Thank you, and the arithmetic is right. E = P / r, and 120 W over 1.2 GPS is 100 joules per graph. The proposal uses that exact figure as its planning anchor, and it uses your formula as more than that. Section 6.1 defines the headline ranking metric as exactly that quotient, mean wall watts over resolved graphs per second; Figure 7 is the same identity rearranged, the rate each power envelope in the field would have to sustain to reach the 100 joules per graph line. The division is not in dispute; it is the program’s own instrument. What it needs is two measured inputs, and for the hardware this program is about, neither exists yet.
Apply the method to the machine the last bounty produced. The M1 Ultra miner sustains 0.8 graphs per second. To match the G1 Mini at 100 J/graph, that Mac Studio has to draw 80 W at the wall while mining. To beat the favourable end of iPollo’s own tolerance band, 81.8 J/graph, it has to hold about 65 W. Nobody knows whether it does.
Apple publishes an idle figure and a stress maximum for the chassis, and a memory-bound miner sits at an unmeasured point between them. Feed the division the 215 W stress ceiling and the Mac lands at 269 joules per graph, worse than every anchor in the field; feed it the 80 W it would need and it matches the ASIC nameplate. Same formula, same machine, opposite verdicts, the inputs are doing all the work, and the inputs are unmeasured.
There is no published wall trace for a Mac running this workload anywhere in the record. Figure 3 of the proposal lines up the public efficiency anchors, and the Apple row is the one marked “no published wall energy record.” Closing that row is the program’s first measurement.
The other anchors are taken at different boundaries, so division cannot compare them. Your 100 J/graph is whole-device at the wall. The RTX 5090’s 217 divides software-reported board power with the host computer excluded entirely. Supply conversion alone puts a floor under that exclusion: at 434 W of device draw, an 80 Plus Gold unit dissipates 38 to 48 W just delivering the power - 92 or 90 percent efficient at half load, on a 230 or 115 volt line - another 19 to 24 J/graph before the CPU, motherboard, RAM, storage or fans draw a watt.
My own A100 figure of 184 carries the same hole. A Mac Studio has no host to exclude; it is the host. The prevailing convention flatters discrete GPUs against exactly the class of hardware under evaluation. This is not a house rule of mine, either: the SPEC power methodology the protocol binds itself to cautions directly against comparing AC and DC referenced results. Division propagates a boundary mismatch. It cannot repair one.
One boundary choice the proposal makes explicit, in Section 6.1: gross whole-system energy is the headline, and incremental energy above a matched idle baseline is reported beside it as a labelled diagnostic. That is the number that matters to an owner whose machine is on anyway, and it never substitutes for the ranking figure.
The denominator is only fixed on the ASIC, and even there it moves: the rating is plus or minus ten percent on both inputs, a stock unit is reported on this forum at 0.9 to 1.1 GPS, and the community firmware held a unit at 1.31 to 1.34 for 24 hours. On general-purpose hardware, r is a property of the solver. The solver behind the 0.8 GPS figure was built to what the bounty paid for: speed, with minimal cycle loss. Energy never entered the objective function. Every engineering decision pushed toward peak throughput, and the operating points below the peak have never been swept. On a memory-bandwidth-bound workload that is where the efficient point tends to sit, because compute running flat out while it waits on DRAM is throughput-neutral and watt-expensive.
Hypothesis H1 states that principle for power-constrained GPUs, research question 6 asks it of Apple silicon, and the Month 2 plan sweeps stock, maximum-stable and best-efficiency operating points on every accessible platform. Whatever the meter reads on day one is the untuned end of that curve. And r has to be a correct r: a solver that silently drops cycles reports a flattering graph rate and a flattering J/graph, which is why the correctness and recall gates sit ahead of every energy claim.
Division answers what a G1 Mini costs to run. The funding question is whether open software on hardware people already own can compete, and there the same formula returns unknown on every input, with the general-purpose side sitting at the untuned end of its curve. A plug meter on one machine is an afternoon. A ranking the community can act on takes one boundary, a frozen workload, a physically measured iPollo in place of a nameplate, and raw traces published whichever way they fall. That is the program. If the numbers come back badly, the deliverable stands: the exact threshold future silicon has to clear, learned at the gate instead of after a build.