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Table of Contents
Decompression - Pool vs Solo
Compressed plots work with a guides:plotting:tradeoff|“time-space” tradeoff, removing parts of the plot and recreating them on the fly during farming. This latter part means that whenever a (partial) proof is fetched, additional computational resources will be utilised, compared to the OG uncompressed plots (C0). In this guide, we try to quantify how much extra resources are used for a farmer due to “recomputation”/“decompression” in a pool vis-à-vis if they were farming solo. We make a distinction between
- quality recomputations: passing the plot filter
- proof recomputations: performing a (partial) proof lookup
note: for simplicity we use k32 and plotfilter 512
Quality Recomputations
For every signage point (9216 per day), a k32 has a 1/512 chance to pass the plotfilter. When passing the filter, a quality string lookup needs to be performed. In the case of compressed plots, this means part of the plot must now be recomputed. That means that for every signage point, 1/512 = 0.001953125 expected recomputations per k32.
Proof Recomputations
When pooling, every k32 is expected to produce 10 point per day on average. Reiterating that at
- difficulty 1, that is 10 (partial) proofs per day of 1 point,
- difficulty 10, that is 1 (partial) proof per day of 10 points,
- difficulty 100, that is 0.1 (partial) proofs per day of 100 points,
- etc.
That means that with difficulty 1 for every signage point, 10/9216 = 0.001085069444 expected recomputations per k32.
Pool vs Solo
Putting those together, we see that*
- a solo farmer is doing 1/512 recomputations per signage point
- a poolfarmer with difficulty 1 is doing 1/512 + 10/9216 recomputations per signage point
That means that the poolfarmer incurs an overhead of ~56% at plotfilter 512. And half of that at plotfilter 216. This overhead decreases linearly with pool difficulty, so that
| Pool Difficulty | Overhead | |
|---|---|---|
| plotfilter 512 | plotfilter 256 | |
| 1 | 56% | 28% |
| 5 | 11% | 6% |
| 10 | 6% | 3% |
| 50 | 1% | 0,5% |
| 100 | 0,5% | 0,3% |
| 500 | 0,1% | 0,06% |
*for simplicity we ignore recomputations for actual blocks
The implication of this is that the computational overhead due to pooling could be said to be directly independent of farm size, although indirectly large farmers generally have a higher pool difficulty.
TIP: When farming compressed plots in a pool, consider increasing your difficulty a bit. e.g. from 3 minutes per partial, to 6 minutes per partial. See https://xchdata.io/diffcalc to choose your optimal difficulty.