from: organofcorti on May 11, 2012, 08:42:34 PM

Quote from: Meni Rosenfeld on May 11, 2012, 10:47:55 AM

It should be possible to create a dataset by running for various parameters, and then interpolating for all other values. Then each pool can show values or graphs for their chosen parameters, and allow the user to set his hashrate with a slider to his how specific results. I have reason to believe that the variance is affine in the miner's hashrate (at least approximately), so that simplifies things. If the interpolation can be done easily enough, maybe the pool can also give sliders for seeing the results for various DGM parameters.

The important parameters being f, c, o, and miner hashrate as a proportion of pool hashrate? Let me know if I missed anything.

A measure of the miner's intermittency would also be good to have.

Quote from: organofcorti on May 11, 2012, 08:42:34 PM

Quote

By the way, in AoBPMRS I mentioned that it's not strictly necessary that all miners in a pool will have the same parameters. So it could be possible for miners to choose their own parameters based on their desired performance metrics.

I didn't see that mentioned explicitly - is it implied?

It's fairly explicit in section 7.4, "Heterogeneous pools".

Quote from: Graet on May 11, 2012, 10:57:47 PM

so miner average hashrate and pool average hashrate over the round
to be able to make that assumption - cheers

Variability in pool hashrate is in a sense equivalent to variability in miner hashrate, which I think should be included. One issue is that the specific form of variability will be different, but perhaps it is possible to encode it approximately with a single value.

Graet

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so miner average hashrate and pool average hashrate over the round
to be able to make that assumption - cheers

organofcorti

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Poor impulse control.

I think you need to assume a miner's hashrate is a constant proportion of the pool's hashrate, excepting when variance in share submission is a variable of interest.

Graet

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Quote from: organofcorti on May 11, 2012, 08:42:34 PM

The important parameters being f, c, o, and miner hashrate as a proportion of pool hashrate? Let me know if I missed anything.

is this assuming a "stable " hashrate through the round
with proxy miners, gpumax miners and some leftover hoppers using us as backup etc coming and going our hashrate can vary significantly within 1 round
eg
https://ozcoin.net/content/hashrate

organofcorti

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Poor impulse control.

Quote from: Meni Rosenfeld on May 11, 2012, 10:47:55 AM

It should be possible to create a dataset by running for various parameters, and then interpolating for all other values. Then each pool can show values or graphs for their chosen parameters, and allow the user to set his hashrate with a slider to his how specific results. I have reason to believe that the variance is affine in the miner's hashrate (at least approximately), so that simplifies things. If the interpolation can be done easily enough, maybe the pool can also give sliders for seeing the results for various DGM parameters.

The important parameters being f, c, o, and miner hashrate as a proportion of pool hashrate? Let me know if I missed anything.

Quote

By the way, in AoBPMRS I mentioned that it's not strictly necessary that all miners in a pool will have the same parameters. So it could be possible for miners to choose their own parameters based on their desired performance metrics.

I didn't see that mentioned explicitly - is it implied?

organofcorti

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Poor impulse control.

Quote from: kano on May 11, 2012, 04:52:59 PM

...

Quote from: kano on March 18, 2012, 09:53:01 AM

As for bankruptcy payout - the main problem I'd see there from DGM vs PPS (or some of the different PPS) is that no one can probably work out the owed amount on DGM since there is a future component to that, that depends on the future also.
On PPS it's pretty simple.

That's not really what I meant. I don't want to see how parameters affect the 'owed amount' , but rather the variance in payout and maturity time. If the score is calculated to represent the 'owed amount', then a graphical illustration of the effects of changing parameters wouldn't be necessary. Unless I'm not following you?

kano

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Linux since 1997 RedHat 4

Quote from: Meni Rosenfeld on March 18, 2012, 10:12:48 AM

...

Quote from: kano on March 18, 2012, 09:53:01 AM

As for bankruptcy payout - the main problem I'd see there from DGM vs PPS (or some of the different PPS) is that no one can probably work out the owed amount on DGM since there is a future component to that, that depends on the future also.
On PPS it's pretty simple.

You can calculate the expected future payment for a given score. (Actually, you can parametrize it so that the expected payout is the score). The operator should pay that out so that miners won't suffer (I'm assuming a deterministic payout is considered better than a variable payout of the same expectation). The total score of all miners is bounded, and the operator should have this as an additional reserve - he should declare bankruptcy before he becomes unable to offer a cashout.

Just thought I'd mention that you seem to be discussing exactly what I was referring to here ...

Meni Rosenfeld

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Quote from: organofcorti on May 11, 2012, 10:39:07 AM

Quote from: Meni Rosenfeld on May 11, 2012, 10:26:07 AM

One problem is that I don't know of a simple calculation that will give the variance and maturity time as a function of the parameters. Also, there is more than one kind of variance. If there is demand for this I'll try to work on some approximations or charts or something. For now there's the variance for a single share in the OP, it's relevant for very small or intermittent miners, and as you can see it's a mouthful.

Thinking about it some more, even listing the single share variance wouldn't be a very good indicator for a general miner. Charted data from a simulation might be a better bet, but I'm not sure how you'd select a set of exemplars that would cover all (or most) situations of interest to a miner. For example, would you need to have separate large and small miner simulation results? Plus, each pool would have to run their own simulation to illustrate what effects their variable choices have on the performance metrics of the examplars selected.

It should be possible to create a dataset by running for various parameters, and then interpolating for all other values. Then each pool can show values or graphs for their chosen parameters, and allow the user to set his hashrate with a slider to his how specific results. I have reason to believe that the variance is affine in the miner's hashrate (at least approximately), so that simplifies things. If the interpolation can be done easily enough, maybe the pool can also give sliders for seeing the results for various DGM parameters.

By the way, in AoBPMRS I mentioned that it's not strictly necessary that all miners in a pool will have the same parameters. So it could be possible for miners to choose their own parameters based on their desired performance metrics.

Topic: Double geometric method: Hopping-proof, low-variance reward system - page 3. (Read 75585 times)